How different are world models from LLMs? I'm not in the AI space but follow it here. I always assumed they belonged to the same "family" of tech and were more similar than different.
But are they sufficiently different that stalling progress in one doesn't imply stalling progress in the other?
dang · 1h ago
This is more interesting and deserves better discussion than we got from the previous title, which was derailed by the "AGI" bit, so I replaced the title with a representative sentence from the video.
(Edit: plus a question mark, as we sometimes do with contentious titles.)
rossdavidh · 7h ago
On the one hand, that isn't necessarily a problem. It can be just a useful algorithm for tool calling or whatever.
On the other hand, if you're telling your investors that AGI is about two years away, then you can only do that for a few years. Rumor has it that such claims were made? Hopefully no big investors actually believed that.
The real question to be asking is, based on current applications of LLMs, can one pay for the hardware to sustain it? The comparison to smartphones is apt; by the time we got to the "Samsung Galaxy" phase, where only incremental improvements were coming, the industry was making a profit on each phone sold. Are any of the big LLMs actually profitable yet? And if they are, do they have any way to keep the DeepSeeks of the world from taking it away?
What happens if you built your business on a service that turns out to be hugely expensive to run and not profitable?
Salgat · 6h ago
>On the other hand, if you're telling your investors that AGI is about two years away, then you can only do that for a few years.
Musk has been doing this with autonomous driving since 2015. Machine learning has enough hype surrounding it that you have to embellish to keep up with every other company's ridiculous claims.
ivan_gammel · 5h ago
I doubt this was the main driver for the investors. People were buying Tesla even without it.
Whether there is hype or not, the laws of money remain the same. If you invest and don’t get expected returns, you will be eventually concerned and will do something about it.
coolThingsFirst · 5h ago
Why are companies allowed to lie? I really can’t understand. If a person lies they lose credibility but it doesn’t apply to the rich and powerful.
bloppe · 5h ago
Lying to investors is illegal, and investors have incentive and means to sue if they think they were defrauded. The problem is proving it. I'm sure a lot of founders genuinely believe AGI is about to appear out of thin air, so they're technically not lying. Even the cynical ones who say whatever they think investors want to hear are hard to catch in a lie. It's not really about being rich and powerful. That's just the unfortunate reality of rhetoric.
orionsbelt · 4h ago
Predictions about the future and puffery are not illegal. Lying about facts are. Nobody knows how far away AGI is, everyone just has their own predictions.
xenotux · 1h ago
It's not a crime to be wrong; it's only a crime to deliberately lie. And unless there's an email saying "haha we're lying to our investors", it's just not easy to prove.
lif · 2h ago
so, without sarcasm:
how many data centers is this non-happening worth?
in other words, what justifies the huge spend?
maxhille · 7h ago
I mean there are different definitions on what to call an AGI. Most of the time people don't specify which one they use.
For me an AGI would mean truly at least human level as in "this clearly has a consciousness paired with knowledge", a.k.a. a person. In that case, what do the investors expect? Some sort of slave market of virtual people to exploit?
kbrkbr · 5h ago
Investors don't use this definition. For one because it contains something you cannot measure yet: consciousness.
How to find out if something has probably consciousness? Much less clearly? What is consciousness?
nemomarx · 6h ago
Being able to make arbitrary duplicates of slaves would be profitable, as long as the energy and compute is lower than salaries yeah
seanalltogether · 7h ago
Do we have a reasonable definition for what intelligence is? Is it like defining porn, you just know it when you see it?
AndrewDucker · 3h ago
My personal definition is "The ability to form models from observations and extrapolate from them."
LLMs are great at forming models of language from observations of language and extrapolating language constructs from them. But to get general intelligence we're going to have to let an AI build their models from direct measurements of reality.
daveguy · 1h ago
> LLMs are great at forming models of language
They really aren't even great at forming models of language. They are a single model of language. They don't build models, much less use those models. See, for example, ARC-AGI 1 and 2. They only performed ARC 1 decently [0] with additional training, and are failing miserably on ARC 2. That's not even getting to ARC 3.
> Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details. We have not yet tested the ARC-untrained model to understand how much of the performance is due to ARC-AGI data.
