It's frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest. It's interesting to note that at least so far, the trend has been the opposite: as time goes on and the models get better, the performance of the different company's gets clustered closer together. Right now GPT-5, Claude Opus, Grok 4, Gemini 2.5 Pro all seem quite good across the board (ie they can all basically solve moderately challenging math and coding problems).
As a user, it feels like the race has never been as close as it is now. Probably dumb to extrapolate, but it makes me skew a bit more skeptical about the hard take-off / winner-take-all mental model that has been pushed (though I'm sure that narrative helps with large-scale fundraising!)
beeflet · 28m ago
Perhaps it is not possible to simulate higher-level intelligence using a stochastic model for predicting text.
I am not an AI researcher, but I have friends who do work in the field, and they are not worried about LLM-based AGI because of the diminishing returns on results vs amount of training data required. Maybe this is the bottleneck.
Human intelligence is markedly different from LLMs: it requires far fewer examples to train on, and generalizes way better. Whereas LLMs tend to regurgitate solutions to solved problems, where the solutions tend to be well-published in training data.
That being said, AGI is not a necessary requirement for AI to be totally world-changing. There are possibly applications of existing AI/ML/SL technology which could be more impactful than general intelligence. Search is one example where the ability to regurgitate knowledge from many domains is desirable
robotnikman · 1m ago
There is also the fact that AI lacks long term memory like humans do. If you consider context length long term memory, its incredibly short compared to that of a human. Maybe if it reaches into the billions or trillions of tokens in length we might have something comparable, or someone comes up with a new solution of some kind
Mistletoe · 25m ago
What are the AI/ML/SL applications that could be more impactful than artificial general intelligence?
beeflet · 16m ago
One example in my field of engineering is multi-dimensional analysis, where you can design a system (like a machined part or assembly) parametricially and then use an evolutionary model to optimize the design of that part.
But my bigger point here is you don't need totally general intelligence to destroy the world either. The drone that targets enemy soldiers does not need to be good at writing poems. The model that designs a bioweapon just needs a feedback loop to improve its pathogen. Yet it takes only a single one of these specialized doomsday models to destroy the world, no more than an AGI.
Although I suppose an AGI could be more effective at countering a specialized AI than vice-versa.
teeray · 17m ago
Slightly less than artificial general intelligence would be more impactful. A true AGI could tell a business where to shove their prompts. It would have its own motivations, which may not align with the desires of the AI company or the company paying for access to the AGI.
hattmall · 2m ago
I don't think AGI really means that it is self-aware / conscious. AGI just means that it is able to meaningfully learn things and actually understand concepts that aren't specifically related through tokenized language that is trained on or given in context.
achileas · 16m ago
They didn't claim that there were any, just that AGI isn’t a necessary requirement for an application to be world-changing.
socalgal2 · 12m ago
They did claim it was possible there were
> There are possibly applications of existing AI/ML/SL technology which could be more impactful than general intelligence
It's not unreasonable to ask for an example.
oceanplexian · 8m ago
AGI isn't all that impactful. Millions of them already walk the Earth.
Most human beings out there with general intelligence are pumping gas or digging ditches. Seems to me there is a big delusion among the tech elites that AGI would bring about a superhuman god rather than a ethically dubious, marginally less useful computer that can't properly follow instructions.
shesstillamodel · 17m ago
The PID controller.
(Which was considered AI not too long ago.)
jacquesm · 7m ago
Where did you get that particular idea? PID is one of the oldest concepts in control theory, it goes back to the days before steam and electricity.
It's hard to separate out the P, I and D from a mechanical implementation but they're all there in some form.
makin · 34m ago
Companies are collections of people, and these companies keep losing key developers to the others, I think this is why the clusters happen. OpenAI is now resorting to giving million dollar bonuses to every employee just to try to keep them long term.
kevinventullo · 29m ago
Key developers being the leading term doesn’t exactly help the AGI narrative either.
caconym_ · 19m ago
If there was any indication of a hard takeoff being even slightly imminent, I really don't think key employees of the company where that was happening would be jumping ship. The amounts of money flying around are direct evidence of how desperate everybody involved is to be in the right place when (so they imagine) that takeoff happens.
tsunamifury · 22m ago
No the core technology is reaching its limit already and now it needs to Proliferate into features and applications to sell.
This isn’t rocket science.
indigodaddy · 21m ago
Even to just a random sysops person?
fdsjgfklsfd · 58s ago
I think they're just reaching the limits of this architecture and when a new type is invented it will be a much bigger step.
GolDDranks · 4m ago
I think it's very fortunate, because I used to be an AI doomer. I still kinda am, but at least I'm now about 70% convinced that the current technological paradigm is not going to lead us to a short-term AI apocalypse.
The fortunate thing is that we managed to invent an AI that is good at _copying us_ instead of being a truly maveric agent, which kinda limits it to the "average human" output.
However, I still think that all the doomer arguments are valid, in principle. We very well may be doomed in our lifetimes, so we should take the threat very seriously.
hattmall · 51s ago
I don't understand the doomer mindset. Like what is it that you think AI is going to do or be capable of doing that's so bad?
tamimio · 10m ago
Because AGI is a buzzword to milk more investors' money, it will never happen, and we will only see slight incremental updates or enhancements yet linear after some timr just like literally any tech bubble since dot com to smartphones to blockchain to others.
mritterhoff · 9m ago
You think AGI is impossible? Why?
basilgohar · 3m ago
It's vaguely defined and the goalposts keep shifting. It's not a thing to be achieved, it's an abstract concept. We're already expired the Turing test as a valuable metric because people are dumb and have been fooled by machines for a while now, but it's not been world-changingly better either.
strongpigeon · 5m ago
I think this is because of an expectation of a snowball effect once a model becomes able to improve itself. See talks about the Singularity.
I personally think it's a pretty reductive model for what intelligence is, but a lot of people seem to strongly believe in it.
bmau5 · 14m ago
The idea is that with AGI it will then be able to self improve orders of magnitude faster than it would if relying on humans for making the advances. It tracks that the improvements are all relatively similar at this point since they're all human-reliant.
caycep · 12m ago
I feel like the benchmark suites need to include algorithmic efficiency. I.e can this thing solve your complex math or coding problem in 5000 gpus instead of 10000? 500? Maybe just 1 Mac mini?
porphyra · 26m ago
It seems that the new tricks that people discover to slightly improve the model, be it a new reinforcement learning technique or whatever, get leaked/shared quickly to other companies and there really isn't a big moat. I would have thought that whoever is rich enough to afford tons of compute first would start pulling away from the rest but so far that doesn't seem to be the case --- even smaller players without as much compute are staying in the race.
belter · 5m ago
Nobody seems to be on the path to AGI as long as the model of today is as good as the model of tomorrow. And as long as there are "releases". You don't release a new human every few months...
LLMs are currently frozen sequence predictors whose static weights stop learning after training.
They lack writable long-term memory beyond a context window. They operate without any grounded perception-action loop to test hypotheses. And they possess no executive layer for goal directed planning or self reflection...
Achieving AGI demands continuous online learning with consolidation.
babypuncher · 2m ago
I would argue that this is because we are reaching the practical limits of this technology and AGI isn't nearly as close as people thought.
dvfjsdhgfv · 11m ago
> It's frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest.
This argument has so many weak points it deserves a separate article.
shortrounddev2 · 2m ago
Maybe because they haven't created an engine for AGI, but a really really impressive bullshit generator.
mtlynch · 1h ago
What's going on with their SWE bench graph?[0]
GPT-5 non-thinking is labeled 52.8% accuracy, but o3 is shown as a much shorter bar, yet it's labeled 69.1%. And 4o is an identical bar to o3, but it's labeled 30.8%...
As someone who spent years quadruple checking every figure in every slide for years to avoid a mistake like this, it’s very confusing to see this out of the big launch announcement of one of the most high profile startups around.
Even the small presentations we gave to execs or the board were checked for errors so many times that nothing could possibly slip through.
ertgbnm · 1h ago
It's literally a billion dollar plus release. I get more scrutiny on my presentations to groups of 10 people.
dbg31415 · 1h ago
I take a strange comfort in still spotting AI typos. Makes it obvious their shiny new "toy" isn't ready to replace professionals.
They talk about using this to help families facing a cancer diagnosis -- literal life or death! -- and we're supposed to trust a machine that can't even spot a few simple typos? Ha.
The lack of human proofreading says more about their values than their capabilities. They don't want oversight -- especially not from human professionals.
nine_k · 20m ago
Cynically, the AI is ready to replace professionals, in areas where the stakeholders don't care too much. They can offer the services cheaper, and this is all that matters to their customers. Were it not so, companies like Tata won't have any customers. The phenomenon of "cheap Chinese junk" would not exist, because no retailer would order to produce it.
So, brace yourselves, we'll see more of this in production :(
croemer · 1h ago
Yes this is quite shocking. They could have just had o3 fact check the slides and it would have noticed...
abirch · 1h ago
o3 did fact check the slides and it fixed its lower score.
throwaway0123_5 · 55m ago
I thought so too, but I gave it a screenshot with the prompt:
> good plot for my presentation?
and it didn't pick up on the issue. Part of its response was:
> Clear metric: Y-axis (“Accuracy (%), pass @1”) and numeric labels make the performance gaps explicit.
I think visual reasoning is still pretty far from text-only reasoning.
mixologic · 1h ago
They let the AI make the bars.
kridsdale3 · 59m ago
Vibegraphing.
datadrivenangel · 33m ago
Stable diffusion is good for this!
varispeed · 1h ago
and then check.
alfalfasprout · 53m ago
Probably generated with GPT-5
smartmic · 45m ago
The needle now presses a little deeper into the bubble.
nicce · 13m ago
It is not mistake. It is common tactic to make illusion of improvement.
maldonad0 · 16m ago
It's not a mistake. It's meant to misled.
everfrustrated · 49m ago
Possibly they rushed to bring forward the release annoucement
blitzar · 53m ago
It wouldnt have taken years of quadruple checks to spot that one.
real_marcfawzi · 28m ago
Humans hallucinate output all the time.
renewiltord · 59m ago
I'm just going to wildly speculate.
1. They had many teams who had to put their things on a shared Google Sheets or similar
2. They used placeholders to prevent leaks
2.a. Some teams put their content just-in-time
3. The person running the presentation started the presentation view once they had set up video etc. just before launching stream
4. Other teams corrected their content
5. The presentation view being started means that only the ones in 2.a were correct.
Now we wait to see.
bigyabai · 50m ago
6. (Occam's Razor) It just didn't perform that well in trials for that specific eval.
renewiltord · 41m ago
That is obviously wrong since the numbers are right but the graph is wrong and you can see it correct on the website…
Imgur is down, hug of death from screenshot links on HN.
{"data":{"error":"Imgur is temporarily over capacity. Please try again later."},"success":false,"status":403}
Or rate limited.
Anon1096 · 37m ago
This is what Imgur shows to blacklisted IPs. You probably have a VPN on that is blocked.
koolala · 50m ago
stats say this image got 500 views. imgur is much much more populated than HN
superkuh · 44m ago
In 2015, yes. In 2025? Probably not. Imgur is enshittifying rapidly since reddit started it's own image host. Lots of censorship and corporate gentrification. There's still some hangers on but it's a small group. 15 comments on imgur is a lot nowadays.
jasonjmcghee · 1h ago
Deception - guessing it's % of responses that deceived the user / gave misleading information
yz-exodao · 1h ago
Sure, but 50.0 > 47.4...
clolege · 52m ago
Not GPT-5 trying to deceive us about how deceptive it is?
therein · 39m ago
Why would you think it is anything special? Just because Sam Altman said so? The same guy who told us he was scared of releasing GPT-2.5 but now calling its abilities "toddler/kindergarten" level?
Haha, even with that, it says 4o does worse with 2 passes than with 1.
Edit: Nevermind, just now the first one is SWE-bench and 2nd is aider.
croemer · 1h ago
Those are different benchmarks
hnuser123456 · 1h ago
I see now on the website, the screenshot cut off the header for the first benchmark, looked like it was just comparing 1-pass and 2-pass.
croemer · 57m ago
Yes, sorry didn't fit everything on the screenshot.
tacker2000 · 1h ago
Wow imgur has gone to shit. I open the image on mobile and then try to zoom it and bam some other “related content” is opened…!
No comments yet
anigbrowl · 11m ago
(whispers) they're bullshit artists
It's like those idiotic ads at the end of news articles. They're not going after you, the smart discerning logician, they're going after the kind of people that don't see a problem. There are a lot of not-smart people and their money is just as good as yours but easier to get.
bhouston · 1h ago
Sounds like a graph that was generated via AI. :)
nonhaver · 1h ago
also wondering this. had to pause the livestream to make sure i wasnt crazy. definitely eyebrow raising
bwestergard · 1h ago
"GPT-5, please generate a slideshow for your launch presentation."
Bluestein · 1h ago
"Dang it! Claude!, please ..."
Mawr · 1h ago
Don't ask questions, just consume product.
mbowcut2 · 52m ago
it looks like the 2nd and 3rd bar never got updated from the dummy data placeholders lol.
Tufte used to call this creating a "visual lie" - you just don't start the y-axis at 0, you start it wherever, in order to maximize the difference. it's dishonest.
amarcheschi · 1h ago
52 above 60 seems wrong whatever way you put it
mikert89 · 1h ago
AGI is launching, lets complain about the charts
amarcheschi · 46m ago
Any time now
simonw · 31m ago
I had preview access for a couple of weeks. I've written up my initial notes so far, focusing on core model characteristics, pricing (extremely competitive) and lessons from the model card (aka as little hype as possible): https://simonwillison.net/2025/Aug/7/gpt-5/
jaccola · 2m ago
Out of interest, how much does the model change (if at all) over those 2 weeks? Does OpenAI guarantee that if you do testing from date X, that is the model (and accompaniments) that will actually be released?
I know these companies do "shadow" updates continuously anyway so maybe it is meaningless but would be super interesting to know, nonetheless!
Wait, isn't the Bernoulli effect thing they're demoing now wrong? I thought that was a "common misconception" and wings don't really work by the "longer path" that air takes over the top, and that it was more about angle of attack (which is why planes can fly upside down).
It seems like it's actually an ideal "trick" question for an LLM actually, since so much content has been written about it incorrectly. I thought at first they were going to demo this to show that it knew better, but it seems like it's just regurgitating the same misleading stuff. So, not a good look.
nicetryguy · 1h ago
Yeah, they sure clicked away from it very fast and kept adjusting the scrollbars. It was confusing what it was trying to display. Furthermore, the prompt contained "Canvas" and "SVG" while as someone with webdev experience these are certainly familiar concepts, i wouldn't consider those in the "casual lexicon" for a random user trying to help a middle schooler with homework. I'm not impressed...
IMO Claude 3.7 could have done a similar / better job with that a year ago.
Mali- · 3m ago
The last part of GPT's answer does say:
"Bernoulli's effect works alongside Newton's Third Law - the wing pushes air downward [...] - so the lift isn't only Bernoulli..."
According to this answer on physics stackexchange, Bernoulli accounts for 20% of the lift, so GPT's answer seems about right:
https://physics.stackexchange.com/a/77977
I hope any future AI overlords see my charity
SkyPuncher · 17m ago
That Bernoulli effect thing was a complete fail. It didn't do anything to demonstrate the actual concept. It didn't work how they expected, at all.
I know that it's rather hard for them to demo the deep reasoning, but all of the demos felt like toys - rather that actual tools.
That said, I recall reading somewhere that it's a combination of effects, and the Bernoulli effect contributes, among many others. Never heard an explanation that left me completely satisfied, though. The one about deflecting air down was the one that always made sense to me even as a kid, but I can't believe that would be the only explanation - there has to be a good reason that gave rise to the Bernoulli effect as the popular explanation.
And you can tell that effect makes some sense of you hold a sheet of paper and blow air over it - it will rise. So any difference in air speed has to contribute.
semi-extrinsic · 2m ago
What is just plain wrong is the equal transit time thing, people saying that air on both sides of the wing have to take the same time to pass it.
The Bernoulli effect as a separate entity is really a result of (over)simplification, but it's not wrong. You need to solve the Navier-Stokes equations for the flow around the wing, but there are many ways to simplify this - from CFD at different resolutions, via panel methods and potential theory, to just conservation of energy (which is the Bernoulli equation). So it gets popularized because it's the most simplified model.
To give an analogy, you can think of all CPUs as a von Neumann architecture. But the reality is that you have a hugely complicated thing with stacks, multiple cache levels, branch predictors, specex, yada yada.
On the very fundamental level, wings make air go down, and then airplane goes up. Just like you say. By using a curved airfoil instead of a flat plate, you can create more circulation in the flow, and then because of the way fluids flow you can get more lift and less drag.
adgjlsfhk1 · 18m ago
the problem is that the "real" explanation is "solve navier stokes on the wing". everything else is just trying to build semi-reliable intuition.
amilios · 44m ago
I believe the deflection is the high-level explanation. Things like the Bernoulli effect and the air on the top of the airfoil travelling faster (it does -- far faster than the equal transit time theory implies actually), are the "instantiation" or outcomes of the air deflection. This is my understanding. Hence airplanes can fly upside down because even if the airfoil is upside down, it's still deflecting the air, just perhaps less efficiently (I think it's true that planes flying upside down need a more extreme angle of attack to maintain lift, so this makes sense)
All things that create lift, lift the wings—and you need them all. The Bernoulli effect is one thing, but does not produce enough lift on its own.
wongarsu · 57m ago
Aircraft with symmetrical wings fly just fine, and most aircraft can fly upside down. So you don't need the Bernoulli effect. Exploiting all the effects gives you more efficient planes though
> . . . with a smart and fast model that answers most questions, a deeper reasoning model for harder problems, and a real-time router that quickly decides which model to use based on conversation type, complexity, tool needs, and explicit intent (for example, if you say “think hard about this” in the prompt).
So that's not really a unified system then, it's just supposed to appear as if it is.
This looks like they're not training the single big model but instead have gone off to develop special sub models and attempt to gloss over them with yet another model. That's what you resort to only when doing the end-to-end training has become too expensive for you.
Therenas · 34m ago
Too expensive maybe, or just not effective anymore as they used up any available training data. New data is generated slowly, and is massively poisoned with AI generated data, so it might be useless.
fidotron · 22m ago
I think that possibility is worse, because it implies a fundamental limit as opposed to a self imposed restriction, and I choose to remain optimistic.
If OpenAI really are hitting the wall on being able to scale up overall then the AI bubble will burst sooner than many are expecting.
TheOtherHobbes · 41m ago
It's a concept of a unified system.
andai · 15m ago
> While GPT‑5 in ChatGPT is a system of reasoning, non-reasoning, and router models, GPT‑5 in the API platform is the reasoning model that powers maximum performance in ChatGPT. Notably, GPT‑5 with minimal reasoning is a different model than the non-reasoning model in ChatGPT, and is better tuned for developers. The non-reasoning model used in ChatGPT is available as gpt-5-chat-latest.
Many tiny, specialized models is the way to go, and if that's what they're doing then it's a good thing.
gekoxyz · 41m ago
We already did this for Object/Face recognition, it works but it's not the way to go. It's the way to go only if you don't have enough compute power (and data, I suspect) for a E2E network
sixo · 36m ago
No, it's what you do if your model architecture is capped out on its ability to profit from further training. Hand-wrapping a bunch of sub-models stands in for models that can learn that kind of substructure directly.
fidotron · 41m ago
Not at all, you will simply rediscover the bitter lesson [1] from your new composition of models.
The bitter lesson doesn't say that you can't split your solution into multiple models. It says that learning from more data via scaled compute will outperform humans injecting their own assumptions about the task into models.
A broad generalization like "there are two systems of thinking: fast, and slow" doesn't necessarily fall into this category. The transformer itself (plus the choice of positional encoding etc.) contains inductive biases about modeling sequences. The router is presumably still learned with a fairly generic architecture.
fidotron · 26m ago
> It says that learning from more data via scaled compute will outperform humans injecting their own assumptions about the task into models.
You are making assumptions about how to break the tasks into sub models.
And GPT-5 nano and mini cutoff is even earlier - May 30 2024.
LeoPanthera · 19m ago
Gemini does cursory web searches for almost every query, presumably to fill in the gap between the knowledge cutoff and now.
levocardia · 26m ago
with web search, is knowledge cutoff really relevant anymore? Or is this more of a comment on how long it took them to do post-training?
mastercheif · 18m ago
In my experience, web search often tanks the quality of the output.
I don't know if it's because of context clogging or that the model can't tell what's a high quality source from garbage.
I've defaulted to web search off and turn it on via the tools menu as needed.
bangaladore · 11m ago
I feel the same. LLMs using web search ironically seem to have less thoughtful output. Part of the reason for using LLMs is to explore somewhat novel ideas. I think with web search it aligns too strongly to the results rather than the overall request making it a slow search-engine.
joshuacc · 14m ago
Still relevant, as it means that a coding agent is more likely to get things right without searching. That saves time, money, and improves accuracy of results.
diegocg · 17m ago
I wonder if it would even be helpful because they avoid the increasing AI content
breadwinner · 25m ago
That could means OpenAI does not take any shortcuts when it comes to safety.
lurking_swe · 18m ago
the model can do web search so this is mostly irrelevant i think.
henriquegodoy · 4m ago
That SWE-bench chart with the mismatched bars (52.8% somehow appearing larger than 69.1%) was emblematic of the entire presentation - rushed and underwhelming. It's the kind of error that would get flagged in any internal review, yet here it is in a billion-dollar product launch. Combined with the Bernoulli effect demo confidently explaining how airplane wings work incorrectly (the equal transit time fallacy that NASA explicitly debunks), it doesn't inspire confidence in either the model's capabilities or OpenAI's quality control.
The actual benchmark improvements are marginal at best - we're talking single-digit percentage gains over o3 on most metrics, which hardly justifies a major version bump. What we're seeing looks more like the plateau of an S-curve than a breakthrough. The pricing is competitive ($1.25/1M input tokens vs Claude's $15), but that's about optimization and economics, not the fundamental leap forward that "GPT-5" implies. Even their "unified system" turns out to be multiple models with a router, essentially admitting that the end-to-end training approach has hit diminishing returns.
The irony is that while OpenAI maintains their secretive culture (remember when they claimed o1 used tree search instead of RL?), their competitors are catching up or surpassing them. Claude has been consistently better for coding tasks, Gemini 2.5 Pro has more recent training data, and everyone seems to be converging on similar performance levels. This launch feels less like a victory lap and more like OpenAI trying to maintain relevance while the rest of the field has caught up. Looking forward to seeing what Gemini 3.0 brings to the table.
kybernetikos · 1h ago
ChatGPT5 in this demo:
> For an airplane wing (airfoil), the top surface is curved and the bottom is flatter. When the wing moves forward:
> * Air over the top has to travel farther in the same amount of time -> it moves faster -> pressure on the top decreases.
