OpenAI prepares to launch GPT-5 in August

That was my thought, except the author even mentioned they couldn’t even get a comment from OpenAI for their “article”. Can’t beat free advertising.

Probably because OpenAI is the best at this than any other player in the game. They’re on their way to replacing Google as the #1 search engine. Instead of “google it” it’s going to be “gpt it”, and we all know who “gpt” is.

When I had some mild success with my first startup in the UK, I got flooded by news organisations offering "premium publication content" --- basically pay us a big chunk of cash to write a positive article on your company.

I was surprised at the number and calibre of orgs that came to me who would basically say anything I wanted for cash, this opened my eyes a lot and made me very suspicious of published media.

the media outlets respond to our clicks, and we click on gpt5 stories. monkey brain go brr.

For OpenAI at least, it's obvious. They are considered the industry leader at this point and are the most widely used LLM that folks are aware of (arguably, Google's 'in search' summarization is the most widely used).

People get excited on an update in such a rapidly changing space. It really is that simple.

the real hero - thanks

They already are. I have been using Kimi k2. It is 90% as good as Sonnet and on Groq 3x faster and 1/5th the price.

>If it were any good I would assume there would be no need to hype it up.

If it were good, there would also be no need for their devs to tell people to temper their expectations, alas... [0]

[0] https://xcancel.com/alexwei_/status/1946477756738629827#m

"My theory is that LLMs will get commoditized within the next year."

Incredibly bad theory, it's like you're saying every LLM is the same because they can all talk, even though the newer ones continue to smash through benchmarks the older ones couldn't. And now it happens quarterly instead of yearly, so you can't even say it's slowing down.

I don't think so, look at how Sora changed every... Well Operator was a game changer for.. Hmm, but what about gpt-4.5 or PhD level o3... o3-pro...? I mean, the 10k/mon agents are definitely coming... any day now...

Anyway, I'm sure gpt-5 will be AGI.

At the moment most of the dollars are coming from consumer, inclusive of business, subscriptions. That’s where the valuations are getting pegged and most API dollars are probably seen as experimental. The model quality matters but product experience is what is driving revenue. In that sense OpenAI is doing quite well.

Which year did Linux become the dominant desktop OS?

> If it were any good I would assume there would be no need to hype it up.

Yes, this is why apple famously just dumped the original iphone on the market without telling anybody about it ahead of time.

The fact that xAI only exists for Elon Musk's personal spite and they produced a top performing model certainly implies that model training isn't any kind of moat. It's certainly very expensive but not mysterious.

I doubt it will have. OpenAI planned to release GPT-5 in 2024 or early 2025, it underwhelmed, and anonymous OpenAI sources have claimed that the later GPT-4.5 was actually GPT-5 relabelled to set expectations. It was seen as roughly a 20% improvement over GPT-4o. This is when it sunk in for OpenAI that they were at the end of the road for non-reasoning models. Scaling issues made them too costly.

Turning to their reasoning models, it’s also known and documented through SimpleQA and PersonQA that OpenAI o3 hallucinates more than o1, and o4-mini even more than o3. There’s an unmanaged issue where training on synthetic data improves benchmark results on STEM tasks but increases hallucination rates, especially troubling OpenAI models for some reason (my guess: they’re fine-tuned to take risks since it’s known to also increase likelihood of getting it right for hard tasks?)

Google has long known OpenAI struggles with hallucinations more than them according to an anonymous Googler that I saw commented on this. This has been verified by the aforementioned benchmarks. Anthropic also struggles less. But as far as I can tell, they’re all facing issues with synthetic data acting like a double edged sword.

So GPT-5 is going to be interesting. How well it exactly does will bear a lot of meaning for the kind of trouble OpenAI is in right now. Maybe OpenAI has found a novel approach in reducing hallucinations? I think that’s among their most crucial points right now. But other than this, no, I don’t expect a revolution, only an evolution. They might currently win benchmarks, but it will hardly be something that catapults them.

If GPT-5 underwhelms, it will bear a stronger signal than merely the one that GPT-5 underwhelms. Because then OpenAI has trouble with both non-reasoning and reasoning models, and we’re likely to be looking at the end of the road on the horizon for current GPT based LLM’s and one where the winner will probably ultimately be cheaper open weight models once they catch up.

This is the smart take. The version numbers were useful going from GPT-3 to GPT-3.5 and then GPT-4, but after that OpenAI butchered the usefulness of the naming scheme, with stuff like o4 and 4-o. Version numbers now tell you almost nothing about the change.