... Clearly not able to reason about the problems without additional training. And no indication that the additional training didn't include some feature extraction, scaffolding, RLHF, etc created by human intelligence. Impressive that fine tuning can get >85%, but it's still additional human directed training and not self contained intelligence at the level of performance reported. The blog was very generous making the undefined "fine tuning" a footnote and praising the results as if they were directly from the model that would have cost > $65,000 to run.
Edit: to be clear, I understand LLMs are a huge leap forward in AI research and possibly the first models that can provide useful results across multiple domains without being retrained. But they're still not creating their own models, even of language.
pan69 · 1h ago
> Is it like defining porn
I guess when it comes to the definition of intelligence, just like porn, different people have different levels of tolerance.
alan-crowe · 6h ago
LLMs have demonstrated that "intelligence" is a broad umbrella term that covers a variety of very different things.
Med-Gemini is clearly intelligent, but equally clearly it is an inhuman intelligence with different failure modes from human intelligence.
If we say Med-Gemini is not intelligent, we will end up having to concede that actually it is intelligent. And the danger of this concession is that we will under-estimate how different it is from human intelligence and then get caught out by inhuman failures.
erikerikson · 7h ago
One of my favorites is efficient cross domain maximization
optimalsolver · 3h ago
Efficient, cross-domain optimization.
I believe that’s Eliezer Yudkowsky’s definition.
erikerikson · 2h ago
I did initially encounter it on LessWrong and modified it slightly according to my preference. Did he coin the term? There are a lot of ideas (not inappropriately) presented without attribution in that context.
optimalsolver · 2m ago
As far as I know, it’s his own term.
mmphosis · 7h ago
mayhaps a prediction by an Artificial General Intelligence that is already here
rationalpath · 7h ago
Feels like we’re all just betting on the biggest “what if” in history.
bpodgursky · 8h ago
It is critical to remember that there is a market for people who say "AGI is not coming"
It doesn't matter whether they are lying. People want to hear it. It's comforting. So the market fills the void, and people get views and money for saying it.
Don't use the fact that people are saying it, as evidence that it is true.
TheOtherHobbes · 8h ago
You can remove the "not" and everything you wrote is just as true. If not more so.
It's not the AGI sceptics who are getting $500bn valuations.
toasterlovin · 7h ago
Right, it’s exactly the opposite. What is the AI skeptic version of MIRI, for instance?
drdeca · 6h ago
I guess the AI skeptic version of MIRI would be like, an organization that tries to anticipate possible future large problems that could arise from people anticipating an AGI that never arrives, but which people might believe has arrived, and proposes methods to attempt to prevent or mitigate those potential problems?
d4rkn0d3z · 7h ago
Can you say non-sequitor.
d4rkn0d3z · 7h ago
Oddly, in a bubble the highest valuations come just before the burst. This is obvious mathematical certainty that can be read by anyone viewing an exponential growth curve.
kbrkbr · 5h ago
> obvious mathematical certainty
You mean like euclidean geometry?
d4rkn0d3z · 1h ago
I mean that as valuations rise before a bubble bursts, the curve provides that successive values grow, sometimes at an increasing rate. The greatest values, and change in values comes just before the bubble bursts. The point being that high valuations and increasing valuations are not very capable of distinguishing bubble/non-bubble. In fact, tulips were most valuable, and those values were climbing at the highest rate before the tulip bubble burst.
kbrkbr · 1h ago
Look, I asked
>> obvious mathematical certainty
> You mean like euclidean geometry
To which you reply stuff about values and bubble bursts.
What you said may or may not be true. But it's hard for me to tell how it is related to what I asked.
d4rkn0d3z · 37m ago
I said that high valuation or valuations rising at an increasing rate is common to bubbles. This clearly refers back to the comment about the current high and rising valuations for AGI prospects.
gls2ro · 6h ago
Usually the burden of proof is on the one who is making a positive claim like: AGI is here or even AGI is coming.
The default position that does not need any more justification is the one that is skeptic or even agnostic to the claim that is made until proof is shown.
So when talking about evidence as a way to prove a claim: AGI is coming is the team that needs to provide this evidence. Someone saying AGI is not coming can add as many arguments or opinions as they like but it does not usually invite to such a high scrutiny as saying they need to provide evidence.
lostmsu · 6h ago
Using the very basic definition of AGI where "general" is just cross-domain, as in e.g. chemistry and law, the very first ChatGPT was already it. Not very smart one though.