> * Air underneath moves slower -> pressure underneath is higher
> * The presure difference creates an upward force - lift
Isn't that explanation of why wings work completely wrong? There's nothing that forces the air to cover the top distance in the same time that it covers the bottom distance, and in fact it doesn't. https://www.cam.ac.uk/research/news/how-wings-really-work
Very strange to use a mistake as your first demo, especially while talking about how it's phd level.
peterdsharpe · 1h ago
Yes, it is completely wrong. If this were a valid explanation, flat-plate airfoils could not generate lift. (They can.)
Source: PhD on aircraft design
timr · 31m ago
Except it isn't "completely wrong". The article the OP links to says it explicitly:
> “What actually causes lift is introducing a shape into the airflow, which curves the streamlines and introduces pressure changes – lower pressure on the upper surface and higher pressure on the lower surface,” clarified Babinsky, from the Department of Engineering. “This is why a flat surface like a sail is able to cause lift – here the distance on each side is the same but it is slightly curved when it is rigged and so it acts as an aerofoil. In other words, it’s the curvature that creates lift, not the distance.”
The meta-point that "it's the curvature that creates the lift, not the distance" is incredibly subtle for a lay audience. So it may be completely wrong for you, but not for 99.9% of the population. The pressure differential is important, and the curvature does create lift, although not via speed differential.
I am far from an AI hypebeast, but this subthread feels like people reaching for a criticism.
ttoinou · 27m ago
I would say a wing with two sides of different length is more difficult to understand than one shape with two sides of opposites curvatures but same length
avs733 · 11m ago
the wrongness isn't germane to most people but it is a specific typology of how LLMs get technica lthings wrong that is critically important to progressing them. It gets subtle things wrongby being biased towards lay understandings that introduce vagueness because greater precision isn't useful.
That doesn't matter for lay audieces and doesn't really matter at all until we try and use them for technical things.
timr · 3m ago
I grant your broader point, but extrapolating from this marketing copy is not a great example.
The real question is, if you go back to the bot following this conversation and you challenge it, does it generate the more correct answer?
carabiner · 26m ago
It's the "same amount of time" part that is blatantly wrong. Yes geometry has an effect but there is zero reason to believe leading edge particles, at the same time point, must rejoin at the trailing edge of a wing. This is a misconception at the level of "heavier objects fall faster." It is non-physical.
The video in the Cambridge link shows how the upper surface particles greatly overtake the lower surface flow. They do not rejoin, ever.
timr · 18m ago
Again, you're not wrong, it's just irrelevant for most audiences. The very fact that you have to say this:
> Yes geometry has an effect but there is zero reason to believe leading edge particles, at the same time point, must rejoin at the trailing edge of a wing.
...implicitly concedes that point that this is subtle. If you gave this answer in a PhD qualification exam in Physics, then sure, I think it's fair for someone to say you're wrong. If you gave the answer on a marketing page for a general-purpose chatbot? Meh.
(As an aside, this conversation is interesting to me primarily because it's a perfect example of how scientists go wrong in presenting their work to the world...meeting up with AI criticism on the other side.)
adgjlsfhk1 · 12m ago
right, the other is that if you remove every incorrect statement from the AI "explanation", the answer it would have given is "airplane wings generate lift because they are shaped to generate lift".
timr · 7m ago
> right, the other is that if you remove every incorrect statement from the AI "explanation", the answer it would have given is "airplane wings generate lift because they are shaped to generate lift".
...only if you omit the parts where it talks about pressure differentials, caused by airspeed differences, create lift?
Both of these points are true. You have to be motivated to ignore them.
GPT-6 will just go on forums and pretend to be a girl that needs help with homework.
snerbles · 32m ago
Fallback is posting a confidently wrong answer on another forum to bait for angry correct answers.
ge96 · 49m ago
What is the actual answer? I know the "skipping stone" idea is wrong too, thinking it's just angle of attack
bilsbie · 45m ago
Angle of attack is a big part but I think the other thing going on is air “sticks” to the surface of the top of the wing and gets directed downward as it comes off the wing. It also creates a gap as the wing curves down leaving behind lower pressure from that.
base698 · 46m ago
Weight of the air deflecting downward. Plain ole Newtonian equal and opposite reaction.
datadrivenangel · 34m ago
But also pressure providing force. It's complicated.
qq66 · 43m ago
Air pushes on the wing. The control surfaces determine in which direction.
Sorry, I know nothing about this topic, but this is how it was explained to me every time it's come up throughout my life. Could you explain a bit more?
I've always been under the impression that flat-plate airfoils can't generate lift without a positive angle-of-attack - where lift is generated through the separate mechanism of the air pushing against an angled plane? But a modern airfoil can, because of this effect.
And that if you flip them upside down, a flat plate is more efficient and requires less angle-of-attack than the standard airfoil shape because now the lift advantage is working to generate a downforce.
I just tried to search Google, but I'm finding all sorts of conflicting answers, with only a vague consensus that the AI-provided answer above is, in fact, correct. The shape of the wing causes pressure differences that generate lift in conjunction with multiple other effects that also generate lift by pushing or redirecting air downward.
stonemetal12 · 17m ago
>Air over the top has to travel farther in the same amount of time
There is no requirement for air to travel any where. Let alone in any amount of time. So this part of the AI's response is completely wrong. "Same amount of time" as what? Air going underneath the wing? With an angle of attack the air under the wing is being deflected down, not magically meeting up with the air above the wing.
andoando · 29m ago
Im quite sure the "air on the top has to travel faster to meet the air at the bottom " is false. Why would they have to meet at the same time? What would cause air on the top to accelerate?
FeepingCreature · 13m ago
(Layman guess) Pressure? The incoming split air has to go somewhere. The volume of air inflowing above and below is roughly the same.
zombiwoof · 33m ago
But we live in the world of Trump where facts don’t matter. If GPt 5 says this is how it works, that’s how it works and Fox News will back it up
tshaddox · 52m ago
It's an extremely famous example of a widespread misconception. I don't know anything about aeronautical engineering but I'm quite familiar with the "equal transit time fallacy."
During the demo they quickly shuffled off of, the air flow lines completely broke. It was just a few dots moving left to right, changing the angle of the surface showed no visual difference in airflow.
tths · 1h ago
Yeah, the explanation is just shallow enough to seem correct and deceive someone who doesn't grasp really well the subject.
No clue how they let it pass, that without mentioning the subpar diagram it created, really didn't seem like something miles better than what previous models can do already.
Vegenoid · 42m ago
> No clue how they let it pass
It’s very common to see AI evangelists taking its output at face value, particularly when it’s about something that they are not an expert in. I thought we’d start seeing less of this as people get burned by it, but it seems that we’re actually just seeing more of it as LLMs get better at sounding correct. Their ability to sound correct continues to increase faster than their ability to be correct.
chasd00 · 30m ago
This is just like the early days of Google search results, "It's on the Internet, it must be true".
traceroute66 · 51m ago
Hilarious how the team spent so much time promising GPT5 had fewer hallucinations and deceptions.
Meanwhile the demo seems to suggest business as usual for AI hallucinations and deceptions.
stanmancan · 36m ago
> Yeah, the explanation is just shallow enough to seem correct and deceive someone who doesn't grasp really well the subject.
This is the problem with AI in general.
When I ask it about things I already understand, it’s clearly wrong quite often.
When I ask it about something I don’t understand, I have no way to know if its response is right or wrong.
theappsecguy · 54m ago
This is the headline for all LLM output past "hello world"
ricardobayes · 8m ago
To me, it's weird to call it "PhD-level". That, to me, means to be able to take in existing information on a certain very niche area and able to "push the boundary". I might be wrong but to date I've never seen any LLM invent "new science", that makes PhD, really PhD. It also seems very confusing to me that many sources mention "stone age" and "PhD-level" in the same article. Which one is it?
People seem to overcomplicate what LLM's are capable of, but at their core they are just really good word parsers.
tim333 · 25m ago
From Wikipedia
>In fact, theory predicts – and experiments confirm – that the air traverses the top surface of a body experiencing lift in a shorter time than it traverses the bottom surface; the explanation based on equal transit time is false.
So the effect is greater than equal time transit.
I've seen the GPT5 explanation in GCSE level textbooks but I thought it was supposed to be PhD level;)
arcumaereum · 1h ago
Yeah I'm surprised they used that example. The correct (and PhD-level) response would have been to refuse or redirect to a better explanation
Its not fully wrong but its a typical example of how simplified scientific explanations have spread everywhere without personal verification of each person involved in the chinese whisper
samfriedman · 50m ago
The "demo" it made was pretty horrible too. I would have been impressed if it had simulated a NACA 4412 or something.
timr · 49m ago
Your link literally says pressure differential is the reason, and that curvature matters:
> “What actually causes lift is introducing a shape into the airflow, which curves the streamlines and introduces pressure changes – lower pressure on the upper surface and higher pressure on the lower surface,” clarified Babinsky, from the Department of Engineering. “This is why a flat surface like a sail is able to cause lift – here the distance on each side is the same but it is slightly curved when it is rigged and so it acts as an aerofoil. In other words, it’s the curvature that creates lift, not the distance.”
So I'd characterize this answer as "correct, but incomplete" or "correct, but simplified". It's a case where a PhD in fluid dynamics might state the explanation one way to an expert audience, but another way to a room full of children.
kybernetikos · 45m ago
Pressure differential is absolutely one of the main components of lift (although I believe conservation of momentum is another - the coanda effect changes the direction of the airflows and there's 2nd law stuff happening on the bottom edge too), but the idea that the pressure differential is caused by the fact that "air over the top has to travel farther in the same amount of time" because the airfoil is curved is completely incorrect, as the video in my link shows.
timr · 39m ago
It's "completely incorrect" only if you're being pedantic. It's "partially correct" if you're talking casually to a group of regular people. It's "good enough" if you're talking to a classroom of children. Audience matters.
The hilarious thing about this subthread is that it's already getting filled with hyper-technical but wrong alternative explanations by people eager to show that they know more than the robot.
kybernetikos · 31m ago
"air over the top has to travel farther in the same amount of time" is just wrong, it doesn't have to, and in fact it doesn't.
It's called the "equal transit-time fallacy" if you want to look it up, or follow the link I provided in my comment, or perhaps the NASA link someone else offered.
timr · 28m ago
I'm not saying that particular point is wrong. I'm saying that for most people, it doesn't matter, and the reason the "fallacy" persists is because it's a good enough explanation for the layman that is easy to conceptualize.
Pretty much any scientific question is fractal like this: there's a superficial explanation, then one below that, and so on. None are "completely incorrect", but the more detailed ones are better.
The real question is: if you prompt the bot for the better, deeper explanation, what does it do?
kybernetikos · 9m ago
So I worry that you think that the equal transit time thing is true, but is just one effect among others. This is not the case. There are a number of different effects, including bernoulli and coanda and newtons second law that all contribute to lift, but none of the things that actually happen have anything to do with equal transit time.
The equal transit time is not a partially correct explanation, it's something that doesn't happen. It's not a superficial explanation, it's a wrong explanation. It's not even a good lie-to-children, as it doesn't help predict or understand any part of the system at any level. It instead teaches magical thinking.
As to whether it matters? If I am told that I can ask my question to a system and it will respond like a team of PhDs, that it is useful to help someone with their homework and physical understanding, but it gives me instead information that is incorrect and misleading, I would say the system is not working as it is intended to.
Even if I accept that "audience matters" as you say, the suggested audience is helping someone with their physics homework. This would not be a suitable explanation for someone doing physics homework.
bccdee · 29m ago
No, it's never good enough, because it's flat-out wrong. This statement:
> Air over the top has to travel farther in the same amount of time
is not true. The air on top does not travel farther in the same amount of time. The air slows down and travels a shorter distance in the same amount of time.
It's only "good enough for a classroom of children" in the same way that storks delivering babies is—i.e., if you're content to simply lie rather than bothering to tell the truth.
mcs5280 · 41m ago
Sam will fix this in the next release he just needs you to give him more money
IanCal · 38m ago
As a complete aside I’ve always hated that explanation where air moves up and over a bump, the lines get closer together and then the explanation is the pressure lowers at that point. Also the idea that the lines of air look the same before and after and yet somehow the wing should have moved up.
addaon · 52m ago
> Isn't that explanation of why wings work completely wrong?
This is an LLM. "Wrong" is not a concept that applies, as it requires understanding. The explanation is quite /probable/, as evidenced by the fact that they thought to use it as an example…
karel-3d · 23m ago
yeah that's a great thing to use as LLM demo because it sounds plausible yet it's completely misleading and wrong.
AnimalMuppet · 1h ago
Yes. But I strongly suspect that it's the most frequent answer in the training data...
bambax · 34m ago
They couldn't find a more apt demnonstration of what an LLM is and does if they tried.
An LLM doesn't know more than what's in the training data.
In Michael Crichton's The Great Train Robbery (published in 1975 about events that happened in 1855) the perpetrator, having been caught, explains to a baffled court that he was able to run on top of a running train "because of the Bernoulli effect", that he misspells and completely misunderstands. I don't remember if this argument helps him get away with the crime? Maybe it does, I'm not sure.
This is another attempt at a Great Robbery.
NelsonMinar · 51m ago
IIRC I was required to regurgitate this wrong answer to pass my FAA pilot exam.
carabiner · 6m ago
Yeah, it's like asking a car driver (even a professional driver) to explain the Otto cycle. Enduser vs. engineer.
CPLX · 49m ago
Yeah me too, so it's found in many authoritative places.
And I might be wrong but my understanding is that it's not wrong per-se, it's just wildly incomplete. Which, is kind of like the same as wrong. But I believe the airfoil design does indeed have the effect described which does contribute to lift somewhat right? Or am I just a victim of the misconception.
gekoxyz · 44m ago
And your suspicion is right. The sad reality is that it's just a stochastic parrot, that can produce really good answers in certain occasions.
avs733 · 13m ago
Its a particular type of mistake that is really interesting and telling. It is a misconception - and a common socially disseminated simplifcation. In students, these don't come from a lack of knowledge but rather from places where knowledge is structured incorrectly. Often because the phenomenon are difficult to observe or mislead when observed. Another example is heat and temperature. Heat is not temperature, but it is easy to observe them always being the same in your day to day life and so you bring that belief into a college thermodynamics course where you are learning that heat and temperature are different for the first time. It is a commonsense observation of the world that is only incorrect in technical circles
These are places where common lay discussions use language in ways that is wrong, or makes simplifcations that are reasonable but technically incorrect. They are especially common when something is so 'obvious' that experts don't explain it, the most frequent version of the concepts being explained
These, in my testing, show up a lot in LLMs - technical things are wrong when the most language of the most common explanations simplifies or obfuscates the precise truth. Often, it pretty much matches the level of knowledge of a college freshman/sophmore or slightly below, which is sort of the level of discussion of more technical topics on the internet.
croes · 30m ago
It’s a common misconception, I doubt they know themselves and GPT 5 doesn’t tell them otherwise because it’s the mist common in explanation in the training data.
The hallmark of an LLM response: plausible sounding, but if you dig deeper, incorrect
on_the_train · 54m ago
It's a misconception that almost everyone does though. I recently even saw it being being taught in a zeppelin museum!
xeromal · 52m ago
Why replace humans if make human mistakes
metalliqaz · 42m ago
less overhead on benefits and pay raises
carabiner · 45m ago
Holy shit that is wrong. That's what happens when you get software, ML engineers who think they know everything.
Q6T46nT668w6i3m · 51m ago
Yeah, that’s slop.
antoni4040 · 53m ago
Oh my God, they were right, ChatGPT5 really is like talking to a bunch of PhD. You let it write an answer and THEN check the comments on Hacker News.
Truly innovative.
adolph · 35m ago
The HN comments are "one of the most important methods of building knowledge – . . . the intersubjective verification of the interobjective." [0]
The marketing copy and the current livestream appear tautological: "it's better because it's better."
Not much explanation yet why GPT-5 warrants a major version bump. As usual, the model (and potentially OpenAI as a whole) will depend on output vibe checks.
pram · 1h ago
We’re at the audiophile stage of LLMs where people are talking about the improved soundstage, tonality, reduced sibilance etc
jaredcwhite · 1h ago
Note GPT-5's subtle mouthfeel reminiscent of cranberries with a touch of bourbon.
__loam · 1h ago
Every bourbon tastes the same unless it's Weller, King's County Peated, or Pappy (or Jim Beam for the wrong reasons lol)
alephnerd · 59m ago
Tbh, a mid-shelf Four Roses gets you 90% of the way to a upper shelf Weller.
__loam · 56m ago
I'm being hyperbolic but yeah four roses is probably the best deal next to Buffalo trace. All their stuff is fairly priced. If you want something like Weller though, you should get another wheated bourbon like Maker's Mark French oaked.
alephnerd · 48m ago
Buffalo trace is ridiculously overpriced nowadays. Good bourbon, but def not worth $35-40 for 750ml.
> you should get another wheated bourbon like Maker's Mark French oaked
I agree. I've found Maker Mark products to be a great bang for your buck quality wise and flavor wise as well.
__loam · 33m ago
If you can find Buffalo Trace for msrp which is $20-30, it's a good deal. I think the bourbon "market" kind of popped recently so finding things has been getting a little easier.
alephnerd · 29m ago
Yep! I agree! At MSRP BT is a great buy.
> I think the bourbon "market" kind of popped recently
It def did. The overproduction that was invested in during the peak of the COVID collector boom is coming into markets now. I think we'll see some well priced age stated products in the next 3-4 years based on by acquaintances in the space.
Ofc, the elephant in the room is consolidation - everyone wants to copy the LVMH model (and they say Europeans are ethical elves who never use underhanded mopolistic and market making behavior to corner markets /s).
alephnerd · 1h ago
Explains why I find AGI fundamentalists similar to tater heads. /s
(Not to undermine progress in the foundational model space, but there is a lack of appreciation for the democratization of domain specific models amongst HNers).
javchz · 1h ago
I can already see LLMs Sommeliers: Yes, the mouthfeel and punch of GPT-5 it's comparable to the one of Grok 4, but it's tenderness lacks the crunch from Gemini 2.5 Pro.
0x7cfe · 52m ago
Isn't it exactly what the typical LLM discourse is about? People are just throwing anecdotes and stay with their opinion. A is better than B because C, and that's basically it. And whoever tries to actually bench them gets called out because all benches are gamed. Go figure.
tuesdaynight · 15m ago
You need to burn-in your LLM by using for 100 hours before you see the true performance of it.
satyrun · 1h ago
Come on, we aren't even close to the level of audiophile nonsense like worrying about what cable sounds better.
leptons · 19m ago
We're still at the stage of which LLM lies the least (but they all do). So yeah, no different than audiophiles really.
catigula · 1h ago
Informed audiophiles rely on Klippel output now
bobson381 · 1h ago
The empirical ones do! There's still a healthy sports car element to the scene though, at least in my experience.
catigula · 1h ago
You're right, it's hard to admit you can buy a $50 speaker and sub and EQ it to 95% maximum performance.
riknos314 · 41m ago
This is and isn't true.
The room is the limiting factor in most speaker setups. The worse the room, the sooner you hit diminishing returns for upgrading any other part of the system.
In a fantastic room a $50 speaker will be nowhere near 95% of the performance of a mastering monitor, no matter how much EQ you put on it. In the average living room with less than ideal speaker and listening position placement there will still be a difference, but it will be much less apparent due to the limitations of the listening environment.
jpc0 · 23m ago
Absolutely not true.
You might lose headroom or have to live with higher latency but if your complaint is about actual empirical data like frequency response or phase, that can be corrected digitally.
catigula · 40m ago
Ah, the aforementioned snake oil.
virgil_disgr4ce · 30m ago
Well, reduced sibilance is an ordinary and desirable thing. A better "audiophile absurdity" example would be $77,000 cables, freezing CDs to improve sound quality, using hospital-grade outlets, cryogenically frozen outlets (lol), the list goes on and on
Q6T46nT668w6i3m · 1h ago
It’s always been this way with LLMs.
krat0sprakhar · 1h ago
> Not much explanation yet why GPT-5 warrants a major version bump
Exactly. Too many videos - too little real data / benchmarks on the page. Will wait for vibe check from simonw and others
2:40 "I do like how the pelican's feet are on the pedals." "That's a rare detail that most of the other models I've tried this on have missed."
4:12 "The bicycle was flawless."
5:30 Re generating documentation: "It nailed it. It gave me the exact information I needed. It gave me full architectural overview. It was clearly very good at consuming a quarter million tokens of rust." "My trust issues are beginning to fall away"
Honestly, I have mixed feelings about him appearing there. His blog posts are a nice way to be updated about what's going on, and he deserves the recognition, but he's now part of their marketing content. I hope that doesn't make him afraid of speaking his mind when talking about OpenAI's models. I still trust his opinions, though.
WD-42 · 1h ago
It has the last ~6 months worth of flavor of the month Javascript libraries in it's training set now, so it's "better at coding".
How is this sustainable.
sethops1 · 48m ago
Who said anything about sustainable? The only goal here is to hobble to the next VC round. And then the next, and the next, ...
jcgrillo · 53m ago
Vast quantities of extremely dumb money
some-guy · 54m ago
As someone who tries to push the limits of hard coding tasks (mainly refactoring old codebases) to LLMs with not much improvement since the last round of models, I'm finding that we are hitting the reduction of rate of improvement on the S-curve of quality. Obviously getting the same quality cheaper would be huge, but the quality of the output day to day isn't noticeable to me.
camdenreslink · 11m ago
I find it struggles to even refactor codebases that aren't that large. If you have a somewhat complicated change that spans the full stack, and has some sort of wrinkle that makes it slightly more complicated than adding a data field, then even the most modern LLMs seem to trip on themselves. Even when I tell it to create a plan for implementation and write it to a markdown file and then step through those steps in a separate prompt.
Not that it makes it useless, just that we seem to not "be there" yet for the standard tasks software engineers do every day.
scosman · 1h ago
There's a bunch of benchmarks on the intro page including AIME 2025 without tools, SWE-bench Verified, Aider Polyglot, MMMU, and HealthBench Hard (not familiar with this one): https://openai.com/index/introducing-gpt-5/
Pretty par for course evals at launch setup.
nicetryguy · 21m ago
Yeah. We're entered the Smartphone stage: "You want the new one because it's the new one."
anthonypasq · 1h ago
its >o3 performance at gpt4 price. seems pretty obvious
thegeomaster · 1h ago
o3 pricing: $8/Mtok out
GPT-5 pricing: $10/Mtok out
What am I missing?
anthonypasq · 49m ago
pretty sure reduced cache input pricing is a pretty big deal for reasoning models, but im not positive
doctoboggan · 1h ago
Watching the livestream now, the improvement over their current models on the benchmarks is very small. I know they seemed to be trying to temper our expectations leading up to this, but this is much less improvement than I was expecting
827a · 46m ago
I have a suspicion that while the major AI companies have been pretty samey and competing in the same space for a while now, the market is going to force them to differentiate a bit, and we're going to see OpenAI begin to lose the race toward extremely high levels of intelligence instead choosing to focus on justifying their valuations by optimizing cost and for conversational/normal intelligence/personal assistant use-cases. After all, most of their users just want to use it to cheat at school, get relationship advice, and write business emails. They also have Ive's company to continue investing in.