This happened because training progressively larger models used to be the main path forward, which was easy to track and name, but currently it's all about quickly incorporating synthetic data chain-of-thoughts created by flash models.

Meh. The models are already quite useful. If the improvement is half of what the jump to GPT-4 was, it will be a big deal.

I will die on this hill.

Nothing annoys me more than OpenAI acting like something is rolling out (or rolled out already) and then taking forever to do so.

> ChatGPT agent starts rolling out today to Pro, Plus, and Team; Pro will get access by the end of day, while Plus and Team users will get access over the next few days.

"Next few days" - It's 8 days later (so far). Lest one think "It's only 8 days, geez, calm down": They do this _all the time_. I don't even remember the length of the gap between announcing the enhanced voices and then forgetting about it completely before it finally rolled out.

It sours every announcement they make in my opinion.

For what it's worth, I had Agent Mode deployed to my account earlier this morning.

Pay close attention to these demos. Often the AI is ok but not amazing, but because it’s shaped like the right thing they don’t look any deeper.

It makes selling improvements fairly hard actually. If the last model already wrote an amazing poem about hot dogs, the English language doesn’t have superlatives to handle what the next model creates.

This statement is definitely just marketing hype, but if we're being pedantic there are tons of questions that are hard to answer but have easy to verify solutions, e.g. all NP-complete problems.

>If he didn't understand the question how could he know the model answered it perfectly?

Also, 'thing that I don't know about but is broadly and uncontroversially known and documented by others' is sort of dead center of the value proposition for current-generation LLMs and also doesn't make very impressive marketing copy.

Unless he's saying that he fed it an unknown-to-experts-in-the-field question and it figured it out in which case I am very skeptical.

There's plenty of things to roast Altman about, but this isn't really one of them. A specialized problem might not be understood by someone unversed in that field even if the solution is simple and knowable. "What is the Euler characteristic of a torus?" for a rudimentary off-the-cuff example. Altman could easily know or check the answer ("0") without ever understanding the meaning of the question.

It takes a really special kind of self-delusion to recognize that you don't understand the question and also think you are qualified to evaluate the answer.

Maybe, after thinking for a really long time, GPT-5 said "42". The answer might have been so shocking to Altman that now he'll have to build GPT-6.

But more seriously - it's a ridiculous statement to think you understand the answer when you don't understand the question in the first place..

World class grifter grifting hard

I use Gemini at work, and ChatGPT for everything else 'personal'. Also from my non-tech friends, I usually hear them talk about ChatGPT and not Gemini or other models. I think, even if Gemini outperforms ChatGPT, there's definitely a strong 'first mover advantage' at play. I suspect that being outperformed by Gemini etc won't diminish their market share significantly.

I am still skeptical about the value of LLM as coding helper in 2025. I have not dedicated myself to an "AI first" workflow so maybe I am just doing it wrong.

The most positive metaphor I have heard about why LLM coding assistance is so great is that it's like having a hard-working junior dev that does whatever you want and doesn't waste time reading HN. You still have to check the work, there will be some bad decisions in there, the code maybe isn't that great, but you can tell it to generate tests so you know it is functional.

OK, let's say I accept that 100% (I personally haven't seen evidence that LLM assistance is really even up to that level, but for the sake of argument). My experience as a senior dev is that adding juniors to a team slows down progress and makes the outcome worse. You only do it because that's how you train and mentor juniors to be able to work independently. You are investing in the team every time you review a junior's code, give them advice, answer their questions about what is going on.

With an LLM coding assistant, all the instruction and review you give it is just wasted effort. It makes you slower overall and you spend a lot of time explaining code and managing/directing something that not only doesn't care but doesn't even have the ability to remember what you said for the next project. And the code you get out, in my experience at least, is pretty crap.

I get that it's a different and, to some, interesting way of programming-by-specification, but as far as I can tell the hype about how much faster and better you can code with an AI sidekick is just that -- hype. Maybe that will be wrong next year, maybe it's wrong now with state-of-the-art tools, but I still can't help thinking that the fundamental problem, that all the effort you spend on "mentoring" an LLM is just flushed down the toilet, means that your long term team health will suffer.'

>programming needs to be redesigned from the ground up as LLM first.

Yes, because non-deterministic systems are great softwares. I mean, who want's repeatable execution on the control program for their nuclear submarine or their hospital lighting controls. Why would anyone want a computer capable of actual math running on the President's nuclear "football" when we can have the outputs of hallucinating tools running there.