"Modern" definitions that include non-intelligence related stuff like agency sound like goalpost moving, so it's unclear why would you want them.
ivan_gammel · 5h ago
Depends on definition of “cross-domain”. Can any of the current models be plugged in in an emulator of a human with equivalent senses (vision, hearing etc) and process those inputs in real time with the same speed of reaction, i.e. emulate human or animal intelligence in interactions with environment? That would be truly cross-domain.
lostmsu · 4h ago
I defined cross-domain with an example. ChatGPT is not trained to practice chemistry and law, yet it can do both. It is cross-domain.
You can make it stronger at being cross domain, but it satisfies the minimum requirement.
RugnirViking · 46m ago
It is trained to practice chemistry and law. The reason it can do those because it's trained on an appreciable portion of all human output on both or those fields. If that's not training on them I don't know what is.
lostmsu · 40m ago
> It is trained to practice chemistry and law
No, it is not. It is trained to predict next token, and it is trained to follow user instructions.
ivan_gammel · 3h ago
It cannot. It doesn’t reason. Gambling and winning (1-10^N)*100% times is not the same as reasoning and providing accurate answers the same amount of times. If you reason about something, your errors fall into certain categories of fallacies often related to incomplete information. LLM hallucinations are easy to spot with reasoning, they are of statistical nature.
lostmsu · 1h ago
> (1-10^N)*100% times
good_stuffs · 7h ago
Nobody even knows what AGI even is. This will most likely be defined by a corporation, not science. Due to obvious incentives.
asimpletune · 5h ago
AGI is being able to learn from first principles, not being trained on trillions of examples. If you can start with priors and perform a demonstration that is not already a prior then you are intelligent. It’s the difference between the result and understanding the process that produces the result.
kbrkbr · 5h ago
Can you elaborate on the process by which you created this definition?
asimpletune · 4h ago
I just applied some stuff that’s been known for a long time in a different context. But let me give you a scenario to think about as a demonstration of how I mean.
Imagine we trained an AI on everything ever written, but the catch is we’ve restricted the training data to the year, let’s say, 400 BCE and earlier (Ignore the fact that most of what was written then is lost to us now and just pretend that’s not issue for our thought experiment) The AI is also programmed to seek new knowledge based off that starting knowledge.
Also pretend that this AI has an oracle it could talk to that would help the AI simulate experiments. So the AI could ask questions and get answers but only in a way that builds ever so slightly off what it already knows.
Making any progress at all in this experiment and discovering new knowledge is what we’re after and “new knowledge” would be defined as some r that’s demonstrated using some p and q as propositions, where r is neither p or q, and r is also correct in terms of 2025 knowledge.
If the AI, with the aid of the knowledge it started with and the help of the oracle to let it ask questions about the world and build off that knowledge, can ever arrive, or exceed, 2025 knowledge then it’s at least generally intelligent and equal to a human. Although the bar could maybe be even less.
It loses, however, if it never advances, gets stuck in a loop, or in some other sense can’t make progress.
This is intelligence: to proceed from things everyone agrees on and ask questions and formulate assertions that depend on propositions holding true, and in the process demonstrate new things that were not already part of common belief.
I don’t know how this experiment could be done in real life with an LLM for example but this is a story version of what I mean in my original comment.
kbrkbr · 1h ago
> I just applied some stuff that’s been known for a long time in a different context.
I tried this, and screamed "Goal!!!!" on a golf course when the ball went in the hole. Did not work as expected. Lost my membership.
But maybe I applied it wrong.
nkrisc · 6h ago
Faster than light travel is not coming.
Given that AGI does not exist, “AGI is not coming” is the status quo until someone disproves it.
righthand · 8h ago
Waiting for Agi-dot…
The inverse can be true too: Just because people ARE saying that Agi is coming, isn’t evidence that it is true.
bpodgursky · 8h ago
OK, but your null hypothesis should always be a first or second degree linear projection.
"AI is getting better rapidly" is the current state of affairs. Arguing "AI is about to stop getting better" is the argument that requires strong evidence.
righthand · 7h ago
“AI is getting better rapidly” is a false premise. As AI is a large domain. There is no way to quanitify the better as compared to the entire domain. “Llms are improving rapidly during a short period of time where they gain popularity” is more accurate.