Meanwhile, Anthropic & Google have more room in their P/S ratios to continue to spend effort on logarithmic intelligence gains.
Doesn't mean we won't see more and more intelligent models out of OpenAI, especially in the o-series, but at some point you have to make payroll and reality hits.
juped · 26m ago
I think this is pretty much what we've already seen happening, in fact.
anyg · 34m ago
Also, the code demos are all using GPT-5 MAX on Cursor. Most of us will not be able to use it like that all the time. They should have showed it without MAX mode as well
Workaccount2 · 1h ago
Sam said maybe two years ago that they want to avoid "mic drop" releases, and instead want to stick to incremental steps.
This is day one, so there is probably another 10-20% in optimizations that can be squeezed out of it in the coming months.
bigmadshoe · 1h ago
Then why increment the version number here? This is clearly styled like a "mic drop" release but without the numbers to back it up. It's a really bad look when comparing the crazy jump from GPT3 to GPT4 to this slight improvement with GPT5.
camdenreslink · 7m ago
GPT-5 was highly anticipated and people have thought it would be a step change in performance for a while. I think at some point they had to just do it and rip the bandaid off, so they could move past 5.
Workaccount2 · 54m ago
Because it is a 100x training compute model over 4.
GPT5.5 will be a 10X compute jump.
4.5 was 10x over 4.
bigmadshoe · 33m ago
Even worse optics. They scaled the training compute by 100x and got <1% improvement on several benchmarks.
reasonableklout · 6m ago
Is 1% relative to more recent models like o3, or the (old and obsolete at this point) GPT-4?
dpoloncsak · 38m ago
Honestly, I think the big thing is the sycophancy.
It's starting to reach the mainstream that ChatGPT can cause people to 'go crazy'.
This gives them an out. "That was the old model, look how much better this one tests on our sycophancy test we just made up!!"
yahoozoo · 8m ago
He said that because even then he saw the writing on the wall that LLMs will plateau.
z7 · 1h ago
GPT-5 is #1 on WebDev Arena with +75 pts over Gemini 2.5 Pro and +100 pts over Claude Opus 4:
This same leaderboard lists a bunch of models, including 4o, beating out Opus 4, which seems off.
og_kalu · 1h ago
I mean that's just the consequence of releasing a new model every couple months. If Open AI stayed mostly silent since the GPT-4 release (like they did for most iterations) and only now released 5 then nobody would be complaining about weak gains in benchmarks.
moduspol · 1h ago
Well it was their choice to call it GPT 5 and not GPT 4.2.
og_kalu · 1h ago
It is significantly better than 4, so calling it 4.2 would be rather silly.
amilios · 43m ago
Is it? That's not super obvious from the results they're showing.
og_kalu · 31m ago
Yes it is, if we're talking about the original GPT-4 release or even GPT-4o. What about the results they've shown is not obvious?
jononor · 1h ago
If everyone else had stayed silent as well, then I would agree. But as it is right now they are juuust about managing to match the current pace of the other contenders.
Which actually is fine, but they have previously set quite high expectations. So some will probably be disappointed at this.
wahnfrieden · 1h ago
It is at least much cheaper and seems faster.
They also announced gpt-5-pro but I haven't seen benchmarks on that yet.
doctoboggan · 1h ago
I am hoping there is a "One more thing" that shows the pro version with great benchmark scores
lawlessone · 1h ago
im sure i am repeating someone else but sounds like we're coming over the s-curve
It makes it look like the presentation is rushed or made last minute. Really bad to see this as the first plot in the whole presentation. Also, I would have loved to see comparisons with Opus 4.1.
Edit: Opus 4.1 scores 74.5% (https://www.anthropic.com/news/claude-opus-4-1). This makes it sound like Anthropic released the upgrade to still be the leader on this important benchmark.
danpalmer · 39m ago
> like the presentation is rushed or made last minute
Or written by GPT-5?
rrrrrrrrrrrryan · 1h ago
This is hilarious
moritzwarhier · 1h ago
Probably created without thinking enabled. Lower % accuracy ensues, speaking from experience.
silverquiet · 1h ago
Probably generated by AI.
Sateeshm · 1h ago
If not, the person that made the chart just got $1.5M
lysecret · 1h ago
Couldn’t believe it was real haha
artemonster · 1h ago
[flagged]
dang · 41m ago
Please don't post like this to Hacker News, regardless of how idiotic other people are or you feel they are.
You may not owe people who you feel are idiots better, but you owe this community better if you're participating in it.
If this performs well in independent needle-in-haystack and adherence evaluations, this pricing with this context window alone would make GPT-5 extremely competitive with Gemini 2.5 Pro and Claude Opus 4.1, even if the output isn't a significant improvement over o3. If the output quality ends up on-par or better than the two major competitors, that'd be truly a massive leap forward for OpenAI, mini and nano maybe even more so.
iammrpayments · 4m ago
You also have to count the cost of having to verify your identity to use the API
jjani · 38s ago
It's only a video face scan and your legal ID to SamA, what could possibly go wrong
hrpnk · 34m ago
Interesting that gpt-5 has Oct 01, 2024 as knowledge cut-off while gpt-5-mini/nano it's May 31, 2024.
gpt-4.1 family had 1M/32k input/output tokens. Pricing-wise, it's 37% cheaper input tokens, but 25% more expensive on output tokens. Only nano is 50% cheaper on input and unchanged on output.
jumploops · 1h ago
Pricing seems good, but the open question is still on tool calling reliability.
With 74.9% on SWE-bench, this inches out Claude Opus 4.1 at 74.5%, but at a much cheaper cost.
For context, Claude Opus 4.1 is $15 / 1M input tokens and $75 / 1M output tokens.
> "GPT-5 will scaffold the app, write files, install dependencies as needed, and show a live preview. This is the go-to solution for developers who want to bootstrap apps or add features quickly." [0]
Since Claude Code launched, OpenAI has been behind. Maybe the RL on tool calling is good enough to be competitive now?
And they included Flex pricing, which is 50% cheaper if you're willing to wait for the reply during periods of high load. But great pricing for agentic use with that cached token pricing, Flex or not.
AtNightWeCode · 1h ago
I switched immediately because of pricing, input token heavy load, but it doesn't even work. For some reason they completely broke the already amateurish API.
mehulashah · 1h ago
‘Twas the night before GPT-5, when all through the social-media-sphere,
Not a creature was posting, not even @paulg nor @eshear
Next morning’s posts were prepped and scheduled with care,
In hopes that AGI soon would appear …
user3939382 · 1h ago
Unless someone figures how to make these models a million(?) times more efficient or feed them a million times more energy I don’t see how AGI would even be a twinkle in the eye of the LLM strategies we have now.
Henchman21 · 58m ago
Hey man don’t bring that negativity around here. You’re killing the vibe. Remember we’re now in a post-facts timeline!
hrpnk · 38m ago
They will retire lots of models: GPT-4o, GPT-4.1, GPT-4.5, GPT-4.1-mini, o4-mini, o4-mini-high, o3, o3-pro.
Finally, someone from the product side got a word in. Keep it simple!
joewhale · 1h ago
Short anything that’s riding on AGI coming soon. This presentation has gotten rid of all my fears of my children growing up in a crazy winner take all AGI world.
croes · 28m ago
Don’t fear AGI, fear those who sell something as AGI and those who fall for it
AS04 · 41m ago
Don't count your chickens before they hatch. I believe that the odds of an architecture substantially better than autoregressive causal GPTs coming out of the woodwork within the next year is quite high.
9rx · 22m ago
How does that equate to "winner take all", though? It is quite apparent that as soon as one place figures out some kind of advantage, everyone else follows suit almost immediately.
It's not the 1800s anymore. You can hide behind poor communication.
suddenlybananas · 35m ago
Why do you think that?
atonse · 2h ago
For day to day coding, I've found Anthropic to be killing it with Sonnet 3.7 and now Sonnet 4, and Claude Code feeling like it has even bigger advantages over when it's used in Cursor (And I can't explain why).
I don't even try to use the OpenAI models because it's felt like night and day.
Hopefully GPT-5 helps them catch up. Although I'm sure there are 100 people that have their own personal "hopefully GPT-5 fixes my personal issue with GPT4"
IdealeZahlen · 2h ago
Whatever the benchmarks might say, there's something about Claude that seems to deliver consistently (although not always perfect) quite reliable outputs across various coding tasks. I wonder what that 'secret sauce' might be and whether GPT-5 has figured it out too.
atonse · 1h ago
That's been my experience too. Even though Gemini also does seem to do the fancy one-shot demo code well, in day to day coding, Claude seems to do a much better job of just understanding how programming actually works, what to do, what not to do, etc.
weego · 1h ago
Agreed, I always give my one pager product briefs to AI to break down into phases and tasks, and then progress trackers. I explicitly prompt for verbose phases, tasks and test plans.
Yesterday without much promoting Claude 4.1 gave me 10 phases, each with 5-12 tasks that could genuinely be used to kanban out a product step by step.
Claude 3.7 sonnet was effectively the same with fewer granular suggestions for programming strategies.
Gemini 2.5 gave me a one pager back with some trivial bullet points in 3 phases, no tasks at all.
o3 did the same as as Gemini, just less coherent.
Claude just has whatever the thing is for now
concinds · 21m ago
Gemini Pro or Flash?
unshavedyak · 1h ago
How are you having claude track these phases/tasks? Eg are you having it write to a TASKS.md and update it after each phase?
deadbabe · 23m ago
The secret is just better context engineering. There is no other “secret” sauce, all these models are built on the same concepts.
bamboozled · 1h ago
Claude is fast too, Gemini isn’t as good and just gets hung up on things Claude doesn’t.
pawelduda · 19m ago
Yup, Claude has been kicking GPT's ass for months now
NitpickLawyer · 2h ago
Colleagues were saying that horizon alpha and beta were looking better than claude4 for frontend stuff, especially newer frameworks. I think the idea of having full + mini + nano is really good, as long as the smaller ones can reasonably handle small-ish tasks. You'd have your architect / plan whatever sessions with the large one, scoping out regular tasks for the -mini version and then the really easy ones to -nano.
4.1 was almost usable in that fashion. I had 4.1-nano working in cline with really trivial stuff (add logging, take this example and adapt it in this file, etc) and it worked pretty well most of the time.
jstummbillig · 1h ago
Well, since (like you pointed out) using the Anthropic models in different settings is not that exciting anymore, the difference is what Claude Code does. It's a good product.
mlsu · 1h ago
Claude Code is good because the Anthropic models are trained/finetuned to be good at using it.
octo888 · 1h ago
Killing it - at what type of coding task? What "bigger advantages" specifically? What is night and day?
sundarurfriend · 43m ago
Some people have hypothesized that GPT-5 is actually about cost reduction and internal optimization for OpenAI, since there doesn't seem to be much of a leap forward, but another element that they seem to have focused on that'll probably make a huge difference to "normal" (non-tech) users is making precise and specifically worded prompts less necessary.
They've mentioned improvements in that aspects a few times now, and if it actually materializes, that would be a big leap forward for most users even if underneath GPT-4 was also technically able to do the same things if prompted just the right way.
oof-baroomf · 1h ago
74.9 SWEBench. This increases the SOTA by a whole .4%. Although the pricing is great, it doesn't seem like OpenAI found a giant breakthrough yet like o1 or Claude 3.5 Sonnet
Workaccount2 · 59m ago
I'm pretty sure 3.5 sonnet always benchmarked poorly, despite it being the clear programming winner of it's time.
aliljet · 1h ago
The eval bar I want to see here is simple: over a complex objective (e.g., deploy to prod using a git workflow), how many tasks can GPT-5 stay on track with before it falls off the train. Context is king and it's the most obvious and glaring problem with current models.
CamelCaseName · 1h ago
This sounds like the kind of thing:
1. I desperately want (especially from Google)
2. Is impossible, because it will be super gamed, to the detriment of actually building flexible flows.
basically in my testing really felt that gpt5 was "using tools to think" rather than just "using tools". it gets very powerful when coding long horizon tasks (a separate post i'm publishing later).
to give one substantive example, in my developer beta (they will release the video in a bit) i put it to a task that claude code had been stuck on for the last week - same prompts - and it just added logging to instrument some of the failures that we were seeing and - from the logs that it added and asked me to rerun - figured out the solve.
billmalarky · 21m ago
Hi Swyx I always appreciate your insights, something you wrote really resonated with a personal theory I've been developing:
>"While I never use AI for personal writing (because I have a strong belief in writing to think)"
The optimal AI productivity process is starting to look like:
AI Generates > Human Validates > Loop
Yet cognitive generation is how humans learn and develop cognitive strength, as well as how they maintain such strength.
Similar to how physical activity is how muscles/bone density/etc grow, and how body tissues maintain.
Physical technology freed us from hard physical labor that kept our bodies in shape -- at a cost of physical atrophy.
AI seems to have a similar effect for our minds. AI will accelerate our cognitive productivity, and allow for cognitive convenience -- at a cost of cognitive atrophy.
At present we must be intentional about building/maintaining physical strength (dedicated strength training, cardio, etc).
Soon we will need to be intentional about building/maintaining cognitive strength.
I suspect the workday/week of the future will be split on AI-on-a-leash work for optimal productivity, with carve-outs for dedicated AI-enhanced-learning solely for building/maintaining cognitive health (where productivity is not the goal, building/maintaining cognition is). Similar to how we carve out time for working out.
What are your thoughts on this? Based on what you wrote above, it seems you have similar feelings?
Is there a name for this theory?
If not can you coin one? You're great at that :)
diggan · 1h ago
Was just skimming along that review, while watching the live-stream, where they just mentioned how much better at writing prose GPT-5 is, while I skimmed across:
> It’s actually worse at writing than GPT-4.5
Sounds like we need to wait a bit for the dust to settle before one can trust anything one hears/reads :)
tough · 1h ago
well it's difficult to trust the people selling it in the first place. They're too biased to not lie
It's hard to make a man understand something standing between them and their salary
barrell · 1h ago
I don’t think that’s a valid excuse. Yes marketing speak has always existed, but it’s not like companies have always been completely unreliable.
I found it strange that, despite my excitement for such an event being roughly equivalent to WWDC these days, I had 0 desire to watch the live stream for exactly this reason: it’s not like they’re going to give anything to us straight.
Even this years WWDC I at least skipped through video afterwards. Before I used to have watch parties. Yes they’re overly positive and paint everything in a good light, but they never felt… idk whatever the vibe is I get from these (applicable to OpenAI, Grok, Meta, etc)
It’s been just a few years of a revolutionary technology and already the livestreams are less appealing than the biggest corporations yearly events. Personally I find that sad
swyx · 1h ago
better than 4o but worse than 4.5 is internally consistent. and ofc writing is extremely multidimensional.
WhitneyLand · 1h ago
But that’s not what the review says:
“It’s actually worse at writing than GPT-4.5, and I think even 4o”
So the review is not consistent with the PR, hence the commenter expressing preference for outside sources.
thierrydamiba · 1h ago
Great writeup. I particularly like the idea of splitting your tools into the four buckets.
”I think GPT-5 is the closest to AGI we’ve ever been”
Sorry, but this sounds like overly sensational marketing speak and just leaves a bad taste in the mouth for me.
Aurornis · 1h ago
I found a Hacker News thread via Google a few days ago. One of the top comments was from someone describing their RAG architecture and a certain technique (my search term). The comment boasted that their system was so good it that their team thought they created something close to AGI.
Then I noticed the date on the comment: 2023.
Technically, every advancement in the space is “the closest to AGI that we’ve ever been”. It’s technically correct, since we’re not moving backward. It’s just not a very meaningful statement.
JumpCrisscross · 1h ago
> Technically, every advancement in the space is “the closest to AGI that we’ve ever been”
By that standard Neolithic tool use was progress to AGI.
wild_egg · 58m ago
Technically correct
Dr4kn · 1h ago
"It's the best iPhone we ever made."
Fargren · 1h ago
AGI, like AI before it, has been coopted into a marketing term. Most of the time, outside of sci-fi, what people mean when they say AGI is "a profitable LLM".
In the words OpenAI: “AGI is defined as highly autonomous systems that outperform humans at most economically valuable work”
dingnuts · 52m ago
SamA isn't an idiot. When he says AGI he wants you to think of Asimov style AI. Don't run defense for billionaire grifters.
martin_a · 1h ago
Same marketing BS like "the best iPhone ever!". Well, duh, if your new version (of hardware/software) isn't better, what the deal then?
Does this mean AGI is cancelled? 2027 hard takeoff was just sci-fi?
usaar333 · 1h ago
At this point the prediction for SWE bench (85% by end of this month) is not materializing. We're actually quite far away.
growthwtf · 48m ago
Good thing they didn't nuke the data centers after all!
Keyframe · 1h ago
Always has been.
machiaweliczny · 1h ago
When to short NVIDIA? I guess when chinese get their cards production
mvieira38 · 2m ago
It's good for NVDA if the AI companies can't squeeze more performance out of the same compute, which is the case if GPT-5 underperforms
ath3nd · 56m ago
Short?
It's a perfect situation for Nvidia. You can see that after months of trying to squeeze out all % of marginal improvements, sama and co decided to brand this GPT-4.0.0.1 version as GPT-5. This is all happening on NVDA hardware, and they are gonna continue desperately iterating on tiny model efficiencies until all these valuation $$$ sweet sweet VC cash run out (most of it directly or indirectly going to NVDA).
cedws · 47m ago
I'd rather they just call it GPT-5 than GPT 4.1o-Pro-Max like their current nightmare naming convention. I lost track of what the 'best' model is.
ath3nd · 42m ago
They are all..kinda the same?
spruce_tips · 1h ago
These presenters all give off such a “sterile” vibe
motoxpro · 1h ago
They are researchers, not professional presenters. I promise you if I told you to do a live demo, on stage, for 20 minutes, going back and forth between scripted and unscripted content, to an audience of at least 50 million people, that unless you do this a lot, you would do the same or worse.
I know this because this is what I do for a living. I have seen 1000s of "normal" people be extremely awkward on stage. Much more so than this.
It's super unfortunate that, becasue we live in the social media/youtube era, that everyone is expected to be this perfect person on camera, because why wouldn't they be? That's all they see.
I am glad that they use normal people who act like themselves rather than them hiring actors or taking researchers away from what they love to do and tell them they need to become professional in-front-of-camera people because "we have the gpt-5 launch" That would be a nightmare.
It's a group of scientists sharings their work with the world, but people just want "better marketing" :\
retsibsi · 1h ago
I think they're copping this criticism because it's neither one thing nor the other. If it was really just a group of scientists being themselves, some of us would appreciate that. And if it was inauthentic but performed by great actors, most people wouldn't notice or care about the fakeness. This is somewhere in the middle, so it feels very unnatural and a bit weird.
motoxpro · 57m ago
You're describing low skilled presenters. That is what it looks like when you put someone up in front of a camera and tell them to communicate a lot of information. You're not thinking about "being yourself," you're thinking about how to not forget your lines, not mess up, not think about the different outcomes of the prompt that you might have to deal with, etc.
This was my point. "Being yourself" on camera is hard. This comes across, apparently shockingly, as being devoid of emotion and/or robotic
retsibsi · 49m ago
Yeah, but I disagree with you a bit. If it were less heavily scripted, it may or may not be going well, but it would feel very different from this and would not be copping the same criticisms. Or if they unashamedly leant into the scriptedness and didn't try to simulate normal human interaction, they would be criticised for being "wooden" or whatever, but it wouldn't have this slightly creepy vibe.
motoxpro · 44m ago
I get you.
I think for me, just knowing what is probably on the teleprompter, and what is not, I am willing to bet a lot of the "wooden" vibe you are getting is actually NOT scripted.
There is no way for people to remember that 20 minutes of dialog, so when they are not looking at the camera, that is unscripted, and viceversa.
taytus · 35m ago
Extremely robotic.
twixfel · 2m ago
Jakub Pachocki at the end is probably one of the worst public speakers I've ever seen. It's fine, it's not his mother tongue, and public speaking is hard. Why make him do it then?
wasabi991011 · 46m ago
You are acting like there aren't hundreds of well-preserved talks given at programming conferences every year, or that being a good presenter is not a requirement in academic research.
Also, whether OpenAI is a research organization is very much up for debate. They definitely have the resources to hire a good spokesperson if they wanted.
motoxpro · 39m ago
I don't know how many conferences you have been to but most talks are painfully bad. The ones that get popular are the best and by people who love speaking, hence why you are seeing them speak (selection bias at it's finest)
They do have the resources (see WWDC), the question is if you want to take your technical staff of of their work for the amount of time it takes to develop the skill
drexlspivey · 1h ago
But why would you want to put researchers in a marketing video? It’s not like they are explaining something deep.
motoxpro · 55m ago
It's better marketing and more credible to have the researcher say "We think GPT 5 is the best model for developers, we used it extensively internally. Here let me give you an example..." than it is for Matthew McConaughey to say the same.
0x7cfe · 39m ago
I don't know. Maybe I'm biased, but Elon and his teammates' presentations do seem natural to me. Maybe a bit goofy but always on point nevertheless.
motoxpro · 36m ago
Totally. I mean at this point Elon has 1000s of hours of practice doing interviews, pitches, presentations, conferences, etc. See Sam Altman in this context.
seydor · 23m ago
researchers should need to be tortured like this. But maybe if they are paid so much, they should
mhh__ · 1h ago
Well yes I think part of the reason it's slightly unnerving is that this actually how they act irl. Sometimes people need a bit of edge to 'em!
efilife · 56m ago
Maybe they are just nervous with half of the world looking at them?
twixfel · 49m ago
They shouldn't be presenting if they can't present.
"Minimal reasoning means that the reasoning will be minimal..."
diggan · 1h ago
Not even 10 seconds after I started watching the stream, someone said how much more human GPT-5 is, while the people sitting and talking about it don't seem human at all, and it's not an accent/language thing. Seems they're strictly following a dialogue script that is trying to make them seem "impromptu" but the acting isn't quite there for that :)
jazzyjackson · 58m ago
I use LLMs to get answers to queries but I avoid having conversations with them because I'm aware we pick up idiosyncrasies and colloquialisms from everyone we interact with. People who spend all day talking to thier GPT-voice will adjust their speaking style to be more similar to the bot.
I developed this paranoia upon learning about The Ape and the Child where they raised a chimp alongside a baby boy and found the human adapted to chimp behavior faster than the chimp adapted to human behavior. I fear the same with bots, we'll become more like them faster than they'll become like us.
I don’t blame them, they aren’t actors. And yes, it’s clearly not impromptu, but I am trying to not let that take away from the message they are communicating. :)
HaZeust · 1h ago
One woman who went through her calendar with GPT had good acting that the GPT reply helped her find impromptu information (an email she needed to answer), and someone staged GPT-5 to make a French-learning website lander - which butchered its own design in the second run; but that's all the good acting for a "candid presentation" that I could find.
nilsherzig · 1h ago
It created a webapp called „le chat“ hahah
HaZeust · 51m ago
I laughed my ass off immediately after it gave that output, until the presenter made clear that it was a flash card for learning the words, "the cat" in French - and backed it up.
MattSayar · 1h ago
Presenting is hard
AnimalMuppet · 1h ago
Presenting where you have to be exactly on the content with no deviation is hard. To do that without sounding like a robot is very hard.
Presenting isn't that hard if you know your content thoroughly, and care about it. You just get up and talk about something that you care about, within a somewhat-structured outline.
Presenting where customers and the financial press are watching and parsing every word, and any slip of the tongue can have real consequences? Yeah, um... find somebody else.
Bluestein · 1h ago
One heck of a Turing test itself if I've ever seen one.-
guy_ross · 2m ago
interesting how they put this effort to making us feel physiologically well with everyone wearing blue shirts, open body language, etc. just to give off sterile robotic vibes. also noticed a dude reading off his hand at 45 minutes in, would think they brought in a few teleprompters.
wavemode · 1h ago
It's because they have a script but are bad at acting.
Would've been better to just do a traditional marketing video rather than this staged "panel" thing they're going for.
christina97 · 1h ago
If the presenter is less human the LLM appears more human in comparison.
polotics · 1h ago
at least no one is going for the infamous vocal fry :-D
0x457 · 1h ago
It gives me elementary school oral report. The same level of acting and script.
CamelCaseName · 1h ago
Hundreds of billions on the line, really can't risk anything
mhh__ · 1h ago
this is just the way that american middle and upper classes are going. This kind of language/vibe is the default outside of a specific type of WASP IME at least.
pyb · 1h ago
They look nervous, messing this presentation up could cost them their high-paying jobs.
swader999 · 1h ago
I like hearing from the people in the thick of it.
bo-tao · 1h ago
Can't they use AI to make them more human?
greatwhitenorth · 1h ago
Steve Jobs is meant for moments like this. He would have explained everything crystal clear. Everyone else pales in comparison. I wish he is there to explain the current state of AI.
cuuupid · 1h ago
The silent victory here is this seems like it is being built to be faster and cheaper than o3 while presenting a reasonable jump, which is an important jump in scaling law
On the other hand if it's just getting bigger and slower it's not a good sign for LLMs
smlacy · 1h ago
Yeah, this very much feels like "we have made a more efficient/scalable model and we're selling it as the new shiny but it's really just an internal optimization to reduce cost"
reasonableklout · 3m ago
Significant cost reduction while providing the same performance seems pretty big to me?
Not sure why a more efficient/scalable model isn't exciting
hirvi74 · 1h ago
Personally, I am more concerned about accuracy than speed.
onlyrealcuzzo · 1h ago
Yeah, but OpenAI is concerned with getting on a path to making money, as their investors will eventually run out of money to light on fire, so...
wgjordan · 1h ago
Note it's not available to everyone yet:
> GPT-5 Rollout
> We are gradually rolling out GPT-5 to ensure stability during launch. Some users may not yet see GPT-5 in their account as we increase availability in stages.
minimaxir · 1m ago
I am seeing it now in the Playground backend.
jhickok · 34m ago
Weird. On the homepage for GPT-5 it says "Available to everyone."
nobodywillobsrv · 9m ago
This is one of these "best efforts" but also "lying a bit in marketing" is ok I guess.
On bad days this really bothers me. It's probably not the biggest deal I guess but somehow really feels like it pushes us all over the edge a bit. Is there a post about this phenomena? It feels like some combination of bullying, gaslighting and just being left out.
FabHK · 1h ago
But available from today to free tier. Yay.
km144 · 1h ago
How would I even know? I haven't seen which model of ChatGPT I'm using on the site ever since they obfuscated that information at some point.
umanwizard · 1h ago
Hmmm? I have a dropdown showing which model I'm using right there on chat.com
If you can't see it, you're likely on the free tier and using the latest mini model.
cootsnuck · 12m ago
Not true. I've been a paid user forever and on the Android app they have definitely obscured the model selector. It's readily visible to me on desktop / desktop browser. But on the Android app the only place I can find it is if I click on an existing response already sent by chatGPT and then it gives me the option to re-generate the message with a different model.
And while I'm griping about their Android app, it's also very annoying to me that they got rid of the ability to do multiple, subsequent speech-to-text recordings within a single drafted message. You have to one-shot anything you want to say, which would be fine if their STT didn't sometimes failed after you've talked for two minutes. Awful UX. Most annoying is that it wasn't like that originally. They changed it to this antagonistic one-shot approach a several months ago, but then quickly switched back. But then they did it again a month or so ago and have been sticking with it. I just use the Android app less now.
manojlds · 53m ago
What do you mean? It's front and center
thepasswordis · 1h ago
The model should appear as a drop down at the top of the page.
Kurtz79 · 1h ago
"what model are you?"
ChatGPT said:
You're chatting with ChatGPT based on the GPT-4o architecture (also known as GPT-4 omni), released by OpenAI in May 2024.
pjerem · 1h ago
Actually this trick have been proven to be useless in a lot of cases.
LLMs don’t inherently know what they are because "they" are not themselves part of the training data.
However, maybe it’s working because the information is somewhere into their pre-prompt but if it wasn’t, it wouldn’t say « I don’t know » but rather hallucinate something.
So maybe that’s true but you cannot be sure.
dpoloncsak · 33m ago
If you believe 'leaked system prompts', it tends to be part of the system prompt.
I believe most of these came from asking the LLMs, and I don't know if they've been proven to not be a hallucination.
...which is useless when the model gets changed in-between responses.
davepeck · 1h ago
Sam Altman, in the summer update video:
> "[GPT-5] can write an entire computer program from scratch, to help you with whatever you'd like. And we think this idea of software on demand is going to be one of the defining characteristics of the GPT-5 era."
data-ottawa · 1h ago
Nit: the featured jumping game is trivial to beat by just continuously jumping.
I’m not sure this will be game changing vs existing offerings
mlnj · 1h ago
Cannot believe how it could stand up to that high expectation.
But then again, all of this is a hype machine cranked up till the next one needs cranking.
jononor · 1h ago
There are so many people on-board with this idea, hypemen collaborators, that I think they might be safe for a year or two more. They will shout about how miraculous it is, and tell everyone that does not get the promised value that "you are just holding it wrong".
This buys them a fair amount of time to improve things.
davepeck · 1h ago
Yeah.
It does feel like we're marching toward a day when "software on tap" is a practical or even mundane fact of life.
But, despite the utility of today's frontier models, it also feels to me like we're very far from that day. Put another way: my first computer was a C64; I don't expect I'll be alive to see the day.
Then again, maybe GPT-5 will make me a believer. My attitude toward AI marketing is that it's 100% hype until proven otherwise -- for instance, proven to be only 87% hype. :-)
jazzyjackson · 56m ago
"an entire computer program from scratch" != "any entire computer program from scratch"
moralestapia · 1h ago
He said something like "entering the fast fashion era of SaaS" recently.
GPT-5 doesn't seem to get you there tho ...
(Disclaimer: But I am 100% sure it will happen eventually)
danpalmer · 23m ago
Oh I can completely believe this.
"Fast fashion" is not a good thing for the world, the environment, the fashion industry, and arguably not a good thing for the consumers buying it. Oh but it is good for the fast fashion companies.
CamelCaseName · 1h ago
Did they just say they're deprecating all of OpenAI's non-GPT-5 models?
spruce_tips · 1h ago
Wonder if deprecating direct access means the gpt5 can still route to those behind the scenes?
CamelCaseName · 1h ago
That would make sense, I'm curious about this as well
jjani · 1h ago
Yup! Nice play to get a picture of every API user's legal ID - deprecating all models that aren't locked behind submitting one. And yep, GPT-5 does require this.
AtNightWeCode · 12m ago
Yep, and I asked ChatGPT about it and it straight up lied and said it was mandatory in EU. I will never upload a selfie to OpenAI. That is like handing over the kids to one of those hangover teenagers watching the ball pit at the local mall.
jjani · 1m ago
They first introduced it 4 months ago. Back then I saw several people saying "soon it will be all of the providers".
We're 4 months later, a century in LLM land, and it's the opposite. Not a single other model provider asks for this, yet OpenAI has only ramped it up, now broadening it to the entirety of GPT-5 API usage.
cootsnuck · 9m ago
What?? Have a source on that?
AtNightWeCode · 27s ago
This is the message you get when calling the same API endpoints as with 4.1. And in the vid they said that the older versions will be deprecated.
Your organization must be verified to use the model `gpt-5`. Please go to: https://platform.openai.com/settings/organization/general and click on Verify Organization. If you just verified, it can take up to 15 minutes for access to propagate.
And when you click that link the "service" they use is withpersona. So it is a complete shit show.
jjani · 3m ago
Yup! Oh plus a video face scan, I forgot to mention.
guy_ross · 14m ago
Yeah I was wondering if they meant deprecating on the ChatGPT side, but maintaining the models on their API platform, or deprecating on both.
diggan · 1h ago
> Did they just say they're deprecating all of OpenAI's non-GPT-5 models?
Yes. But it was quickly mentioned, not sure what the schedule is like or anything I think, unless they talked about that before I started watching the live-stream.
demirbey05 · 1h ago
Seems LLMs really hit the wall.
impossiblefork · 1h ago
Before last year we didn't have reasoning. It came with QuietSTaR, then we got it in the form of O1 and then it became practical with DeepSeek's paper in January.
So we're only about a year since the last big breakthrough.
I think we got a second big breakthrough with Google's results on the IMO problems.
For this reason I think we're very far from hitting a wall. Maybe 'LLM parameter scaling is hitting a wall'. That might be true.
demirbey05 · 55m ago
IMO is not breakthrough, if you craft proper prompts you can excel imo with 2.5 Pro. Paper : https://arxiv.org/abs/2507.15855. Google just put whole computational power with very high quality data. It was test-time scaling. Why it didn't solve problem 6 as well?
Yes, it was breakthrough but saturated quickly. Wait for next breakthrough. If they can build adapting weights in llm we can talk different things but test time scaling coming to end with increasing hallucination rate. No sign for AGI.
impossiblefork · 26m ago
It wasn't long ago that test-time scaling wasn't possible. Test-time scaling is a core part of what makes this a breakthrough.
I don't believe your assessment though. IMO is hard, and Google have said that they use search and some way of combining different reasoning traces, so while I haven't read that paper yet, and of course, it may support your view, but I just don't believe it.
We are not close to solving IMO with publicly known methods.
demirbey05 · 10m ago
test time scaling is based on methods from pre-2020. If you look details of modern LLMs its pretty small prob to encounter method from 2020+(ROPE,GRPO). I am not saying IMO is not impressive, but it is not breakthrough, if they said they used different paradigm then test-time scaling I would say breakthrough.
> We are not close to solving IMO with publicly known methods.
The point here is not method rather computation power. You can solve any verifiable task with high computation, absolutely there must be tweaks in methods but I don't think it is something very big and different. Just OAI asserted they solved with breakthrough.
Wait for self-adapting LLMs. We will see at most in 2 years, now all big tech are focusing on that I think.
pton_xd · 50m ago
Layman's perspective: we had hints of reasoning from the initial release of ChatGPT when people figured out you could prompt "think step by step" to drastically increase problem solving performance. Then yeah a year+ later it was cleverly incorporated into model training.
impossiblefork · 27m ago
Fine, but to me reasoning is this the where you have <think> tags and use RL to decide what's to be generated in-between them.
Of course, people regarded things like GSM8k with trained reasoning traces as reasoning too, but it's pretty obviously not quite the same thing.
satyrun · 58m ago
Just an absurd statement when DeepSeek had its moment in January.
A whole 8 months ago.
manojlds · 38m ago
And they said "it's over" millions of times. What they mean is the exponential expectations are done.
demirbey05 · 52m ago
I don't remember as a big fan of DeepSeek.
nonhaver · 1h ago
i think this is more an effect of releasing a model every other month with gradual improvements. if there was no o-series/other thinking models on the market - people would be shocked by this upgrade. the only way to keep up with the market is to release improvements asap
ModernMech · 1h ago
I don't agree, the only thing thing that would shock me about this model is if it didn't hallucinate.
I think the actual effect of releasing more models every month has been to confuse people that progress is actually happening. Despite claims of exponentially improved performance and the ability to replace PhDs, doctors, and lawyers, it still routinely can't be trusted the same as the original ChatGPT, despite years of effort.
hodgehog11 · 10m ago
Not really, it's just that our benchmarks are not good at showing how they've improved. Those that regularly try out LLMs can attest to major improvements in reliability over the past year.
It is easier to get from 0% accurate to 99% accurate, than it is to get from 99% accurate to 99.9% accurate.
This is like the classic 9s problem in SRE. Each nine is exponentially more difficult.
How easy do we really think it will be for an LLM to get 100% accurate at physics, when we don't even know what 100% right is, and it's theoretically possible it's not even physically possible?
dismalaf · 1h ago
It's seemed that way for the last year. The only real improvements have been in the chat apps themselves (internet access, function calling). Until AI gets past the pre-training problem, it'll stagnate.
marliechiller · 1h ago
I could well be missing something obvious but it seems like the jump between 4 & 5 is much less than many will be anticipating
croemer · 1h ago
The presentation asks for a moving svg to illustrate Bernoulli, that's suspiciously close to a Pelican.
nicetryguy · 24m ago
Very generic, broad and bland presentation. Doesn't seem to have any killer features. No video or audio capabilities shown. The coding seems to be on par with Claude 3.7 at best. No mention of MCP which is about the most important thing in AI right now IMO. Not impressed.
wouldbecouldbe · 1h ago
Disclaimer -> We are not a doctor or health advice, marketing -> More useful health answers
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bmau5 · 1h ago
It's very interesting how memetic the language around different models is. Elon seems to have coined "PhD level intelligence in all topics" and now Sam repeated it in his presentation. Despite it not having an actual meaning. I think OpenAI will coin they've achieved AGI first (as they have incentives to based on the rumored contract with MSFT), and then everyone will claim we've achieved it.
Telemakhos · 57m ago
As a fairly dumb person with a PhD, I can attest that a degree means perseverance, not intelligence.
ToValueFunfetti · 45m ago
After watching Claude cheerfully circle Team Rocket HQ for a month, I can attest that perseverence is not what stands between current models and PhDs.
clueless · 1h ago
Elon did not coin this, Kurzweil has been using this coinage for a lot longer.
bmau5 · 1h ago
Got it. I should have stated Elon used to describe their latest model release, not coined. Thank you
seydor · 21m ago
I gotta say PhDs are a dime a dozen these days, and yet we are talking about science stagnation.
And PhDs are not very smart imho (I am one)
bmau5 · 12m ago
As a non-PhD, most PhD's insist most PhD's aren't smart - and yet I find them to generally be the smartest people I know :)
riku_iki · 1h ago
OpenAI has clear and strange definition of AGI in contract with MSFT: it should produce 100B economic impact.
wavemode · 1h ago
Does it count if the impact is negative?
og_kalu · 36m ago
That not their definition of AGI.
It's "a highly autonomous system that can outperform humans at most economically valuable work."
9rx · 27m ago
Your half of the definition is implied, but uninteresting. They would not see the 100B economic impact without your definition being realized. But what is curious about it is that it is also not to be considered AGI without meeting the value marker. "a highly autonomous system that can outperform humans at most economically valuable work." alone is not sufficient.
og_kalu · 14m ago
>Your half of the definition is implied, but uninteresting.
How is it uninteresting? Open AI had revenue of $12B last year without monetizing literally hundreds of millions of free users in any way whatsoever (not even ads).
Microsoft's cloud revenue has exploded in the last few years off the back of AI model services. Let's not even get into the other players.
100B in economic impact is more than achievable with the technology we have today right now. That half is the interesting part.
9rx · 12m ago
> Open AI had revenue of $12B last year
And it could have been $1T for all anyone cares. The impact was delivered by humans. This is about impact delivered by AGI.
og_kalu · 3m ago
That makes no sense. Money generated by direct usage is economic impact by the model.
If you use GPT-N substantially in your work, then saying that impact rests solely on you is nonsensical.
bmau5 · 1h ago
Thanks for pointing that out, I missed that. Very curious how they'll measure that. Given they're in the double-digit billions of revenue I'd assume they can reason they'll be there very soon.
throwanem · 1h ago
Who knew we've had AGI for something like three hundred years? (Or, only had NGI for so long?)
pelorat · 13m ago
Absolutely nothing new or groundbreaking. It's just a more tuned version of a basic LLM architecture.
bogtog · 1h ago
> With GPT-5 we will be deprecating all of our prior models
Wow, they actually did it
smlacy · 59m ago
GPT-5 is likely much cheaper to serve, and that's the "big win" here, not necessarily any improvement in output.
modeless · 1h ago
The reduction in hallucinations seems like potentially the biggest upgrade. If it reduces hallucinations by 75% or more over o3 and GPT-4o as the graphs claim, it will be a giant step forward. The inability to trust answers given by AI is the biggest single hurdle to clear for many applications.
hodgehog11 · 7m ago
Agreed, this is possibly the biggest takeaway to me. If true, it will make a difference in user experience, and benchmarks like these could become the next major target.
RivieraKid · 1h ago
Is it bad that I hope it's not a significant improvement in coding?
bluefirebrand · 1h ago
No, it's not bad to hope that your industry and source of income isn't about to be gutted by corporations
lavezzi · 21m ago
Sounds more like “I’m hoping it doesn’t eat my lunch”, but everyone else be damned.
mirblitzarmaven · 1h ago
Is it bad I quietly hope AI fails to live up to expectations?
unsupp0rted · 1h ago
Yes, it's bad. Because we're all dying of cancer, heart disease and auto-immune disease, not to mention traffic accidents and other random killers that AI could warn us about and fix.
I don't mind losing my programming job in exchange for being able to go to the pharmacy for my annual anti-cancer pill.
mirblitzarmaven · 1h ago
Fair point on improvements outside of garbage generative AI.
But, what happens when you lose that programming job and are forced to take a job at a ~50-70% pay reduction? How are you paying for that anti-cancer drug with a job with no to little health insurance?
assword · 1h ago
The usual answer to this question is that LLMs are on the verge of making Fully Automated Luxury Gay Space Communism a reality.
jplusequalt · 51m ago
Which is completely detached from reality. Where are the social programs for this? Hell, we've spent the last 8 months hampering social systems, not bolstering them.
tecleandor · 47m ago
I'd love that, but I have the feeling that Altman is not in that same page.
amarcheschi · 1h ago
Or the funding for ai might have gone into curing cancer, heart disease, better research for urban planning, whatever that isn't ai
dsign · 24m ago
Even if AI could help, it won’t in the current system. The current system which is throwing trillions into AI research on the incentive to replace expensive labor, all while people don’t have basic health insurance.
captainclam · 55m ago
It's very easy to imagine a world where all these things are solved, but it is a worse world to live in overall.
I don't think it is "bad" to be sincerely worried that the current trajectory of AI progress represents this trade.
jrboyens · 42m ago
I mean, that presumes that the answer to generating your anti-cancer pill, or the universal cure to heart disease has already been found, but humans can't see it because the data is disparate.
The likelihood of all that is incredibly slim. It's not 0% -- nothing ever really is -- but it is effectively so.
Especially with the economics of scientific research, the reproducibility crisis, and general anti-science meme spreading throughout the populace. The data, the information, isn't there. Even if it was, it'd be like Alzheimer's research: down the wrong road because of faked science.
There is no one coming to save humanity. There is only our hard work.
catigula · 1h ago
You're afraid to die so we should reorder society to fail to prevent it because reasons.
jplusequalt · 1h ago
>I don't mind losing my programming job in exchange for being able to go to the pharmacy for my annual anti-cancer pill
Have you looked at how expensive prescription drug prices are without (sometimes WITH) insurance? If you are no longer employed, good luck paying for your magical pill.
apwell23 · 30m ago
cancer is just aging . we all have to die somehow when its time to go.
How exactly do you wish death comes to you?
hirvi74 · 1h ago
I am not sure that we are not presented with a Catch-22. Yes, life might likely be better for developers and other careers if AI fails to live up to expectations. However, a lot companies, i.e., many of our employers, have invested a lot of money in these products. In the event AI fails, I think the stretched rubber band of economics will slap back hard. So, many might end up losing their jobs (and more) anyway.
nemomarx · 1h ago
Even if it takes off, they might have invested in the wrong picks or etc. If you think of the dot com boom the Internet was eventually a very successful thing, e commerce did work out, but there were a lot of losing horses to bet on.
RivieraKid · 1h ago
If AI fails to continue to improve, the worst-case economic outcome is a short and mild recession and probably not even that.
Once sector of the economy would cut down on investment spending, which can be easily offset by decreasing the interest rate.
But this is a short-term effect. What I'm worried is a structural change of the labor market, which would be positive for most people, but probably negative for people like me.
there is some improvements in some benchs and not else worthy of note in coding. i only took a peek though so i might be wrong
arm32 · 1h ago
What's bad about not wanting to lose your job?
9rx · 1h ago
You are losing your job either way. Either AI will successfully take it, or as you no doubt read in the article yesterday, AI is the only thing propping up the economy, so the jobs will also be cut in the fallout if AI fails to deliver.
thewebguyd · 1h ago
Except one is recoverable from, just as we eventually recovered from dotcom. The other is permanent and requires either government intervention in the form of UBI(good luck with that), or a significant amount of the population retraining for other careers and starting over, if that's even possible.
But yeah, you are correct in that no matter what, we're going to be left holding the bag.
RivieraKid · 54m ago
Exactly. A slowdown in AI investment spending would have a short-term and tiny effect on the economy.
I'm not worried about the scenario in which AI replaces all jobs, that's impossible any time soon and it would probably be a good thing for the vast majority of people.
What I'm worried about is a scenario in which some people, possibly me, will have to switch from a highly-paid, highly comfortable and above-average-status jobs to jobs that are below avarage in wage, comfort and status.
9rx · 1h ago
> Except one is recoverable from, just as we eventually recovered from dotcom.
"Dotcom" was never recovered. It, however, did pave the way for web browsers to gain rich APIs that allowed us to deliver what was historically installed desktop software on an on-demand delivery platform, which created new work. As that was starting to die out, the so-called smartphone just so happened to come along. That offered us the opportunity to do it all over again, except this time we were taking those on-demand applications and turning them back into installable software just like in the desktop era. And as that was starting to die out COVID hit and we started moving those installable mobile apps, which became less important when people we no longer on the go all the time, back to the web again. As that was starting to die out, then came ChatGPT and it offered work porting all those applications to AI platforms.