Llms getting better != a path to AGI.
metalman · 6h ago
the same is true of solar eclipses, there are no partial eclipses, untill the very last instant of the moon covering the sun, it is far to bright to look at, and then the stars come out and the solar flares are visible, the birds sing there evening songs
and here I have told you of it, but at best it will be hint.
AI is worse, much worse, as we have our own inteligence, but cant even offer a hint of where that line is and how to cross it, where to go to see it
backpackviolet · 7h ago
> "AI is getting better rapidly"
… is it? I hear people saying that. I see “improvement”: the art generally has the right number of fingers more often, the text looks like text, the code agents don’t write stuff that even the linter says is wrong.
But I still see the wrong number of fingers sometimes. I still see the chat bots count the wrong number of letters in a word. I still see agents invent libraries that don’t exist.
I don’t know what “rapid” is supposed to mean here. It feels like Achilles and the Tortoise and also has the energy costs of a nation-state.
righthand · 7h ago
Agreed there really isn’t any metrics that indicate this is true. Considering many models are still too complex to run locally. Llms are getting better for the corporations that sell access to them. Not necessarily for the people that use them.
camillomiller · 7h ago
Compare Altman outlandish claims about GPT-5 and the reality of this update. Do you think they square out in any reasonable way?
bpodgursky · 7h ago
Please, please seriously think back to your 2020 self, and think about whether your 2020 self would be surprised by what AI can do today.
You've frog-boiled yourself into timelines where "No WORLD SHAKING AI launches in the past 4 months" means "AI is frozen". In 4 months, you will be shocked if AI doesn't have a major improvement every 2 months. In 6 months, you will be shocked if it doesn't have a major update ever 1 month.
It's hard to see exponential curves while you're on it, I'm not trying to fault you here. But it's really important to stretch yourself to try.
righthand · 7h ago
What if I’ve not been impressed by giving a bunch of people a spam bot tuned to education materials? Am I frog boiled? Who cares about the actual advancement of this singular component if I was never impressed.
You assume everyone is “impressed”.
backpackviolet · 7h ago
I’m still surprised by what AI can do. It’s amazing. … but I still have to double check when it’s important that I get the right answer, I still have to review the code it writes, and I still am not sure there is actually enough business to cover what it will actually cost to run when it needs to pay for itself.
jononor · 6h ago
I for one am quite surprised. Sometimes impressed. But also often frustrated. And occasionally disappointed. Sometimes worried about the negative follow-on effects. Working with current LLMs spans the whole gamut...
But for coding we are at the point where even the current level is quite useful. And as the tools/systems get better, the usefilness is going to increase quite a bit. Even if models improve slowly from this point on. It will impact the whole industry over the next years, and since software is eating the world, will impact many other industries as well.
Exponential? Perhaps in the same way as computers and Internet have been exponential - cost per X (say tokens) will probably go down exponentially the next years and decades, the same way cost per FLOP went down, on megabytes transferred. But those exponential gains did not results in exponential growth in productivity, or if so, the exponent is much much lower. And I suspect it will likely be the same for artificial intelligence.
th0ma5 · 7h ago
To be honest, I had the right idea back then... This technology has fundamental qualities that require it to provide inaccurate token predictions that are only statistically probable. They aren't even trying to change this situation other than trying to find more data to train, saying you have to keep adding layers of them, or are saying it is the user's responsibility.
There's been the obvious notion that digitizing the world's information is not enough and that hasn't changed.
SalmoShalazar · 8h ago
One could flip your post to say “AGI is coming” and be claiming the opposite, and it would be equally lacking insight. This is not “critical” to remember.
There are interesting and well thought out arguments for why the AGI is not coming with the current state of technology, dismissing those arguments as propaganda/clickbait is not warranted. Yannic is also an AI professional and expert, not one to be offhandedly dismissed because you don’t like the messaging.
TheCraiggers · 7h ago
I doing think that's fair to the person you replied to. At no time did they say they didn't like/dislike the message. Merely that there's a market for it, and thus, people may be biased.