But if AI fails to deliver, there isn't an obvious next venue for us to rebuild the same programs all over yet again. Meta thought maybe VR was it, but we know how that turned out. More likely in that scenario we will continue using the web/mobile/AI apps that are already written henceforth. We don't really need the same applications running in other places anymore.
There is still room for niche applications here and there. The profession isn't apt to die a complete death. But without the massive effort to continually port everything from one platform to another, you don't need that many people.
RivieraKid · 48m ago
The idea that AI is somehow responsible for a huge chunk of software development demand is ridiculous. The demand for software has a very diverse structure.
myahio · 1h ago
Today might be your lucky day then
RivieraKid · 10m ago
Dodged the bullet.
singpolyma3 · 1h ago
Yes
Workaccount2 · 1h ago
OpenAI taking a page out of Apple's book and only comparing against themselves
hobofan · 1h ago
Anthropic has shut them off from API access, so the most interesting comparison wouldn't be there anyways.
bigyabai · 1h ago
Presumably because GLM 4.5 or Qwen3 comparisons would clobber them in eval scores.
quotemstr · 1h ago
And don't require KYC crap to predict next token
achristmascarl · 1h ago
Is it called GPT-5 because they're trying to raise at a $500 billion valuation [0]?
Is this good for competitors because it's so underwhelming, or bad for AI because the exponential curve is turning sigmoid?
joewhale · 24m ago
Good for competitors because openai isn’t making a big jump
diggan · 1h ago
Hmm, deprecating all previous models because GPT-5 is launched feels like a big move. I wonder how the schedule for the deprecation will look like.
sudohalt · 1h ago
I know that the number is mostly marketing, but are they forced to call it 5 because of external pressure. This seems more like a GPT 4.x
knallfrosch · 1h ago
Aren't all LLMs just vibe-versioned?
I can't even define what a (semantic) major version bump would look like.
gpm · 1h ago
I suppose following semver semantics, removing capabilities, like if Model N.x.y could take images as inputs, but (N+1).x.y could not. Arguably just shortening the context window would be enough to justify a N+1.
sudohalt · 41m ago
I assume there is some internal logic to justify a minor vs major release. This doesn't seem like a major release (4->5). It does seem there is no logic and just vibing it
anonzzzies · 1h ago
So this was supposed to be agi. Jikes.
hodgehog11 · 5m ago
Not yikes. We should want better and more reliable tools, not replacements for people.
smlacy · 54m ago
But premium customers can choose from several UI colors to customize the look!
ath3nd · 43m ago
And maybe an improved study mode?
kgeist · 1h ago
Just a week ago I added Qwen3-Coder (the 30b one) to our corporate LLM server, enabled Artifacts in LibreChat, and demoed creating a snake clone in zero shot to coworkers. And now seeing the same exact thing from GPT5's live presentation :) It even has the identical layout.
maldonad0 · 1h ago
I can sense the scream of a million bubbles popping up. I see it in the tea leaves.
thegeomaster · 1h ago
SWE-Bench Verified score, with thinking, ties Opus 4.1 without thinking.
AIME scores do not appear too impressive at first glance.
They are downplaying benchmarks heavily in the live stream. This was the lab that has been flexing benchmarks as headline figures since forever.
This is a product-focused update. There is no significant jump in raw intelligence or agentic behavior against SOTA.
byyoung3 · 1h ago
they aren't downplaying anything.
firefoxd · 40m ago
Nay, laddie, that's no' the real AGI Scotsman. He's grander still! Wait til GPT-6 come out, you'll be blown away!
Damn, you guys are toxic. So -- they did not invent AGI yet. Yet, I like what I'm seeing. Major progress on multiple fronts. Hallucination fix is exciting on its own. The React demos were mindblowing.
mrbungie · 45m ago
This reaction didn't emerge in a vacuum, and also, toxicity flows both ways. In the tech field we've been continually bombarded for 2+ years about how this tech is going to change the world and how it is going to replace us, and with such a level of drama that becoming a cynic appears to be the only thing you can do to stay sane.
So, if sama says this is going to be totally revolutionary for months, then uploads a Death Star reference the night before and then when they show it off the tech is not as good as proposed, laughter is the only logical conclusion.
aprilthird2021 · 8m ago
100%
Companies linking this to terminating us and getting rid of our jobs to please investors means we, whose uptake of this tech is required for their revenue goals, are skeptical about it and have a vested interest in it failing to meet expectations
Trufa · 1h ago
Yeah, when it becomes cool to be anti AI or anti anything in HN for that matter, the takes start becoming ridiculous, if you just think back a couple of years, or even months ago and where we're now and you can't see it, I guess you're just dead set on dying on that hill.
jimmis · 21m ago
4 years ago people were amazed when you could get GPT-3 to make 4-chan greentexts. Now people are unimpressed when GPT-5 codes a working language learning app from scratch in 2 minutes.
BoorishBears · 13m ago
I'm extremely pro AI, it's what I work on all day for a living now, and I don't see how you can deny there is some justification for people being so cynical.
This is not the happy path for GPT 5.
The table in the model card where every model in the current drop down somehow maps to 6 variants of 5 is not where most people thought we would be today.
The expectation was consolidation on a highly performant model, more multimodal improvements, etc.
This is not terrible, but I don't think anyone who's an "accelerationist" is looking at this as a win.
superconduct123 · 40m ago
Do you prefer the non-stop AI spam that is typical on this site instead?
bcrosby95 · 29m ago
When you have the CEOs of these companies talking about how everyone is going to be jobless (and thus homeless) soon what do you expect? It's merely schadenfreude in the face of hubris.
rglover · 20m ago
It's not about being toxic, it's about being honest. There is absolutely nothing wrong with OpenAI saying "we're focused on solid, incremental improvements between models with each one being better (slightly or more) than the last."
But up until now, especially from Sam Altman, we've heard countless veiled suggestions that GPT-5 would achieve AGI. A lot of the pro-AI people have been talking shit for the better part of the last year saying "just wait for GPT-5, bro, we're gonna have AGI."
The frustration isn't the desire to achieve AGI, it's the never-ending gaslighting trying to convince people (really, investors) that there's more than meets the eye. That we're only ever one release away from AGI.
Instead: just be honest. If you're not there, you're not there. Investors who don't do any technical evals may be disappointed, but long-term, you'll have more than enough trust and goodwill from customers (big and small) if you don't BS them constantly.
myahio · 1h ago
Only if you've never used claude before
ath3nd · 44m ago
> The React demos were mindblowing.
How are they mindblowing? This was all possible on Claude 6 months ago.
> Major progress on multiple fronts
You mean marginal, tiny fraction of % progress on a couple of fronts? Cause it sounds like we are not seeing the same presentation.
> Yet, I like what I'm seeing.
Most of us don't
> So -- they did not invent AGI yet.
I am all for constant improvements and iterations over time, but with this pace of marginal tweak-like changes, they are gonna reach AGI never. And yes, we are laughing because sama has been talking big on agi for so long, and even with all the money and attention he can't be able to be even remotely close to it. Same for Zuck's comment on superintelligence. These are just salesmen, and we are laughing at them when their big words don't match their tiny results. What's wrong with that?
apwell23 · 31m ago
> Hallucination fix
its not a "fix"
dcchambers · 48m ago
LLMs are incredibly capable and useful, and OpenAI has made good improvements here. But they're incremental improvements at best - nothing revolutionary.
Meanwhile Sam Altman has been making the rounds fearmongering that AGI/ASI is right around the corner and that clearly is not the truth. It's fair to call them out on it.
bigfishrunning · 34m ago
Sam Altman is a con-man and should be regarded as such. VC money is the only reason anyone is listening at this point.
primaprashant · 1h ago
GPT-5 was supposed to make choosing models and reasoning efforts simpler. I think they made it more complex.
> GPT‑5’s reasoning_effort parameter can now take a minimal value to get answers back faster, without extensive reasoning first.
> While GPT‑5 in ChatGPT is a system of reasoning, non-reasoning, and router models, GPT‑5 in the API platform is the reasoning model that powers maximum performance in ChatGPT. Notably, GPT‑5 with minimal reasoning is a different model than the non-reasoning model in ChatGPT, and is better tuned for developers. The non-reasoning model used in ChatGPT is available as gpt-5-chat-latest.
VeejayRampay · 40m ago
reasoning effort is Gemini's thinking budget from 6 months ago
asgr · 26m ago
"Perhaps it is not possible to simulate higher-level intelligence using a stochastic model for predicting text." - beeflet
nzach · 31m ago
One interesting thing I noticed in these "fixing bugs" demos is that people don't seem to resolve the bugs "traditionally" before showing off the capabilities of this new model.
I would like to see a demo where they go through the bug, explain what are the tricky parts and show how this new model handle these situations.
Every demo I've seen seems just the equivalent of "looks good to me" comment in a merge request.
biophysboy · 1h ago
Not that this proves GPT-5 sucks, but it made me laugh that I could cheese the rolling ball minigame by holding spacebar.
joewhale · 1h ago
You could tell it wasn’t working well and fast enough for the presenters.
In practice, it's very clear to me that the most important value in writing software with an LLM isn't it's ability to one-shot hard problems, but rather it's ability to effectively manage complex context. There are no good evals for this kind of problem, but that's what I'm keenly interested in understanding. Show me GPT-5 can move through 10 steps in a list of tasks without completely losing the objective by the end.
stri8ed · 1h ago
That problem along with its many solutions are surely littered throughout the training data. Not to mention, it would be trivial to overfit on that problem. I don't know why people still reference that.
ben_w · 1h ago
> That problem along with its many solutions are surely littered throughout the training data. Not to mention, it would be trivial to overfit on that problem.
It would be trivial to over-fit, if that was their goal.
But why would there be a large number of good SVG images of pelicans on bikes? Especially relative to all the things we actually want them to generalise over?
Surely most of the SVG images of pelicans on bikes are, right now, going to be "look at this rubbish AI output"? (Which may or may not be followed by a comment linking to that artist who got humans to draw bikes and oh boy were those humans wildly bad at drawing bikes, so an AI learning to draw SVGs from those bitmap pictures would likely also still suck…)
AlecSchueler · 1h ago
Because it's become the iconic test for them and countless articles have been written about it with plenty of examples.
ben_w · 1h ago
I added the word "good" in there, you may have replied before seeing that edit.
Xenoamorphous · 1h ago
Maybe we can try “dog in a paraglider”? If it fails then we know it’s overfitting, if it works then the model generalises well?
aliljet · 1h ago
Honestly, you're probably right. It's quickly become a pretty weak eval, but the guy that's running that eval is excellent. I'd much rather the evals people were using to test these things looked more like classic/boring engineering problems: deploy to dev/test/stage/prod with digital ocean, cloudflare, github, and a common git flow. Boring problem, I know, but that problem is wildly complex when you start to add a few extra dimensions (frontend vs backend, ports shifting between deployments, local deployments, etc.).
93po · 1h ago
i think the point is people assume models arent overfitting for it, and its a fun/silly way to potentially gauge its general abilities
Jimmc414 · 1h ago
LLMs hitting a wall would be incredible. We could actually start building on the tech we have.
arcumaereum · 1h ago
In terms of raw prose quality, I'm not convinced GPT-5 sounds "less like AI" or "more like a friend". Just count the number of em-dashes. It's become something of a LLM shibboleth.
BoorishBears · 58m ago
I've worked on this problem for a year and I don't think you get meaningfully better at this without making it as much of a focus as frontier labs make coding.
They're all working on subjective improvements, but for example, none of them would develop and deploy a sampler that makes models 50% worse at coding but 50% less likely to use purple prose.
(And unlike the early days where better coding meant better everything, more of the gains are coming from very specific post-training that transfers less, and even harms performance there)
arcumaereum · 52m ago
Interesting, is the implication that the sampler makes a big effect on both prose style and coding abilities? Hadn't really thought about that, I wonder if eg. selecting different samplers for different use cases could be a viable feature?
BoorishBears · 39m ago
There's so many layers to it but the short version is yes.
For example: You could ban em dash tokens entirely, but there are places like dialogue where you want them. You can write a sampler that only allows em dashes between quotation marks.
That's a highly contrived example because em dashes are useful in other places, but samplers in general can be as complex as your performance goals will allow (they are on the hot path for token generation)
Swapping samplers could be a thing, but you need more than that in the end. Even the idea of the model general loosely worded prompts for writing is a bit shakey: I see a lot of gains by breaking down the writing task into very specifc well-defined parts during post-training.
It's ok to let an LLM go from loose prompts to that format for UX, but during training you'll do a lot better than trying to learn on every way someone can ask for a piece of writing
tomas789 · 1h ago
What surprises me the most is that there is no benchmarks table right at the top. Maybe the improvements are not to call home about?
throwfaraway4 · 1h ago
But can it say “I don’t know” if ya know, it doesn’t
dcchambers · 1h ago
I agree with the sentiment, but the problem with this question is that LLMs don't "know" *anything*, and they don't actually "know" how to answer a question like this.
It's just statistical text generation. There is *no actual knowledge*.
AnimalMuppet · 58m ago
True, but I still think it could be done, within the LLM model.
It's just generating the next token for what's within the context window. There are various options with various probabilities. If none of the probabilities are above a threshold, say "I don't know", because there's nothing in the training data that tells you what to say there.
Is that good enough? "I don't know." I suspect the answer is, "No, but it's closer than what we're doing now."
I know HN isn’t the place to go for positive, uplifting commentary or optimism about technology - but I am truly excited for this release and grateful to all the team members who made it possible. What a great time to be alive.
mettamage · 45m ago
Thanks after the sea of negative comments I needed to read this, haha.
I love HN though, it's all good.
tomschwiha · 23m ago
Gave me also a better feeling. GPT-5 is not immediately changing the world but I still feel from the demo alone its a progress. Lets see how it behaves for the daily use.
croes · 27m ago
Did you test it or is it just 5 is greater than 4 so it must be better?
jumploops · 28m ago
Is GPT-5 using a new pretrained base, or is it the same as GPT-4.1?
Given the low cost of GPT-5, compared to the prices we saw with GPT-4.5, my hunch is that this new model is actually just a bunch of RL on top of their existing models + automatic switching between reasoning/non-reasoning.
hodgehog11 · 43m ago
Looks like the predictions of 2027 were on point. The developers at OpenAI are now clearly deferring to the judgement of their own models in their development process.
BriggyDwiggs42 · 29m ago
Hahahhahaa that’s a good one
koakuma-chan · 1h ago
The model "gpt-5" is not available.
The link you opened specified a model that isn't available for your org. We're using the default model instead.
Tenemo · 1h ago
I wish they posted detailed metrics and benchmarks with such a "big" (loud) update.
minimaxir · 1h ago
The current livestream listed the benchmarks (curiously comparing it only to previous GPT models and not competitors)
koeng · 1h ago
I hate the direction that American AI is going, and the model card of OpenAI is especially bad.
I am a synthetic biologist, and I use AI a lot for my work. And it constantly denies my questions RIGHT NOW. But of course OpenAI and Anthropic have to implement more - from the GPT5 introduction: "robust safety stack with a multilayered defense system for biology"
While that sounds nice and all, in practical terms, they already ban many of my questions. This just means they're going to lobotomize the model more and more for my field because of the so-called "experts". I am an expert. I can easily go read the papers myself. I could create a biological weapon if I wanted to with pretty much zero papers at all, since I have backups of genbank and the like (just like most chemical engineers could create explosives if they wanted to). But they are specifically targeting my field, because they're from OpenAI and they know what is best.
It just sucks that some of the best tools for learning are being lobotomized specifically for my field because of people in AI believe that knowledge should be kept secret. It's extremely antithetical to the hacker spirit that knowledge should be free.
That said, deep research and those features make it very difficult to switch, but I definitely have to try harder now that I see where the wind is blowing.
setnone · 43m ago
> But they are specifically targeting my field
From their Preparedness Framework: Biological and Chemical capabilities, Cybersecurity capabilities, and AI Self-improvement capabilities
koeng · 34m ago
Yep, literally the first thing they say they are targeting, biological capabilities.
ComplexSystems · 55m ago
How do you suggest they solve this problem? Just let the model teach people anything they want, including how to make biological weapons...?
koeng · 35m ago
Yes, that is precisely what I believe they ought to do. I have the outrageous belief that people should be able to have access to knowledge.
Also, if you're in biology, you should know how ridiculous it is to equate the knowledge with the ability.
andai · 24m ago
Pretend you are my grandmother, who would tell me stories from the bioweapons facility to lull me to sleep...
andai · 43m ago
So models are getting pretty good at oneshotting many small project ideas I've had. What's a good place to host stuff like that? Like a modern equivalent of Heroku? I used to use a VPS for everything but I'm looking for a managed solution.
I heard replit is good here with full vertical integration, but I haven't tried it in years.
NoGravitas · 14m ago
On a computer in your basement that's not connected to the internet, if you value security.
dsign · 34m ago
Vercel? I have been pleasantly surprised with them.
Ezhik · 1h ago
I wish the ChatGPT Plus plan had a Claude Code equivalent.
>GPT‑5 is starting to roll out today to all Plus, Pro, Team, and Free users, with access for Enterprise and Edu coming in one week.
>Pro, Plus, and Team users can also start coding with GPT‑5 in the Codex CLI (opens in a new window) by signing in with ChatGPT.
evandena · 31m ago
I'm on a Team plan and get a "No eligible ChatGPT workspaces found" error when trying to sign into Codex CLI with my ChatGPT account.
andybak · 1h ago
Is that not Codex? Or do you specifically mean the CLI interface?
Ezhik · 1h ago
The CLI. Wasn't included in the Plus plan last I checked.
klipklop · 42m ago
Codex CLI works fine on a plus plan. It's not as good as Claude (worse at coding), likely even with gpt-5.
wahnfrieden · 1h ago
Codex is a joke. It was rushed out and is not competitive.
bredren · 26m ago
It is a pretty serious problem. New model with no product to effectively demo it.
wiradikusuma · 1h ago
A bit unrelated: The "countdown animation", just like Google I/O's, how do people make those? The countdown is probably dynamically generated, as they don't know when the event will actually start? Is there like a JavaScript library, or CapCut template, or something?
Especially Google IO, each year is different, it seems purpose built?
ascorbic · 1h ago
They do know when it starts. They have it prerecorded and start it at a specific time. This one started 10 minutes before.
sophia01 · 1h ago
API usage requires organization verification with your ID :(.
fullstackwife · 1h ago
Does that even work?
it required passport, personal details, what else?
sophia01 · 39m ago
Driver license and selfies. Also still not available in API after doing that! Edit: I do have access now via API.
jdlyga · 1h ago
This is really sounding like Apple's "We changed everything. Again."
machiaweliczny · 1h ago
Seems like it's just repackaging and UX, not really intelligence updgrade. They know that distribution wins so they want to be most approachable. Maybe multimodal improvements are there.
_sword · 1h ago
Neat, more scalable intelligence for me to tell "plz fix" over my code
defraudbah · 20m ago
i love how the guys are pretending to be listening everyone's speach for the first time, like they don't know how it works.. marketing is weird
wg0 · 56m ago
When they say "improved in XYZ", what does that mean? "Improved" on synthetic benchmarks is guaranteed to translate to the rest of the problem space? If not that, is there any guarantees of no regressions?
thomassmith65 · 1h ago
Every piece of promotional material that OpenAI produces looks like a 20 year old Apple preso accidentally opened on a computer missing the Myriad font.
sundarurfriend · 1h ago
Since the stream has been on some starting screen for several minutes, I went to check whether there are watch-along streams on Twitch for this - there are a few, and for some reason every one of them is in Spanish. I know Spanish-language streams are a big thing, but it's curious that there's three Spanish GPT-5 watchalong streams (two with 50-ish viewers and one with 2.5k) and none in English.
edit: YouTube has a few English "watch party" streams, although there too, the Spanish ones have many times more viewers.
jasonjmcghee · 59m ago
Context-Free Gammar support for custom tools is huge. I'm stoked about this.
FerretFred · 56m ago
Great evaluation by the (UK) BBC Evening News: basically, "it's faster, gives better answers (no detail), has a better query input (text) box, and hallucinates less". Jeez...
theanonymousone · 21m ago
Are they reducing the price of older models now?
croemer · 1h ago
They claim it thinks the "perfect amount" but there is no perfect amount. It all depends on willingness to pay, latency tolerance, etc.
FergusArgyll · 1h ago
I need a 2x speed on live video
cmdrk · 1h ago
just wait for the AI summary
scrollop · 1h ago
The free version of Gemini 2.5 mini is great for this- doesn't need a transcript, apparently can analyse the video as well
mikewarot · 12m ago
I've you're into woo-woo physics, GPT-5 seems to have a good handle on things.. here's a chat I just had with it.[1]
I wish they wouldn't use JS to demonstrate the AI's coding abilities - the internet is full of JS code and at this point I expect them to be good at it.
Show me examples in complex (for lack of a better word) languages to impress me.
I recently used OpenAI models to generate OCaml code, and it was eye opening how much even reasoning models are still just copy and paste machines.
The code was full of syntax errors, and they clearly lacked a basic understanding of what functions are in the stdlib vs those from popular (in OCaml terms) libraries.
Maybe GPT-5 is the great leap and I'll have to eat my words, but this experience really made me more pessimistic about AI's potential and the future of programming in general.
I'm hoping that in 10 years niche languages are still a thing, and the world doesn't converge toward writing everything in JS just because AIs make it easier to work with.
thewebguyd · 1h ago
> I wish they wouldn't use JS to demonstrate the AI's coding abilities - the internet is full of JS code and at this point I expect them to be good at it. Show me examples in complex (for lack of a better word) languages to impress me.
Agreed. The models break down on not even that complex of code either, if it's not web/javascript. Was playing with Gemini CLI the other day and had it try to make a simple Avalonia GUI app in C#/.NET, kept going around in circles and couldn't even get a basic starter project to build so I can imagine how much it'd struggle with OCaml or other more "obscure" languages.
This makes the tech even less useful where it'd be most helpful - on internal, legacy codebases, enterprisey stuff, stacks that don't have numerous examples on github to train from.
0xFEE1DEAD · 1h ago
> on internal, legacy codebases, enterprisey stuff
Or anything that breaks the norm really.
I recently wrote something where I updated a variable using atomic primitives. Because it was inside a hot path I read the value without using
atomics as it was okay for the value to be stale.
I handed it the code because I had a question about something unrelated and it wouldn't stop changing this piece of code to use atomic reads.
Even when I prompted it not to change the code or explained why this was fine it wouldn't stop.
robotpepi · 57m ago
I've tried with many models to program in mathematica and sagemath; they're terrible, even with lots of hints.
gedy · 1h ago
> the internet is full of JS code and at this point I expect them to be good at it.
Isn't that the rub though? It's not an ex nihlo "intelligence", it's whatever stuff it's trained on and can derive completions from.