Telling us all to remember that there's potential for bias isn't so bad. It's a hot button issue.
politelemon · 7h ago
What products are people building on not-AGI?
camillomiller · 8h ago
By this measure, considering the current capex all over the board, there is a lot more incentive in pushing the “AGI IS NEAR AND WE AINT READY” narrative than the opposite.
If AGI won’t come, as it’s highly probable, these companies are bust for billions and billions…
d4rkn0d3z · 7h ago
To share my experience, 25 years ago I looked into AI and had inclinations to see what scaling compute would do. It took no time to find advisors who told me the whole program I had in mind could not gain ethics approval and was mathematically limited. The former road block is now lifted due to the fact that nobody cares about ethics any more, the latter seems to be the remaining hurdle.
vlan121 · 7h ago
The goal of economic is not to reach AGI. It would solve the problems we have with the current market, therefore would it make less money, then to just "chase" for the AGI. Shirky principle in a nutshell.
Maybe for LLMs but they are not the only possible algorithm. Only this week we had Genie 3 as in:
>The Surprising Leap in AI: How Genie 3’s World Model Redefines Synthetic Reality https://www.msn.com/en-us/news/technology/the-surprising-lea...
and:
>DeepMind thinks its new Genie 3 world model presents a stepping stone toward AGI https://techcrunch.com/2025/08/05/deepmind-thinks-genie-3-wo...
But are they sufficiently different that stalling progress in one doesn't imply stalling progress in the other?
(Edit: plus a question mark, as we sometimes do with contentious titles.)
On the other hand, if you're telling your investors that AGI is about two years away, then you can only do that for a few years. Rumor has it that such claims were made? Hopefully no big investors actually believed that.
The real question to be asking is, based on current applications of LLMs, can one pay for the hardware to sustain it? The comparison to smartphones is apt; by the time we got to the "Samsung Galaxy" phase, where only incremental improvements were coming, the industry was making a profit on each phone sold. Are any of the big LLMs actually profitable yet? And if they are, do they have any way to keep the DeepSeeks of the world from taking it away?
What happens if you built your business on a service that turns out to be hugely expensive to run and not profitable?
Musk has been doing this with autonomous driving since 2015. Machine learning has enough hype surrounding it that you have to embellish to keep up with every other company's ridiculous claims.
Whether there is hype or not, the laws of money remain the same. If you invest and don’t get expected returns, you will be eventually concerned and will do something about it.
For me an AGI would mean truly at least human level as in "this clearly has a consciousness paired with knowledge", a.k.a. a person. In that case, what do the investors expect? Some sort of slave market of virtual people to exploit?
How to find out if something has probably consciousness? Much less clearly? What is consciousness?
LLMs are great at forming models of language from observations of language and extrapolating language constructs from them. But to get general intelligence we're going to have to let an AI build their models from direct measurements of reality.
They really aren't even great at forming models of language. They are a single model of language. They don't build models, much less use those models. See, for example, ARC-AGI 1 and 2. They only performed ARC 1 decently [0] with additional training, and are failing miserably on ARC 2. That's not even getting to ARC 3.
[0] https://arcprize.org/blog/oai-o3-pub-breakthrough
> Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details. We have not yet tested the ARC-untrained model to understand how much of the performance is due to ARC-AGI data.
... Clearly not able to reason about the problems without additional training. And no indication that the additional training didn't include some feature extraction, scaffolding, RLHF, etc created by human intelligence. Impressive that fine tuning can get >85%, but it's still additional human directed training and not self contained intelligence at the level of performance reported. The blog was very generous making the undefined "fine tuning" a footnote and praising the results as if they were directly from the model that would have cost > $65,000 to run.
Edit: to be clear, I understand LLMs are a huge leap forward in AI research and possibly the first models that can provide useful results across multiple domains without being retrained. But they're still not creating their own models, even of language.
I guess when it comes to the definition of intelligence, just like porn, different people have different levels of tolerance.
Think about this story https://news.ycombinator.com/item?id=44845442
Med-Gemini is clearly intelligent, but equally clearly it is an inhuman intelligence with different failure modes from human intelligence.
If we say Med-Gemini is not intelligent, we will end up having to concede that actually it is intelligent. And the danger of this concession is that we will under-estimate how different it is from human intelligence and then get caught out by inhuman failures.
I believe that’s Eliezer Yudkowsky’s definition.
It doesn't matter whether they are lying. People want to hear it. It's comforting. So the market fills the void, and people get views and money for saying it.
Don't use the fact that people are saying it, as evidence that it is true.
It's not the AGI sceptics who are getting $500bn valuations.
You mean like euclidean geometry?
>> obvious mathematical certainty
> You mean like euclidean geometry
To which you reply stuff about values and bubble bursts.
What you said may or may not be true. But it's hard for me to tell how it is related to what I asked.
The default position that does not need any more justification is the one that is skeptic or even agnostic to the claim that is made until proof is shown.
So when talking about evidence as a way to prove a claim: AGI is coming is the team that needs to provide this evidence. Someone saying AGI is not coming can add as many arguments or opinions as they like but it does not usually invite to such a high scrutiny as saying they need to provide evidence.
"Modern" definitions that include non-intelligence related stuff like agency sound like goalpost moving, so it's unclear why would you want them.
You can make it stronger at being cross domain, but it satisfies the minimum requirement.
No, it is not. It is trained to predict next token, and it is trained to follow user instructions.
Imagine we trained an AI on everything ever written, but the catch is we’ve restricted the training data to the year, let’s say, 400 BCE and earlier (Ignore the fact that most of what was written then is lost to us now and just pretend that’s not issue for our thought experiment) The AI is also programmed to seek new knowledge based off that starting knowledge.
Also pretend that this AI has an oracle it could talk to that would help the AI simulate experiments. So the AI could ask questions and get answers but only in a way that builds ever so slightly off what it already knows.
Making any progress at all in this experiment and discovering new knowledge is what we’re after and “new knowledge” would be defined as some r that’s demonstrated using some p and q as propositions, where r is neither p or q, and r is also correct in terms of 2025 knowledge.
If the AI, with the aid of the knowledge it started with and the help of the oracle to let it ask questions about the world and build off that knowledge, can ever arrive, or exceed, 2025 knowledge then it’s at least generally intelligent and equal to a human. Although the bar could maybe be even less.
It loses, however, if it never advances, gets stuck in a loop, or in some other sense can’t make progress.
This is intelligence: to proceed from things everyone agrees on and ask questions and formulate assertions that depend on propositions holding true, and in the process demonstrate new things that were not already part of common belief.
I don’t know how this experiment could be done in real life with an LLM for example but this is a story version of what I mean in my original comment.
I tried this, and screamed "Goal!!!!" on a golf course when the ball went in the hole. Did not work as expected. Lost my membership.
But maybe I applied it wrong.
Given that AGI does not exist, “AGI is not coming” is the status quo until someone disproves it.
The inverse can be true too: Just because people ARE saying that Agi is coming, isn’t evidence that it is true.
"AI is getting better rapidly" is the current state of affairs. Arguing "AI is about to stop getting better" is the argument that requires strong evidence.
Llms getting better != a path to AGI.
… is it? I hear people saying that. I see “improvement”: the art generally has the right number of fingers more often, the text looks like text, the code agents don’t write stuff that even the linter says is wrong.
But I still see the wrong number of fingers sometimes. I still see the chat bots count the wrong number of letters in a word. I still see agents invent libraries that don’t exist.
I don’t know what “rapid” is supposed to mean here. It feels like Achilles and the Tortoise and also has the energy costs of a nation-state.
You've frog-boiled yourself into timelines where "No WORLD SHAKING AI launches in the past 4 months" means "AI is frozen". In 4 months, you will be shocked if AI doesn't have a major improvement every 2 months. In 6 months, you will be shocked if it doesn't have a major update ever 1 month.
It's hard to see exponential curves while you're on it, I'm not trying to fault you here. But it's really important to stretch yourself to try.
You assume everyone is “impressed”.
There's been the obvious notion that digitizing the world's information is not enough and that hasn't changed.
There are interesting and well thought out arguments for why the AGI is not coming with the current state of technology, dismissing those arguments as propaganda/clickbait is not warranted. Yannic is also an AI professional and expert, not one to be offhandedly dismissed because you don’t like the messaging.
Telling us all to remember that there's potential for bias isn't so bad. It's a hot button issue.