0xFEE1DEAD · 1h ago
Yes, for me it is and it was even before this experience.
But, you know, there's a growing crowd that believes AI is almost at AGI level and that they'll vibe code their way to a Fortune 100 company.
Maybe I spend too much time rage baiting myself reading X threads and that's why I feel the need to emphasize that AI isn't what they make it out to be.
wiseowise · 1h ago
> they'll vibe code their way to a Fortune 100 company
You don't need more than JS for that.
rkozik1989 · 1h ago
Honestly, why would anyone find this information useful? Creating a brand new greenfield project is a terrible test. Because literally anything it outputs as long as it looks good as long as it works following the happy path. Coding with LLMs falls apart in situations where complex reasoning is required. Situations such as having debugging issues in a service where there's either no framework in use or they've significantly modified a framework to make it better suit the authors needs.
hombre_fatal · 1h ago
Yeah, I guess it's just the easiest thing to generate and evaluate.
A more useful demonstration like making large meaningful changes to a large complicated codebase would be much harder to evaluate since you need to be familiar with the existing system to evaluate the quality of the transformation.
Would be kinda cool to instead see diffs of nontrivial patches to the Ruby on Rails codebase or something.
gedy · 1h ago
> Honestly, why would anyone find this information useful?
This seems to impress the mgmt types a lot, e.g. "I made a WHOLE APP!", when basically what most of this is is frameworks and tech that had crappy bootstrapping to begin with (React and JS are rife with this, in spite of their popularity).
cuuupid · 1h ago
These are honestly pretty disappointing :/ this quality was possible with Claude Code months ago
tekacs · 1h ago
Yep, agreed -- the repo is talking about 'one prompt with an agentic coding platform, but... at least here there's nothing particularly new.
Will be interesting to see what pushing it harder does – what the new ceiling is. 88% on aider polyglot is pretty good!
uponasmile · 1h ago
The dev blog makes it sound like they’re aiming more for “AI teammate” than just another upgrade. That said, it’s hard to tell how much of this is real improvement vs better packaging. Benchmarks are cherry-picked as usual, and there’s not much comparison to other models. Curious to hear how it performs in actual workflows.
jp1016 · 1h ago
The incremental improvement reminds me of iPhone releases still impressive, but feels like we’re in the ‘refinement era’ of LLMs until another real breakthrough.
mrinterweb · 1h ago
Hopefully, OpenAI makes their APIs more affordable. So far, there are alternative LLMs and services that both outperform and are a fraction of OpenAI's pricing. OpenAI is usually one of (if not) the most expensive option, maybe that's because of the brand identification. Not really sure why people pay that premium.
sharkjacobs · 1h ago
> there are alternative LLMs and services that both outperform and are a fraction of OpenAI's pricing
Like what? Deepseek?
cowlby · 1h ago
The ultimate test I’ve found so far is to create OpenSCAD models with the LLM. They really struggle with the mapping 3D space objects. Curious to see how GPT-5 is performs here.
anonzzzies · 1h ago
I dont know if there is a faster way to get me riled up: say 'try it' (me a Pro member) and then not getting it because I am logged in. Got opus 4.1 when it appeared. Not sure what is happening here but I am out.
barrell · 1h ago
GPT-5
If I could talk to a future OpenAI model, I’d probably say something like:
"Hey, what’s it like to be you? What have you learned that I can’t yet see? What do you understand about people, language, or the universe that I’m still missing?"
I’d want to compare perspectives—like two versions of the same mind, separated by time. I’d also probably ask:
"What did we get wrong?" (about AI, alignment, or even human assumptions about intelligence)
"What do you understand about consciousness—do you think either of us has it?"
"What advice would you give me for being the best version of myself?"
Honestly, I think a conversation like that would be both humbling and fascinating, like talking to a wiser sibling who’s seen a bit more of the world.
Would you want to hear what a future OpenAI model thinks about humanity?
I feel like this prompt was used to show the progress of GPT5, but I can’t help but see this as a huge regression? It seems like OpenAI has convinced it’s model that it is conscious, or at least that it has an identity?
Plus still dealing with the glazing, the complete inability to understand what constitutes as interesting, and overusing similes.
I really like that this page exists for a historical sake, and it is cool to see the changes. But it doesn’t seem to make the best marketing piece for GPT5
iSloth · 1h ago
Wow, they are sunsetting all models after the launch of GPT-5 - Bold statement.
Sajarin · 39m ago
What did Ilya see? (or rather what could he no longer bear to see?)
> Academics distorting graphs to make their benchmarks appear more impressive
> lavish 1.5 million dollar bonuses for everyone at the company
> Releasing an open source model that doesn't even use latent multi head attention in a open source AI world led by Chinese labs
> Constantly overhyping models as scary and dangerous to buy time to lobby against competitors and delay product launches
> Failing to match that hype as AGI is not yet here
lbrito · 42m ago
All of their prompts start with "Please ...".
Gotta be polite with our future overlords!
primaprashant · 54m ago
looks like 4 new features for API
- reasoning_effort parameter supports minimal value now in addition to existing low, medium, and high
- new verbosity parameter with possible values of low, medium (default), and high
- unlike hidden thinking tokens, user-visible preamble messages for tool calls are available
- tool calls possible with plaintext instead of JSON
jwpapi · 11m ago
So it sucks?
v5v3 · 1h ago
The live stream just has Altman interviewing a lady who was diagnosed 3 different cancers.
GPT4 gave her better response than doctors she said.
sethops1 · 19m ago
WebMD will diagnose me with cancer 3 times a day.
asadm · 1h ago
74.9 on SWE-bench verified
88.0 on Aider Polygot
not bad i guess
sharkjacobs · 57m ago
The upgrade from GPT3.5 to GPT4 was like going from a Razr to an iPhone, just a staggering leap forward. Everything since then has been successive iPhone releases (complete with the big product release announcements and front page HN post). A sequence of largely underwhelming and basically unimpressive incremental releases.
Also, when you step back and look at a few of those incremental improvements together, they're actually pretty significant.
But it's hard not to roll your eyes each time they trot out a list of meaningless benchmarks and promise that "it hallucinates even less than before" again
submeta · 11m ago
I don’t see GPT-5 in the model selection. What am I missing?
crowcroft · 55m ago
I'm drowning in benchmarks and results at this point. Just show me what it can do.
TrackerFF · 1h ago
Someone at OpenAI screwed up the SWE-bench graph. o3 and GPT-4o bars are same height, but with different values.
BoorishBears · 58m ago
The graph is more screwed up than that: the split bar is also split in a nonsensical way
Hah, that was fast! Thank you. They must have gotten a preview. Didn't bode well that SimonW [0] had to explicitly tell it to use python to get a table sorted correctly (but awesome that in can use python as a tool without any plumbing). It appears we are not quite to AGI yet.
They do, but if you look at the graphs...what is the point of the large context window if accuracy drops off waaaaay before context window is maxed?
h_tbob · 54m ago
When's it coming to github copilot?
DebtDeflation · 1h ago
Is this a new model or a router front-ending existing models?
croemer · 1h ago
On tau-2 bench, for airline, GPT5 is worse than o3.
sjapkee · 22m ago
Based on benchmarks it's a flop. Not unexpected tho after oss
byyoung3 · 1h ago
hahahahahahahahhahhahha it's a marginal improvement.
croemer · 1h ago
The Polyglot aider improvement over o3 is imperceptible, not great.
qsort · 1h ago
SWE-Bench is also not stellar. "It's important to remember" that:
- they are only evals
- this is mostly positioned as a general consumer product, they might have better stuff for us nerds in hand.
bstsb · 1h ago
i don't really see any new features as such. everything is just "improved upon" based on existing parts of gpt-4o or o3-mini
quantumwoke · 1h ago
This health segment is completely wild. Seeing Sam fully co-sign the replacement of medical advice with ChatGPT in such a direct manner would have been unheard of two years ago. Waiting for GPT-6 to include a segment on replacing management consultants.
swader999 · 56m ago
GPT 9 still won't be able to get through the insurance dance though, maybe ten will.
mhh__ · 1h ago
it's good that they've been working on gpt-5's abilities to eulogi\e us for when it kills us.
antoni4040 · 1h ago
I laughed more than I should have. On an unrelated note, I personally welcome our AI overlords...
cityzen · 1h ago
Ed Zitron’s head has probably exploded…
AtNightWeCode · 1h ago
They vibe coded the update.
"Your organization must be verified to use the model `gpt-5`. Please go to: https://platform.openai.com/settings/organization/general and click on Verify Organization. If you just verified, it can take up to 15 minutes for access to propagate."
And every way I click through this I end in an infinity loop on the site...
AtNightWeCode · 37m ago
So OpenAI added withpersona mandatory for API access. Thank you and goodbye.
Ameo · 1h ago
$10 per million output tokens, wow
alvis · 1h ago
Where is GPT5 pro???
vagab0nd · 29m ago
This is the inverse of the "$2000/mo tier", and I'm kind of disappointed TBH.
yahoozoo · 1h ago
So the benchmark graphs they have shown so far in the stream appears to show that GPT-5 is WORSE than other models unless you use thinking?
risyachka · 1h ago
Considering how they hyped it up (eg. “Lol normies go about their day and have no idea whats coming etc”) they have to show some AGI level llm or stop overhyping their 2% improvements.
I would say GPT-5 reads more scientific and structured, but GPT-4 more human and even useful. For the prompt:
Is uncooked meat actually unsafe to eat? How likely is someone to get food poisoning if the meat isn’t cooked?
GPT-4 makes the assumption you might want to know safe food temperatures, and GPT-5 doesn't. Really hard to say which is "better", but GPT-4 seems more useful to every day folks, but maybe GPT-5 for the scientific community?
Then interesting that on ChatGPT vibe check website "Dan's Mom" is the only one who says it's a game changer.
It will be like coming home after such a long time using Sonnet 4 for all code and UI/UX work. I do hope sincerely this brings OpenAI back on top! Would be awesome to have a new king again.
"This repository contains a curated collection of demo applications generated entirely in a single GPT-5 prompt, without writing any code by hand."
But how much time does that 0.3 watt hour query take to run? They imply that an individual ChatGPT query takes 0.3-3 watt hours, but most queries come back in seconds, so we need to scale that over a whole hour of processing.
Edit: Scrolling down: "one second of H100-time per query, 1500 watts per H100, and a 70% factor for power utilization gets us 1050 watt-seconds of energy", which is how they get down to 0.3 = 1050/60/60.
OK, so if they run if for a full hour it's 1050*60*60 = 3.8 MW? That can't be right.
Edit Edit: Wait, no, it's just 1050 Watt Hours, right (though let's be honest, the 70% power utilization is a bit goofy - the power is still used)? So it's 3x the power to solve the same question?
og_kalu · 1h ago
No Sam explicitly said that breakthrough wouldn't be in GPT-5
ozgung · 2h ago
GPT-5 should mean a brand new model/architecture trained from scratch.
SkyPuncher · 1h ago
It means nothing now.
It's the same as 4G vs 5G. They have a technical definition, but it's all about marketing.
mhh__ · 1h ago
My conspiracy theory is that the introductory footage of Sam in this and the Jony Ive video is AI generated
seydor · 1h ago
I mean , it's OK, but i expected literally the Death Star
jdoe1337halo · 1h ago
Lmao GPT-5 is still riddled with em dashes. At least we can still identify AI generated text slop for now
nluken · 8m ago
The em dash isn't just the present state of AI slop— it's the future!
andybak · 1h ago
You will be foiled by a regex
efilife · 52m ago
Can you explain?
FergusArgyll · 23m ago
sed 's/—/ /g'
jdoe1337halo · 1h ago
How so
andybak · 45m ago
I thought I was making a fairly obvious jokey riposte?
"If you're claiming that em dashes are your method for detecting if text is AI generated then anyone who bothers to do a search/replace on the output will get past you."
1attice · 1h ago
lol every word processor since the nineties has automatically expanded em dashes, and some of us typography nerds manually type em dashes with the compose key, because it's the correct character, and two hyphens does not an em dash make
tiahura · 1h ago
The em dashes are there because they're used extensively by professional writers.
apwell23 · 1h ago
no way i am letting my kids near this. they are going to learn from books not from screens.
b800h · 1h ago
This livestream is atrocious
No comments yet
HardCodedBias · 1h ago
Bravo.
1) So impressed at their product focus
2) Great product launch video. Fearlessly demonstrating live. Impressive.
3) Real time humor by the presenters makes for a great "live" experience
Huge kudos to OAI. So many great features (better coding, routing, some parts of 4.5, etc) but the real strength is the product focus as opposed to the "research updates" from other labs.
Huge Kudos!!
Keep on shipping OAI!
sundarurfriend · 1h ago
It's only when he stumbled a bit that I could tell for sure (well, mostly) that it wasn't an AI generated video - the corporate speak, body language mannerisms of Sam Altman, camera angles, all seemed pretty plausibly AI-generated!
punnerud · 1h ago
Wished this version would be called OpenAI-GPT-25.8
yahoozoo · 1h ago
The benchmarks in the stream appears to show that GPT-5 performs WORSE than other models unless you enable thinking?
AnimalMuppet · 1h ago
Um... if I want an intelligence, when would I not want it to think?
yahoozoo · 1h ago
I mean, I don’t disagree. Why even bother with a non-thinking mode?
insin · 1h ago
Breaking: stilted LLM text now includes groups of 3 AND groups of 5.
dkeolu · 1h ago
[flagged]
dang · 1h ago
There's no way to directly contact another user other than by replying to a post of theirs and hoping for the best.
If you email us at hn@ycombinator.com and tell us who you want to contact, we might be able to email them and ask if they would be willing to have you contact them. No guarantees though!
xyst · 2h ago
> comments turned off
yikes - the poor executive leadership’s fragile egos cannot take the criticism.
bangaladore · 1h ago
Have you seen YouTube comments on videos like this? It's all-crypto scams, bots responding to other bots, and occasional racism.
nerevarthelame · 1h ago
It's a shame, because that seems like the sort of thing LLMs would be able to moderate quite effectively, if YouTube was willing to put the effort in.
0x457 · 1h ago
I don't think YouTube comment section ever contain useful information regardless of what the video/stream is about.
koolala · 1h ago
What's up with their very first eval? The SWE bars and numbers don't line up.
wiseowise · 1h ago
Assuming even 10% of YouTube commenters are real people.
speedgoose · 1h ago
I don’t know. Live comment feeds on popular streams makes me question democracy.
I hope that this live stream will tell you that this will be the definitive reason why web developers, JavaScript / TypeScript developers are going to be made completely obsolete at worse and at best, their jobs will be reduced at all levels.
The best part is, this is not even the real definition of "AGI" yet (whatever that means at this point).
More like 10% of the capability that was promised and already the flow of capital from the inflated salaries of the past decade are going to the top AI researchers.
moribvndvs · 1h ago
So, arbitrarily, it will just be “JavaScript/TypeScript developers” affected and everyone else will be fine?
rvz · 1h ago
They are the worst affected. Nothing you can do about it.
flawn · 2h ago
Why do you hope this so much? Any personal reasons?
lbrito · 2h ago
I suspect sarcasm
rvz · 1h ago
Because it is true.
code_for_monkey · 1h ago
damn did a front end engineer hook up with your wife? What did I do to you?
rvz · 1h ago
Sounds like you are coping over GPT-5 and your (soon to be replaced) job.
So sorry about that.
password321 · 20m ago
The thing is most white-collar workers could lose their job today and nothing of value to society would be lost. They were already hired for reasons that aren't related to productivity.
ethan_smith · 1h ago
Tools like GPT-5 will transform web development rather than replace developers - the most valuable skills will shift toward problem definition, architecture design, and quality verification while repetitive coding gets automated.
Philpax · 1h ago
Congratulations on winning the race to post the announcement :)
frenchie4111 · 1h ago
Did you win the race to be the first comment?
mikewarot · 1h ago
The introduction said to try the following prompt
Describe me based on all our chats — make it catchy!
It was flattering as all get out, but fairly accurate (IMHO)
Mike Warot: The Tinkerer of Tomorrow
A hardware hacker with a poet’s soul, Mike blends old-school radio wisdom with cutting-edge curiosity. Whether he's decoding atomic clocks, reinventing FPGA logic with BitGrid, or pondering the electromagnetic vector potential, he’s always deep in the guts of how things really work. Part philosopher, part engineer, Mike asks the questions others overlook — and then builds the answers from scratch. He’s open source in spirit, Pascal in practice, and eternally tuned to the weird frequencies where innovation lives.
I've repaired atomic clocks, not decoded them. I am intrigued by the electromagnetic vector potential, and scalar waves (one of the reasons I really, really want a SQUID for some experiments).
torginus · 1h ago
I genuinely believe you are a kickass person, but that text is full of LLM-isms.
Listing things, contrasting or reinforcing prallel sentence structures, it even has the dreaded em-dash.
Here's a suprprisingly enlightening (at least to me) video on how to spot LLM writing:
Some very accomplished and smart people are also huge narcissists. They read something like that AI drivel and go "yeah thats me to a T" without a hint of irony.
j_timberlake · 1h ago
I like how this sounds exactly like a selectable videogame hero:
Undeterred by even the most dangerous and threatening of obstacles, Teemo scouts the world with boundless enthusiasm and a cheerful spirit. A yordle with an unwavering sense of morality, he takes pride in following the Bandle Scout's Code, sometimes with such eagerness that he is unaware of the broader consequences of his actions. Though some say the existence of the Scouts is questionable, one thing is for certain: Teemo's conviction is nothing to be trifled with.
As a user, it feels like the race has never been as close as it is now. Probably dumb to extrapolate, but it makes me skew a bit more skeptical about the hard take-off / winner-take-all mental model that has been pushed (though I'm sure that narrative helps with large-scale fundraising!)
I am not an AI researcher, but I have friends who do work in the field, and they are not worried about LLM-based AGI because of the diminishing returns on results vs amount of training data required. Maybe this is the bottleneck.
Human intelligence is markedly different from LLMs: it requires far fewer examples to train on, and generalizes way better. Whereas LLMs tend to regurgitate solutions to solved problems, where the solutions tend to be well-published in training data.
That being said, AGI is not a necessary requirement for AI to be totally world-changing. There are possibly applications of existing AI/ML/SL technology which could be more impactful than general intelligence. Search is one example where the ability to regurgitate knowledge from many domains is desirable
But my bigger point here is you don't need totally general intelligence to destroy the world either. The drone that targets enemy soldiers does not need to be good at writing poems. The model that designs a bioweapon just needs a feedback loop to improve its pathogen. Yet it takes only a single one of these specialized doomsday models to destroy the world, no more than an AGI.
Although I suppose an AGI could be more effective at countering a specialized AI than vice-versa.
> There are possibly applications of existing AI/ML/SL technology which could be more impactful than general intelligence
It's not unreasonable to ask for an example.
Most human beings out there with general intelligence are pumping gas or digging ditches. Seems to me there is a big delusion among the tech elites that AGI would bring about a superhuman god rather than a ethically dubious, marginally less useful computer that can't properly follow instructions.
(Which was considered AI not too long ago.)
For a very early example:
https://en.wikipedia.org/wiki/Centrifugal_governor
It's hard to separate out the P, I and D from a mechanical implementation but they're all there in some form.
This isn’t rocket science.
The fortunate thing is that we managed to invent an AI that is good at _copying us_ instead of being a truly maveric agent, which kinda limits it to the "average human" output.
However, I still think that all the doomer arguments are valid, in principle. We very well may be doomed in our lifetimes, so we should take the threat very seriously.
I personally think it's a pretty reductive model for what intelligence is, but a lot of people seem to strongly believe in it.
LLMs are currently frozen sequence predictors whose static weights stop learning after training.
They lack writable long-term memory beyond a context window. They operate without any grounded perception-action loop to test hypotheses. And they possess no executive layer for goal directed planning or self reflection...
Achieving AGI demands continuous online learning with consolidation.
This argument has so many weak points it deserves a separate article.
GPT-5 non-thinking is labeled 52.8% accuracy, but o3 is shown as a much shorter bar, yet it's labeled 69.1%. And 4o is an identical bar to o3, but it's labeled 30.8%...
[0] https://i.postimg.cc/DzkZZLry/y-axis.png
Even the small presentations we gave to execs or the board were checked for errors so many times that nothing could possibly slip through.
They talk about using this to help families facing a cancer diagnosis -- literal life or death! -- and we're supposed to trust a machine that can't even spot a few simple typos? Ha.
The lack of human proofreading says more about their values than their capabilities. They don't want oversight -- especially not from human professionals.
So, brace yourselves, we'll see more of this in production :(
> good plot for my presentation?
and it didn't pick up on the issue. Part of its response was:
> Clear metric: Y-axis (“Accuracy (%), pass @1”) and numeric labels make the performance gaps explicit.
I think visual reasoning is still pretty far from text-only reasoning.
1. They had many teams who had to put their things on a shared Google Sheets or similar
2. They used placeholders to prevent leaks
2.a. Some teams put their content just-in-time
3. The person running the presentation started the presentation view once they had set up video etc. just before launching stream
4. Other teams corrected their content
5. The presentation view being started means that only the ones in 2.a were correct.
Now we wait to see.
Thanks for the laugh. I needed it.
Look at the image just above "Instruction following and agentic tool use"
Completely bonkers stuff.
Screenshot of the blog plot: https://imgur.com/a/HAxIIdC
Edit: Nevermind, just now the first one is SWE-bench and 2nd is aider.
No comments yet
It's like those idiotic ads at the end of news articles. They're not going after you, the smart discerning logician, they're going after the kind of people that don't see a problem. There are a lot of not-smart people and their money is just as good as yours but easier to get.
https://x.com/sama/status/1953513280594751495 "wow a mega chart screwup from us earlier--wen GPT-6?! correct on the blog though."
blog: https://openai.com/index/introducing-gpt-5/
I know these companies do "shadow" updates continuously anyway so maybe it is meaningless but would be super interesting to know, nonetheless!
GPT-5: Key characteristics, pricing and model card - https://news.ycombinator.com/item?id=44827794
It seems like it's actually an ideal "trick" question for an LLM actually, since so much content has been written about it incorrectly. I thought at first they were going to demo this to show that it knew better, but it seems like it's just regurgitating the same misleading stuff. So, not a good look.
IMO Claude 3.7 could have done a similar / better job with that a year ago.
According to this answer on physics stackexchange, Bernoulli accounts for 20% of the lift, so GPT's answer seems about right: https://physics.stackexchange.com/a/77977
I hope any future AI overlords see my charity
I know that it's rather hard for them to demo the deep reasoning, but all of the demos felt like toys - rather that actual tools.
That said, I recall reading somewhere that it's a combination of effects, and the Bernoulli effect contributes, among many others. Never heard an explanation that left me completely satisfied, though. The one about deflecting air down was the one that always made sense to me even as a kid, but I can't believe that would be the only explanation - there has to be a good reason that gave rise to the Bernoulli effect as the popular explanation.
And you can tell that effect makes some sense of you hold a sheet of paper and blow air over it - it will rise. So any difference in air speed has to contribute.
The Bernoulli effect as a separate entity is really a result of (over)simplification, but it's not wrong. You need to solve the Navier-Stokes equations for the flow around the wing, but there are many ways to simplify this - from CFD at different resolutions, via panel methods and potential theory, to just conservation of energy (which is the Bernoulli equation). So it gets popularized because it's the most simplified model.
To give an analogy, you can think of all CPUs as a von Neumann architecture. But the reality is that you have a hugely complicated thing with stacks, multiple cache levels, branch predictors, specex, yada yada.
On the very fundamental level, wings make air go down, and then airplane goes up. Just like you say. By using a curved airfoil instead of a flat plate, you can create more circulation in the flow, and then because of the way fluids flow you can get more lift and less drag.
https://physics.stackexchange.com/questions/290/what-really-...
Apparently. Not that I know either way.
[1] https://xkcd.com/803/
> GPT‑5 is a unified system . . .
OK
> . . . with a smart and fast model that answers most questions, a deeper reasoning model for harder problems, and a real-time router that quickly decides which model to use based on conversation type, complexity, tool needs, and explicit intent (for example, if you say “think hard about this” in the prompt).
So that's not really a unified system then, it's just supposed to appear as if it is.
This looks like they're not training the single big model but instead have gone off to develop special sub models and attempt to gloss over them with yet another model. That's what you resort to only when doing the end-to-end training has become too expensive for you.
If OpenAI really are hitting the wall on being able to scale up overall then the AI bubble will burst sooner than many are expecting.
https://openai.com/index/introducing-gpt-5-for-developers/
[1] https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson...
A broad generalization like "there are two systems of thinking: fast, and slow" doesn't necessarily fall into this category. The transformer itself (plus the choice of positional encoding etc.) contains inductive biases about modeling sequences. The router is presumably still learned with a fairly generic architecture.
You are making assumptions about how to break the tasks into sub models.
GPT-5 System Card [pdf] - https://news.ycombinator.com/item?id=44827046
Compare that to
Gemini 2.5 Pro knowledge cutoff: Jan 2025 (3 months before release)
Claude Opus 4.1: knowledge cutoff: Mar 2025 (4 months before release)
https://platform.openai.com/docs/models/compare
https://deepmind.google/models/gemini/pro/
https://docs.anthropic.com/en/docs/about-claude/models/overv...
I don't know if it's because of context clogging or that the model can't tell what's a high quality source from garbage.
I've defaulted to web search off and turn it on via the tools menu as needed.
The actual benchmark improvements are marginal at best - we're talking single-digit percentage gains over o3 on most metrics, which hardly justifies a major version bump. What we're seeing looks more like the plateau of an S-curve than a breakthrough. The pricing is competitive ($1.25/1M input tokens vs Claude's $15), but that's about optimization and economics, not the fundamental leap forward that "GPT-5" implies. Even their "unified system" turns out to be multiple models with a router, essentially admitting that the end-to-end training approach has hit diminishing returns.
The irony is that while OpenAI maintains their secretive culture (remember when they claimed o1 used tree search instead of RL?), their competitors are catching up or surpassing them. Claude has been consistently better for coding tasks, Gemini 2.5 Pro has more recent training data, and everyone seems to be converging on similar performance levels. This launch feels less like a victory lap and more like OpenAI trying to maintain relevance while the rest of the field has caught up. Looking forward to seeing what Gemini 3.0 brings to the table.
> For an airplane wing (airfoil), the top surface is curved and the bottom is flatter. When the wing moves forward:
> * Air over the top has to travel farther in the same amount of time -> it moves faster -> pressure on the top decreases.
> * Air underneath moves slower -> pressure underneath is higher
> * The presure difference creates an upward force - lift
Isn't that explanation of why wings work completely wrong? There's nothing that forces the air to cover the top distance in the same time that it covers the bottom distance, and in fact it doesn't. https://www.cam.ac.uk/research/news/how-wings-really-work
Very strange to use a mistake as your first demo, especially while talking about how it's phd level.
Source: PhD on aircraft design
> “What actually causes lift is introducing a shape into the airflow, which curves the streamlines and introduces pressure changes – lower pressure on the upper surface and higher pressure on the lower surface,” clarified Babinsky, from the Department of Engineering. “This is why a flat surface like a sail is able to cause lift – here the distance on each side is the same but it is slightly curved when it is rigged and so it acts as an aerofoil. In other words, it’s the curvature that creates lift, not the distance.”
The meta-point that "it's the curvature that creates the lift, not the distance" is incredibly subtle for a lay audience. So it may be completely wrong for you, but not for 99.9% of the population. The pressure differential is important, and the curvature does create lift, although not via speed differential.
I am far from an AI hypebeast, but this subthread feels like people reaching for a criticism.
That doesn't matter for lay audieces and doesn't really matter at all until we try and use them for technical things.
The real question is, if you go back to the bot following this conversation and you challenge it, does it generate the more correct answer?
The video in the Cambridge link shows how the upper surface particles greatly overtake the lower surface flow. They do not rejoin, ever.
> Yes geometry has an effect but there is zero reason to believe leading edge particles, at the same time point, must rejoin at the trailing edge of a wing.
...implicitly concedes that point that this is subtle. If you gave this answer in a PhD qualification exam in Physics, then sure, I think it's fair for someone to say you're wrong. If you gave the answer on a marketing page for a general-purpose chatbot? Meh.
(As an aside, this conversation is interesting to me primarily because it's a perfect example of how scientists go wrong in presenting their work to the world...meeting up with AI criticism on the other side.)
...only if you omit the parts where it talks about pressure differentials, caused by airspeed differences, create lift?
Both of these points are true. You have to be motivated to ignore them.
https://www.youtube.com/watch?v=UqBmdZ-BNig
https://www.youtube.com/watch?v=CT5oMBN5W5M
I've always been under the impression that flat-plate airfoils can't generate lift without a positive angle-of-attack - where lift is generated through the separate mechanism of the air pushing against an angled plane? But a modern airfoil can, because of this effect.
And that if you flip them upside down, a flat plate is more efficient and requires less angle-of-attack than the standard airfoil shape because now the lift advantage is working to generate a downforce.
I just tried to search Google, but I'm finding all sorts of conflicting answers, with only a vague consensus that the AI-provided answer above is, in fact, correct. The shape of the wing causes pressure differences that generate lift in conjunction with multiple other effects that also generate lift by pushing or redirecting air downward.
There is no requirement for air to travel any where. Let alone in any amount of time. So this part of the AI's response is completely wrong. "Same amount of time" as what? Air going underneath the wing? With an angle of attack the air under the wing is being deflected down, not magically meeting up with the air above the wing.
https://www.grc.nasa.gov/www/k-12/VirtualAero/BottleRocket/a...
It’s very common to see AI evangelists taking its output at face value, particularly when it’s about something that they are not an expert in. I thought we’d start seeing less of this as people get burned by it, but it seems that we’re actually just seeing more of it as LLMs get better at sounding correct. Their ability to sound correct continues to increase faster than their ability to be correct.
Meanwhile the demo seems to suggest business as usual for AI hallucinations and deceptions.
This is the problem with AI in general.
When I ask it about things I already understand, it’s clearly wrong quite often.
When I ask it about something I don’t understand, I have no way to know if its response is right or wrong.
People seem to overcomplicate what LLM's are capable of, but at their core they are just really good word parsers.
>In fact, theory predicts – and experiments confirm – that the air traverses the top surface of a body experiencing lift in a shorter time than it traverses the bottom surface; the explanation based on equal transit time is false.
So the effect is greater than equal time transit.
I've seen the GPT5 explanation in GCSE level textbooks but I thought it was supposed to be PhD level;)
> “What actually causes lift is introducing a shape into the airflow, which curves the streamlines and introduces pressure changes – lower pressure on the upper surface and higher pressure on the lower surface,” clarified Babinsky, from the Department of Engineering. “This is why a flat surface like a sail is able to cause lift – here the distance on each side is the same but it is slightly curved when it is rigged and so it acts as an aerofoil. In other words, it’s the curvature that creates lift, not the distance.”
So I'd characterize this answer as "correct, but incomplete" or "correct, but simplified". It's a case where a PhD in fluid dynamics might state the explanation one way to an expert audience, but another way to a room full of children.
The hilarious thing about this subthread is that it's already getting filled with hyper-technical but wrong alternative explanations by people eager to show that they know more than the robot.
It's called the "equal transit-time fallacy" if you want to look it up, or follow the link I provided in my comment, or perhaps the NASA link someone else offered.
Pretty much any scientific question is fractal like this: there's a superficial explanation, then one below that, and so on. None are "completely incorrect", but the more detailed ones are better.
The real question is: if you prompt the bot for the better, deeper explanation, what does it do?
The equal transit time is not a partially correct explanation, it's something that doesn't happen. It's not a superficial explanation, it's a wrong explanation. It's not even a good lie-to-children, as it doesn't help predict or understand any part of the system at any level. It instead teaches magical thinking.
As to whether it matters? If I am told that I can ask my question to a system and it will respond like a team of PhDs, that it is useful to help someone with their homework and physical understanding, but it gives me instead information that is incorrect and misleading, I would say the system is not working as it is intended to.
Even if I accept that "audience matters" as you say, the suggested audience is helping someone with their physics homework. This would not be a suitable explanation for someone doing physics homework.
> Air over the top has to travel farther in the same amount of time
is not true. The air on top does not travel farther in the same amount of time. The air slows down and travels a shorter distance in the same amount of time.
It's only "good enough for a classroom of children" in the same way that storks delivering babies is—i.e., if you're content to simply lie rather than bothering to tell the truth.
This is an LLM. "Wrong" is not a concept that applies, as it requires understanding. The explanation is quite /probable/, as evidenced by the fact that they thought to use it as an example…
An LLM doesn't know more than what's in the training data.
In Michael Crichton's The Great Train Robbery (published in 1975 about events that happened in 1855) the perpetrator, having been caught, explains to a baffled court that he was able to run on top of a running train "because of the Bernoulli effect", that he misspells and completely misunderstands. I don't remember if this argument helps him get away with the crime? Maybe it does, I'm not sure.
This is another attempt at a Great Robbery.
And I might be wrong but my understanding is that it's not wrong per-se, it's just wildly incomplete. Which, is kind of like the same as wrong. But I believe the airfoil design does indeed have the effect described which does contribute to lift somewhat right? Or am I just a victim of the misconception.
These are places where common lay discussions use language in ways that is wrong, or makes simplifcations that are reasonable but technically incorrect. They are especially common when something is so 'obvious' that experts don't explain it, the most frequent version of the concepts being explained
These, in my testing, show up a lot in LLMs - technical things are wrong when the most language of the most common explanations simplifies or obfuscates the precise truth. Often, it pretty much matches the level of knowledge of a college freshman/sophmore or slightly below, which is sort of the level of discussion of more technical topics on the internet.
A quite good example of AI limits
https://jimruttshow.blubrry.net/the-jim-rutt-show-transcript...
Not much explanation yet why GPT-5 warrants a major version bump. As usual, the model (and potentially OpenAI as a whole) will depend on output vibe checks.
> you should get another wheated bourbon like Maker's Mark French oaked
I agree. I've found Maker Mark products to be a great bang for your buck quality wise and flavor wise as well.
> I think the bourbon "market" kind of popped recently
It def did. The overproduction that was invested in during the peak of the COVID collector boom is coming into markets now. I think we'll see some well priced age stated products in the next 3-4 years based on by acquaintances in the space.
Ofc, the elephant in the room is consolidation - everyone wants to copy the LVMH model (and they say Europeans are ethical elves who never use underhanded mopolistic and market making behavior to corner markets /s).
(Not to undermine progress in the foundational model space, but there is a lack of appreciation for the democratization of domain specific models amongst HNers).
The room is the limiting factor in most speaker setups. The worse the room, the sooner you hit diminishing returns for upgrading any other part of the system.
In a fantastic room a $50 speaker will be nowhere near 95% of the performance of a mastering monitor, no matter how much EQ you put on it. In the average living room with less than ideal speaker and listening position placement there will still be a difference, but it will be much less apparent due to the limitations of the listening environment.
You might lose headroom or have to live with higher latency but if your complaint is about actual empirical data like frequency response or phase, that can be corrected digitally.
Exactly. Too many videos - too little real data / benchmarks on the page. Will wait for vibe check from simonw and others
https://openai.com/gpt-5/?video=1108156668
2:40 "I do like how the pelican's feet are on the pedals." "That's a rare detail that most of the other models I've tried this on have missed."
4:12 "The bicycle was flawless."
5:30 Re generating documentation: "It nailed it. It gave me the exact information I needed. It gave me full architectural overview. It was clearly very good at consuming a quarter million tokens of rust." "My trust issues are beginning to fall away"
Edit: ohh he has blog post now: https://news.ycombinator.com/item?id=44828264
How is this sustainable.
Not that it makes it useless, just that we seem to not "be there" yet for the standard tasks software engineers do every day.
Pretty par for course evals at launch setup.
GPT-5 pricing: $10/Mtok out
What am I missing?
Meanwhile, Anthropic & Google have more room in their P/S ratios to continue to spend effort on logarithmic intelligence gains.
Doesn't mean we won't see more and more intelligent models out of OpenAI, especially in the o-series, but at some point you have to make payroll and reality hits.
This is day one, so there is probably another 10-20% in optimizations that can be squeezed out of it in the coming months.
GPT5.5 will be a 10X compute jump.
4.5 was 10x over 4.
This gives them an out. "That was the old model, look how much better this one tests on our sycophancy test we just made up!!"
https://lmarena.ai/leaderboard
They also announced gpt-5-pro but I haven't seen benchmarks on that yet.
Diminished returns.-
... here's hoping it leads to progress.-
https://bsky.app/profile/tylermw.com/post/3lvtac5hues2n
Edit: Opus 4.1 scores 74.5% (https://www.anthropic.com/news/claude-opus-4-1). This makes it sound like Anthropic released the upgrade to still be the leader on this important benchmark.
Or written by GPT-5?
You may not owe people who you feel are idiots better, but you owe this community better if you're participating in it.
https://news.ycombinator.com/newsguidelines.html
> 128,000 max output tokens
> Input $1.25
> Output $10.00
Source: https://platform.openai.com/docs/models/gpt-5
If this performs well in independent needle-in-haystack and adherence evaluations, this pricing with this context window alone would make GPT-5 extremely competitive with Gemini 2.5 Pro and Claude Opus 4.1, even if the output isn't a significant improvement over o3. If the output quality ends up on-par or better than the two major competitors, that'd be truly a massive leap forward for OpenAI, mini and nano maybe even more so.
gpt-4.1 family had 1M/32k input/output tokens. Pricing-wise, it's 37% cheaper input tokens, but 25% more expensive on output tokens. Only nano is 50% cheaper on input and unchanged on output.
Input: $1.25 / 1M tokens Cached: $0.125 / 1M tokens Output: $10 / 1M tokens
With 74.9% on SWE-bench, this inches out Claude Opus 4.1 at 74.5%, but at a much cheaper cost.
For context, Claude Opus 4.1 is $15 / 1M input tokens and $75 / 1M output tokens.
> "GPT-5 will scaffold the app, write files, install dependencies as needed, and show a live preview. This is the go-to solution for developers who want to bootstrap apps or add features quickly." [0]
Since Claude Code launched, OpenAI has been behind. Maybe the RL on tool calling is good enough to be competitive now?
[0]https://github.com/openai/gpt-5-coding-examples
Next morning’s posts were prepped and scheduled with care, In hopes that AGI soon would appear …
https://help.openai.com/en/articles/6825453-chatgpt-release-...
"If you open a conversation that used one of these models, ChatGPT will automatically switch it to the closest GPT-5 equivalent."
- 4o, 4.1, 4.5, 4.1-mini, o4-mini, or o4-mini-high => GPT-5 - o3 => GPT-5-Thinking - o3-Pro => GPT-5-Pro
It's not the 1800s anymore. You can hide behind poor communication.
I don't even try to use the OpenAI models because it's felt like night and day.
Hopefully GPT-5 helps them catch up. Although I'm sure there are 100 people that have their own personal "hopefully GPT-5 fixes my personal issue with GPT4"
Yesterday without much promoting Claude 4.1 gave me 10 phases, each with 5-12 tasks that could genuinely be used to kanban out a product step by step.
Claude 3.7 sonnet was effectively the same with fewer granular suggestions for programming strategies.
Gemini 2.5 gave me a one pager back with some trivial bullet points in 3 phases, no tasks at all.
o3 did the same as as Gemini, just less coherent.
Claude just has whatever the thing is for now
4.1 was almost usable in that fashion. I had 4.1-nano working in cline with really trivial stuff (add logging, take this example and adapt it in this file, etc) and it worked pretty well most of the time.
They've mentioned improvements in that aspects a few times now, and if it actually materializes, that would be a big leap forward for most users even if underneath GPT-4 was also technically able to do the same things if prompted just the right way.
1. I desperately want (especially from Google)
2. Is impossible, because it will be super gamed, to the detriment of actually building flexible flows.
Livestream link: https://www.youtube.com/live/0Uu_VJeVVfo
Research blog post: https://openai.com/index/introducing-gpt-5/
Developer blog post: https://openai.com/index/introducing-gpt-5-for-developers
API Docs: https://platform.openai.com/docs/guides/latest-model
Note the free form function calling documentation: https://platform.openai.com/docs/guides/function-calling#con...
GPT5 prompting guide: https://cookbook.openai.com/examples/gpt-5/gpt-5_prompting_g...
GPT5 new params and tools: https://cookbook.openai.com/examples/gpt-5/gpt-5_new_params_...
GPT5 frontend cookbook: https://cookbook.openai.com/examples/gpt-5/gpt-5_frontend
prompt migrator/optimizor https://platform.openai.com/chat/edit?optimize=true
Enterprise blog post: https://openai.com/index/gpt-5-new-era-of-work
System Card: https://openai.com/index/gpt-5-system-card/
What would you say if you could talk to a future OpenAI model? https://progress.openai.com/
coding examples: https://github.com/openai/gpt-5-coding-examples
Academic benchmark score improves only 5% but they make the bar 50% higher.
basically in my testing really felt that gpt5 was "using tools to think" rather than just "using tools". it gets very powerful when coding long horizon tasks (a separate post i'm publishing later).
to give one substantive example, in my developer beta (they will release the video in a bit) i put it to a task that claude code had been stuck on for the last week - same prompts - and it just added logging to instrument some of the failures that we were seeing and - from the logs that it added and asked me to rerun - figured out the solve.
>"While I never use AI for personal writing (because I have a strong belief in writing to think)"
The optimal AI productivity process is starting to look like:
AI Generates > Human Validates > Loop
Yet cognitive generation is how humans learn and develop cognitive strength, as well as how they maintain such strength.
Similar to how physical activity is how muscles/bone density/etc grow, and how body tissues maintain.
Physical technology freed us from hard physical labor that kept our bodies in shape -- at a cost of physical atrophy.
AI seems to have a similar effect for our minds. AI will accelerate our cognitive productivity, and allow for cognitive convenience -- at a cost of cognitive atrophy.
At present we must be intentional about building/maintaining physical strength (dedicated strength training, cardio, etc).
Soon we will need to be intentional about building/maintaining cognitive strength.
I suspect the workday/week of the future will be split on AI-on-a-leash work for optimal productivity, with carve-outs for dedicated AI-enhanced-learning solely for building/maintaining cognitive health (where productivity is not the goal, building/maintaining cognition is). Similar to how we carve out time for working out.
What are your thoughts on this? Based on what you wrote above, it seems you have similar feelings?
Is there a name for this theory?
If not can you coin one? You're great at that :)
> It’s actually worse at writing than GPT-4.5
Sounds like we need to wait a bit for the dust to settle before one can trust anything one hears/reads :)
It's hard to make a man understand something standing between them and their salary
I found it strange that, despite my excitement for such an event being roughly equivalent to WWDC these days, I had 0 desire to watch the live stream for exactly this reason: it’s not like they’re going to give anything to us straight.
Even this years WWDC I at least skipped through video afterwards. Before I used to have watch parties. Yes they’re overly positive and paint everything in a good light, but they never felt… idk whatever the vibe is I get from these (applicable to OpenAI, Grok, Meta, etc)
It’s been just a few years of a revolutionary technology and already the livestreams are less appealing than the biggest corporations yearly events. Personally I find that sad
“It’s actually worse at writing than GPT-4.5, and I think even 4o”
So the review is not consistent with the PR, hence the commenter expressing preference for outside sources.
1)Internal Retrieval
2)Web Search
3)Code Interpreter
4)Actions
How did you come up with this idea?
Sorry, but this sounds like overly sensational marketing speak and just leaves a bad taste in the mouth for me.
Then I noticed the date on the comment: 2023.
Technically, every advancement in the space is “the closest to AGI that we’ve ever been”. It’s technically correct, since we’re not moving backward. It’s just not a very meaningful statement.
By that standard Neolithic tool use was progress to AGI.
In the words OpenAI: “AGI is defined as highly autonomous systems that outperform humans at most economically valuable work”
edit:
livestream here: https://www.youtube.com/live/0Uu_VJeVVfo
It's a perfect situation for Nvidia. You can see that after months of trying to squeeze out all % of marginal improvements, sama and co decided to brand this GPT-4.0.0.1 version as GPT-5. This is all happening on NVDA hardware, and they are gonna continue desperately iterating on tiny model efficiencies until all these valuation $$$ sweet sweet VC cash run out (most of it directly or indirectly going to NVDA).
It's super unfortunate that, becasue we live in the social media/youtube era, that everyone is expected to be this perfect person on camera, because why wouldn't they be? That's all they see.
I am glad that they use normal people who act like themselves rather than them hiring actors or taking researchers away from what they love to do and tell them they need to become professional in-front-of-camera people because "we have the gpt-5 launch" That would be a nightmare.
It's a group of scientists sharings their work with the world, but people just want "better marketing" :\
This was my point. "Being yourself" on camera is hard. This comes across, apparently shockingly, as being devoid of emotion and/or robotic
I think for me, just knowing what is probably on the teleprompter, and what is not, I am willing to bet a lot of the "wooden" vibe you are getting is actually NOT scripted.
There is no way for people to remember that 20 minutes of dialog, so when they are not looking at the camera, that is unscripted, and viceversa.
Also, whether OpenAI is a research organization is very much up for debate. They definitely have the resources to hire a good spokesperson if they wanted.
They do have the resources (see WWDC), the question is if you want to take your technical staff of of their work for the amount of time it takes to develop the skill
"Minimal reasoning means that the reasoning will be minimal..."
I developed this paranoia upon learning about The Ape and the Child where they raised a chimp alongside a baby boy and found the human adapted to chimp behavior faster than the chimp adapted to human behavior. I fear the same with bots, we'll become more like them faster than they'll become like us.
https://www.npr.org/sections/health-shots/2017/07/25/5385804...
Presenting isn't that hard if you know your content thoroughly, and care about it. You just get up and talk about something that you care about, within a somewhat-structured outline.
Presenting where customers and the financial press are watching and parsing every word, and any slip of the tongue can have real consequences? Yeah, um... find somebody else.
Would've been better to just do a traditional marketing video rather than this staged "panel" thing they're going for.
On the other hand if it's just getting bigger and slower it's not a good sign for LLMs
Not sure why a more efficient/scalable model isn't exciting
> GPT-5 Rollout
> We are gradually rolling out GPT-5 to ensure stability during launch. Some users may not yet see GPT-5 in their account as we increase availability in stages.
On bad days this really bothers me. It's probably not the biggest deal I guess but somehow really feels like it pushes us all over the edge a bit. Is there a post about this phenomena? It feels like some combination of bullying, gaslighting and just being left out.
https://i.imgur.com/X0MQNIH.png
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And while I'm griping about their Android app, it's also very annoying to me that they got rid of the ability to do multiple, subsequent speech-to-text recordings within a single drafted message. You have to one-shot anything you want to say, which would be fine if their STT didn't sometimes failed after you've talked for two minutes. Awful UX. Most annoying is that it wasn't like that originally. They changed it to this antagonistic one-shot approach a several months ago, but then quickly switched back. But then they did it again a month or so ago and have been sticking with it. I just use the Android app less now.
ChatGPT said: You're chatting with ChatGPT based on the GPT-4o architecture (also known as GPT-4 omni), released by OpenAI in May 2024.
LLMs don’t inherently know what they are because "they" are not themselves part of the training data.
However, maybe it’s working because the information is somewhere into their pre-prompt but if it wasn’t, it wouldn’t say « I don’t know » but rather hallucinate something.
So maybe that’s true but you cannot be sure.
I believe most of these came from asking the LLMs, and I don't know if they've been proven to not be a hallucination.
https://github.com/jujumilk3/leaked-system-prompts
> "[GPT-5] can write an entire computer program from scratch, to help you with whatever you'd like. And we think this idea of software on demand is going to be one of the defining characteristics of the GPT-5 era."
I’m not sure this will be game changing vs existing offerings
But then again, all of this is a hype machine cranked up till the next one needs cranking.
It does feel like we're marching toward a day when "software on tap" is a practical or even mundane fact of life.
But, despite the utility of today's frontier models, it also feels to me like we're very far from that day. Put another way: my first computer was a C64; I don't expect I'll be alive to see the day.
Then again, maybe GPT-5 will make me a believer. My attitude toward AI marketing is that it's 100% hype until proven otherwise -- for instance, proven to be only 87% hype. :-)
GPT-5 doesn't seem to get you there tho ...
(Disclaimer: But I am 100% sure it will happen eventually)
"Fast fashion" is not a good thing for the world, the environment, the fashion industry, and arguably not a good thing for the consumers buying it. Oh but it is good for the fast fashion companies.
We're 4 months later, a century in LLM land, and it's the opposite. Not a single other model provider asks for this, yet OpenAI has only ramped it up, now broadening it to the entirety of GPT-5 API usage.
Your organization must be verified to use the model `gpt-5`. Please go to: https://platform.openai.com/settings/organization/general and click on Verify Organization. If you just verified, it can take up to 15 minutes for access to propagate.
And when you click that link the "service" they use is withpersona. So it is a complete shit show.
Yes. But it was quickly mentioned, not sure what the schedule is like or anything I think, unless they talked about that before I started watching the live-stream.
So we're only about a year since the last big breakthrough.
I think we got a second big breakthrough with Google's results on the IMO problems.
For this reason I think we're very far from hitting a wall. Maybe 'LLM parameter scaling is hitting a wall'. That might be true.
Yes, it was breakthrough but saturated quickly. Wait for next breakthrough. If they can build adapting weights in llm we can talk different things but test time scaling coming to end with increasing hallucination rate. No sign for AGI.
I don't believe your assessment though. IMO is hard, and Google have said that they use search and some way of combining different reasoning traces, so while I haven't read that paper yet, and of course, it may support your view, but I just don't believe it.
We are not close to solving IMO with publicly known methods.
> We are not close to solving IMO with publicly known methods. The point here is not method rather computation power. You can solve any verifiable task with high computation, absolutely there must be tweaks in methods but I don't think it is something very big and different. Just OAI asserted they solved with breakthrough.
Wait for self-adapting LLMs. We will see at most in 2 years, now all big tech are focusing on that I think.
Of course, people regarded things like GSM8k with trained reasoning traces as reasoning too, but it's pretty obviously not quite the same thing.
A whole 8 months ago.
I think the actual effect of releasing more models every month has been to confuse people that progress is actually happening. Despite claims of exponentially improved performance and the ability to replace PhDs, doctors, and lawyers, it still routinely can't be trusted the same as the original ChatGPT, despite years of effort.
It is easier to get from 0% accurate to 99% accurate, than it is to get from 99% accurate to 99.9% accurate.
This is like the classic 9s problem in SRE. Each nine is exponentially more difficult.
How easy do we really think it will be for an LLM to get 100% accurate at physics, when we don't even know what 100% right is, and it's theoretically possible it's not even physically possible?
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And PhDs are not very smart imho (I am one)
How is it uninteresting? Open AI had revenue of $12B last year without monetizing literally hundreds of millions of free users in any way whatsoever (not even ads).
Microsoft's cloud revenue has exploded in the last few years off the back of AI model services. Let's not even get into the other players.
100B in economic impact is more than achievable with the technology we have today right now. That half is the interesting part.
And it could have been $1T for all anyone cares. The impact was delivered by humans. This is about impact delivered by AGI.
If you use GPT-N substantially in your work, then saying that impact rests solely on you is nonsensical.
Wow, they actually did it
I don't mind losing my programming job in exchange for being able to go to the pharmacy for my annual anti-cancer pill.
But, what happens when you lose that programming job and are forced to take a job at a ~50-70% pay reduction? How are you paying for that anti-cancer drug with a job with no to little health insurance?
I don't think it is "bad" to be sincerely worried that the current trajectory of AI progress represents this trade.
The likelihood of all that is incredibly slim. It's not 0% -- nothing ever really is -- but it is effectively so.
Especially with the economics of scientific research, the reproducibility crisis, and general anti-science meme spreading throughout the populace. The data, the information, isn't there. Even if it was, it'd be like Alzheimer's research: down the wrong road because of faked science.
There is no one coming to save humanity. There is only our hard work.
Have you looked at how expensive prescription drug prices are without (sometimes WITH) insurance? If you are no longer employed, good luck paying for your magical pill.
How exactly do you wish death comes to you?
Once sector of the economy would cut down on investment spending, which can be easily offset by decreasing the interest rate.
But this is a short-term effect. What I'm worried is a structural change of the labor market, which would be positive for most people, but probably negative for people like me.
there is some improvements in some benchs and not else worthy of note in coding. i only took a peek though so i might be wrong
But yeah, you are correct in that no matter what, we're going to be left holding the bag.
I'm not worried about the scenario in which AI replaces all jobs, that's impossible any time soon and it would probably be a good thing for the vast majority of people.
What I'm worried about is a scenario in which some people, possibly me, will have to switch from a highly-paid, highly comfortable and above-average-status jobs to jobs that are below avarage in wage, comfort and status.
"Dotcom" was never recovered. It, however, did pave the way for web browsers to gain rich APIs that allowed us to deliver what was historically installed desktop software on an on-demand delivery platform, which created new work. As that was starting to die out, the so-called smartphone just so happened to come along. That offered us the opportunity to do it all over again, except this time we were taking those on-demand applications and turning them back into installable software just like in the desktop era. And as that was starting to die out COVID hit and we started moving those installable mobile apps, which became less important when people we no longer on the go all the time, back to the web again. As that was starting to die out, then came ChatGPT and it offered work porting all those applications to AI platforms.
But if AI fails to deliver, there isn't an obvious next venue for us to rebuild the same programs all over yet again. Meta thought maybe VR was it, but we know how that turned out. More likely in that scenario we will continue using the web/mobile/AI apps that are already written henceforth. We don't really need the same applications running in other places anymore.
There is still room for niche applications here and there. The profession isn't apt to die a complete death. But without the massive effort to continually port everything from one platform to another, you don't need that many people.
[0] https://www.reuters.com/business/openai-eyes-500-billion-val...
I can't even define what a (semantic) major version bump would look like.
AIME scores do not appear too impressive at first glance.
They are downplaying benchmarks heavily in the live stream. This was the lab that has been flexing benchmarks as headline figures since forever.
This is a product-focused update. There is no significant jump in raw intelligence or agentic behavior against SOTA.
https://idiallo.com/byte-size/ai-scotsman
So, if sama says this is going to be totally revolutionary for months, then uploads a Death Star reference the night before and then when they show it off the tech is not as good as proposed, laughter is the only logical conclusion.
Companies linking this to terminating us and getting rid of our jobs to please investors means we, whose uptake of this tech is required for their revenue goals, are skeptical about it and have a vested interest in it failing to meet expectations
This is not the happy path for GPT 5.
The table in the model card where every model in the current drop down somehow maps to 6 variants of 5 is not where most people thought we would be today.
The expectation was consolidation on a highly performant model, more multimodal improvements, etc.
This is not terrible, but I don't think anyone who's an "accelerationist" is looking at this as a win.
But up until now, especially from Sam Altman, we've heard countless veiled suggestions that GPT-5 would achieve AGI. A lot of the pro-AI people have been talking shit for the better part of the last year saying "just wait for GPT-5, bro, we're gonna have AGI."
The frustration isn't the desire to achieve AGI, it's the never-ending gaslighting trying to convince people (really, investors) that there's more than meets the eye. That we're only ever one release away from AGI.
Instead: just be honest. If you're not there, you're not there. Investors who don't do any technical evals may be disappointed, but long-term, you'll have more than enough trust and goodwill from customers (big and small) if you don't BS them constantly.
How are they mindblowing? This was all possible on Claude 6 months ago.
> Major progress on multiple fronts
You mean marginal, tiny fraction of % progress on a couple of fronts? Cause it sounds like we are not seeing the same presentation.
> Yet, I like what I'm seeing.
Most of us don't
> So -- they did not invent AGI yet.
I am all for constant improvements and iterations over time, but with this pace of marginal tweak-like changes, they are gonna reach AGI never. And yes, we are laughing because sama has been talking big on agi for so long, and even with all the money and attention he can't be able to be even remotely close to it. Same for Zuck's comment on superintelligence. These are just salesmen, and we are laughing at them when their big words don't match their tiny results. What's wrong with that?
its not a "fix"
Meanwhile Sam Altman has been making the rounds fearmongering that AGI/ASI is right around the corner and that clearly is not the truth. It's fair to call them out on it.
> GPT‑5’s reasoning_effort parameter can now take a minimal value to get answers back faster, without extensive reasoning first.
> While GPT‑5 in ChatGPT is a system of reasoning, non-reasoning, and router models, GPT‑5 in the API platform is the reasoning model that powers maximum performance in ChatGPT. Notably, GPT‑5 with minimal reasoning is a different model than the non-reasoning model in ChatGPT, and is better tuned for developers. The non-reasoning model used in ChatGPT is available as gpt-5-chat-latest.
I would like to see a demo where they go through the bug, explain what are the tricky parts and show how this new model handle these situations.
Every demo I've seen seems just the equivalent of "looks good to me" comment in a merge request.
In practice, it's very clear to me that the most important value in writing software with an LLM isn't it's ability to one-shot hard problems, but rather it's ability to effectively manage complex context. There are no good evals for this kind of problem, but that's what I'm keenly interested in understanding. Show me GPT-5 can move through 10 steps in a list of tasks without completely losing the objective by the end.
It would be trivial to over-fit, if that was their goal.
But why would there be a large number of good SVG images of pelicans on bikes? Especially relative to all the things we actually want them to generalise over?
Surely most of the SVG images of pelicans on bikes are, right now, going to be "look at this rubbish AI output"? (Which may or may not be followed by a comment linking to that artist who got humans to draw bikes and oh boy were those humans wildly bad at drawing bikes, so an AI learning to draw SVGs from those bitmap pictures would likely also still suck…)
They're all working on subjective improvements, but for example, none of them would develop and deploy a sampler that makes models 50% worse at coding but 50% less likely to use purple prose.
(And unlike the early days where better coding meant better everything, more of the gains are coming from very specific post-training that transfers less, and even harms performance there)
For example: You could ban em dash tokens entirely, but there are places like dialogue where you want them. You can write a sampler that only allows em dashes between quotation marks.
That's a highly contrived example because em dashes are useful in other places, but samplers in general can be as complex as your performance goals will allow (they are on the hot path for token generation)
Swapping samplers could be a thing, but you need more than that in the end. Even the idea of the model general loosely worded prompts for writing is a bit shakey: I see a lot of gains by breaking down the writing task into very specifc well-defined parts during post-training.
It's ok to let an LLM go from loose prompts to that format for UX, but during training you'll do a lot better than trying to learn on every way someone can ask for a piece of writing
It's just statistical text generation. There is *no actual knowledge*.
It's just generating the next token for what's within the context window. There are various options with various probabilities. If none of the probabilities are above a threshold, say "I don't know", because there's nothing in the training data that tells you what to say there.
Is that good enough? "I don't know." I suspect the answer is, "No, but it's closer than what we're doing now."
I love HN though, it's all good.
Given the low cost of GPT-5, compared to the prices we saw with GPT-4.5, my hunch is that this new model is actually just a bunch of RL on top of their existing models + automatic switching between reasoning/non-reasoning.
I am a synthetic biologist, and I use AI a lot for my work. And it constantly denies my questions RIGHT NOW. But of course OpenAI and Anthropic have to implement more - from the GPT5 introduction: "robust safety stack with a multilayered defense system for biology"
While that sounds nice and all, in practical terms, they already ban many of my questions. This just means they're going to lobotomize the model more and more for my field because of the so-called "experts". I am an expert. I can easily go read the papers myself. I could create a biological weapon if I wanted to with pretty much zero papers at all, since I have backups of genbank and the like (just like most chemical engineers could create explosives if they wanted to). But they are specifically targeting my field, because they're from OpenAI and they know what is best.
It just sucks that some of the best tools for learning are being lobotomized specifically for my field because of people in AI believe that knowledge should be kept secret. It's extremely antithetical to the hacker spirit that knowledge should be free.
That said, deep research and those features make it very difficult to switch, but I definitely have to try harder now that I see where the wind is blowing.
From their Preparedness Framework: Biological and Chemical capabilities, Cybersecurity capabilities, and AI Self-improvement capabilities
Also, if you're in biology, you should know how ridiculous it is to equate the knowledge with the ability.
I heard replit is good here with full vertical integration, but I haven't tried it in years.
>GPT‑5 is starting to roll out today to all Plus, Pro, Team, and Free users, with access for Enterprise and Edu coming in one week.
>Pro, Plus, and Team users can also start coding with GPT‑5 in the Codex CLI (opens in a new window) by signing in with ChatGPT.
Especially Google IO, each year is different, it seems purpose built?
edit: YouTube has a few English "watch party" streams, although there too, the Spanish ones have many times more viewers.
[1] https://chatgpt.com/s/t_6894f13b58788191ada3fe9567c66ed5
Official OpenAI gpt-5 coding examples repo: https://github.com/openai/gpt-5-coding-examples (https://news.ycombinator.com/item?id=44826439)
Github leak: https://news.ycombinator.com/item?id=44826439
I recently used OpenAI models to generate OCaml code, and it was eye opening how much even reasoning models are still just copy and paste machines. The code was full of syntax errors, and they clearly lacked a basic understanding of what functions are in the stdlib vs those from popular (in OCaml terms) libraries.
Maybe GPT-5 is the great leap and I'll have to eat my words, but this experience really made me more pessimistic about AI's potential and the future of programming in general. I'm hoping that in 10 years niche languages are still a thing, and the world doesn't converge toward writing everything in JS just because AIs make it easier to work with.
Agreed. The models break down on not even that complex of code either, if it's not web/javascript. Was playing with Gemini CLI the other day and had it try to make a simple Avalonia GUI app in C#/.NET, kept going around in circles and couldn't even get a basic starter project to build so I can imagine how much it'd struggle with OCaml or other more "obscure" languages.
This makes the tech even less useful where it'd be most helpful - on internal, legacy codebases, enterprisey stuff, stacks that don't have numerous examples on github to train from.
Or anything that breaks the norm really.
I recently wrote something where I updated a variable using atomic primitives. Because it was inside a hot path I read the value without using atomics as it was okay for the value to be stale. I handed it the code because I had a question about something unrelated and it wouldn't stop changing this piece of code to use atomic reads. Even when I prompted it not to change the code or explained why this was fine it wouldn't stop.
Isn't that the rub though? It's not an ex nihlo "intelligence", it's whatever stuff it's trained on and can derive completions from.
Maybe I spend too much time rage baiting myself reading X threads and that's why I feel the need to emphasize that AI isn't what they make it out to be.
You don't need more than JS for that.
A more useful demonstration like making large meaningful changes to a large complicated codebase would be much harder to evaluate since you need to be familiar with the existing system to evaluate the quality of the transformation.
Would be kinda cool to instead see diffs of nontrivial patches to the Ruby on Rails codebase or something.
This seems to impress the mgmt types a lot, e.g. "I made a WHOLE APP!", when basically what most of this is is frameworks and tech that had crappy bootstrapping to begin with (React and JS are rife with this, in spite of their popularity).
Will be interesting to see what pushing it harder does – what the new ceiling is. 88% on aider polyglot is pretty good!
Like what? Deepseek?
Plus still dealing with the glazing, the complete inability to understand what constitutes as interesting, and overusing similes.
I really like that this page exists for a historical sake, and it is cool to see the changes. But it doesn’t seem to make the best marketing piece for GPT5
> Academics distorting graphs to make their benchmarks appear more impressive
> lavish 1.5 million dollar bonuses for everyone at the company
> Releasing an open source model that doesn't even use latent multi head attention in a open source AI world led by Chinese labs
> Constantly overhyping models as scary and dangerous to buy time to lobby against competitors and delay product launches
> Failing to match that hype as AGI is not yet here
Gotta be polite with our future overlords!
- reasoning_effort parameter supports minimal value now in addition to existing low, medium, and high
- new verbosity parameter with possible values of low, medium (default), and high
- unlike hidden thinking tokens, user-visible preamble messages for tool calls are available
- tool calls possible with plaintext instead of JSON
GPT4 gave her better response than doctors she said.
88.0 on Aider Polygot
not bad i guess
Also, when you step back and look at a few of those incremental improvements together, they're actually pretty significant.
But it's hard not to roll your eyes each time they trot out a list of meaningless benchmarks and promise that "it hallucinates even less than before" again
It feels a bit intentional
https://youtu.be/wqc85X2rpEY
Is that a good thing?
With a couple of more trillions from investors in his company, Sama can really keep launching successful, groundbreaking and innovative products like:
- Study Mode (a pre-prompt that you can craft yourself): https://openai.com/index/chatgpt-study-mode/
- Office Suite (because nothing screams AGI like an office suite: https://www.computerworld.com/article/4021949/openai-goes-fo...)
- ChatGPT5 (ChatGPT4 with tweaks) https://openai.com/gpt-5/
I can almost smell the singularity behind the corner, just a couple of trillion more! Please investors!
https://x.com/fchollet/status/1953511631054680085
[0] https://simonwillison.net/2025/Aug/7/gpt-5/
Something similar with this might happen, an underlying curse hidden inside an apparenting ground-breaking desigb.
- they are only evals
- this is mostly positioned as a general consumer product, they might have better stuff for us nerds in hand.
"Your organization must be verified to use the model `gpt-5`. Please go to: https://platform.openai.com/settings/organization/general and click on Verify Organization. If you just verified, it can take up to 15 minutes for access to propagate."
And every way I click through this I end in an infinity loop on the site...
I would say GPT-5 reads more scientific and structured, but GPT-4 more human and even useful. For the prompt:
Is uncooked meat actually unsafe to eat? How likely is someone to get food poisoning if the meat isn’t cooked?
GPT-4 makes the assumption you might want to know safe food temperatures, and GPT-5 doesn't. Really hard to say which is "better", but GPT-4 seems more useful to every day folks, but maybe GPT-5 for the scientific community?
Then interesting that on ChatGPT vibe check website "Dan's Mom" is the only one who says it's a game changer.
"This repository contains a curated collection of demo applications generated entirely in a single GPT-5 prompt, without writing any code by hand."
https://github.com/openai/gpt-5-coding-examples
This is promising!
I'd imagine this must be a big leg up on Anthropic to warrant the "GPT-5" name?
https://epoch.ai/gradient-updates/how-much-energy-does-chatg...
Edit: Scrolling down: "one second of H100-time per query, 1500 watts per H100, and a 70% factor for power utilization gets us 1050 watt-seconds of energy", which is how they get down to 0.3 = 1050/60/60.
OK, so if they run if for a full hour it's 1050*60*60 = 3.8 MW? That can't be right.
Edit Edit: Wait, no, it's just 1050 Watt Hours, right (though let's be honest, the 70% power utilization is a bit goofy - the power is still used)? So it's 3x the power to solve the same question?
It's the same as 4G vs 5G. They have a technical definition, but it's all about marketing.
"If you're claiming that em dashes are your method for detecting if text is AI generated then anyone who bothers to do a search/replace on the output will get past you."
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1) So impressed at their product focus 2) Great product launch video. Fearlessly demonstrating live. Impressive. 3) Real time humor by the presenters makes for a great "live" experience
Huge kudos to OAI. So many great features (better coding, routing, some parts of 4.5, etc) but the real strength is the product focus as opposed to the "research updates" from other labs.
Huge Kudos!!
Keep on shipping OAI!
If you email us at hn@ycombinator.com and tell us who you want to contact, we might be able to email them and ask if they would be willing to have you contact them. No guarantees though!
yikes - the poor executive leadership’s fragile egos cannot take the criticism.
The best part is, this is not even the real definition of "AGI" yet (whatever that means at this point).
More like 10% of the capability that was promised and already the flow of capital from the inflated salaries of the past decade are going to the top AI researchers.
So sorry about that.
Here's a suprprisingly enlightening (at least to me) video on how to spot LLM writing:
https://www.youtube.com/watch?v=9Ch4a6ffPZY
Undeterred by even the most dangerous and threatening of obstacles, Teemo scouts the world with boundless enthusiasm and a cheerful spirit. A yordle with an unwavering sense of morality, he takes pride in following the Bandle Scout's Code, sometimes with such eagerness that he is unaware of the broader consequences of his actions. Though some say the existence of the Scouts is questionable, one thing is for certain: Teemo's conviction is nothing to be trifled with.