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There are no new ideas in AI, only new datasets

blog.jxmo.io

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Re: There are no new ideas in AI, only new datasets

#101

Post by smokel »

t55 wrote: post #61
EternalFury wrote: post #30

What John Carmack is exploring is pretty revealing. Train models to play 2D video games to a superhuman level, then ask them to play a level they have not seen before or another 2D video game they have not seen before. The transfer function is negative. So, in my definition, no intelligence has been developed, only expertise in a narrow set of tasks. It’s apparently much easier to scare the masses with visions of ASI…

this is what deepmind did 10 years ago lol

No, they (and many others before them) are genuinely trying to improve on the original research.

The original paper "Playing Atari with Deep Reinforcement Learning" (2013) from Deepmind describes how agents can play Atari games, but these agents would have to be specifically trained on every individual game using millions of frames. To accomplish this, simulators were run in parallel, and much faster than in real-time.

Also, additional trickery was added to extract a reward signal from the games, and there is some minor cheating on supplying inputs.

What Carmack (and others before him) is interested in, is trying to learn in a real-life setting, similar to how humans learn.

Re: There are no new ideas in AI, only new datasets

#102

Post by keerthiko »

vladimirralev wrote: post #48
EternalFury wrote: post #30

What John Carmack is exploring is pretty revealing. Train models to play 2D video games to a superhuman level, then ask them to play a level they have not seen before or another 2D video game they have not seen before. The transfer function is negative. So, in my definition, no intelligence has been developed, only expertise in a narrow set of tasks. It’s apparently much easier to scare the masses with visions of ASI…

He is not using appropriate models for this conclusion and neither is he using state of the art models in this research and moreover he doesn't have an expensive foundational model to build upon for 2d games. It's just a fun project. A serious attempt at video/vision would involve some probabilistic latent space that can be noised in ways that make sense for games in general. I think veo3 proves that ai can generaliz…

> generating a video under prompt constraints is basically playing a game

Besides static puzzles (like a maze or jigsaw) I don't believe this analogy holds? A model working with prompt constraints that aren't evolving or being added over the course of "navigating" the generation of the model's output means it needs to process 0 new information that it didn't come up with itself — playing a game is different from other generation because it's primarily about reacting to input you didn't know the precise timing/spatial details of, but can learn that they come within a known set of higher order rules. Obviously the more finite/deterministic/predictably probabilistic the video game's solution space, the more it can be inferred from the initial state, aka reduce to the same type of problem as generating a video from a prompt), which is why models are still able to play video games. But as GP pointed out, transfer function negative in such cases — the overarching rules are not predictable enough across disparate genres.

> I think you could prompt veo3 to play any game for a few seconds

I'm curious what your threshold for what constitutes "play any game" is in this claim? If I wrote a script that maps button combinations to average pixel color of a portion of the screen buffer, by what metric(s) would veo3 be "playing" the game more or better than that script "for a few seconds"?

edit: removing knee-jerk reaction language

Re: There are no new ideas in AI, only new datasets

#103

Post by nomel »

Swizec wrote: post #85
nomel wrote: post #74

Earlier quoted context omitted.

There are many people who mentally developed while paralyzed that literally drive around their bodies via motorized wheelchair. I don't think there's any evidence that a brain couldn't exist or develop in a jar, given only the inputs modern AI now has (text, video, audio).

> any evidence that a brain couldn't exist or develop in a jar The brain could . Of course it could. It's just a signals processing machine. But would it be missing anything we consider core to the way humans think? Would it struggle with parts of cognition? For example: experiments were done with cats growing up in environments with vertical lines only. They were then put in a normal room and had a hard time underst…

This isn't remotely a hypothetical, so I imagine there are some examples out there, especially from back when polio was a problem. Although, for practical reasons, they might have had limited exposure to novelty, which could have negative consequences.

Re: There are no new ideas in AI, only new datasets

#104

Post by EternalFury »

fsmv wrote: post #45
NBJack wrote: post #40

Earlier quoted context omitted.

In other words, they learn the game, not how to play games .

They memorize the answers not the process to arrive at answers

They learn the value of specific actions in specific contexts based on the rewards they received during their play time. Specific actions and specific contexts are not transferable for various reasons. John quoted that varying frame rates and variable latency between action and effect really confuse the models.

Re: There are no new ideas in AI, only new datasets

#105

Post by MichaelZuo »

pdabbadabba wrote: post #82
0xWTF wrote: post #65

Earlier quoted context omitted.

> You can trivially prove this yourself. Given the long list of dead philosophers of mind, if you have a trivial proof, would you mind providing a link?

It’s really easy: go to Claude and ask it a novel question. It will generally reason its way to a perfectly good answer even if there is no direct example of it in the training data.

How do you know it’s a novel question?

Re: There are no new ideas in AI, only new datasets

#106

Post by altairprime »

vladimirralev wrote: post #48
EternalFury wrote: post #30

What John Carmack is exploring is pretty revealing. Train models to play 2D video games to a superhuman level, then ask them to play a level they have not seen before or another 2D video game they have not seen before. The transfer function is negative. So, in my definition, no intelligence has been developed, only expertise in a narrow set of tasks. It’s apparently much easier to scare the masses with visions of ASI…

He is not using appropriate models for this conclusion and neither is he using state of the art models in this research and moreover he doesn't have an expensive foundational model to build upon for 2d games. It's just a fun project. A serious attempt at video/vision would involve some probabilistic latent space that can be noised in ways that make sense for games in general. I think veo3 proves that ai can generaliz…

Is any model currently known to succeed in the scenario that Carmack’s inappropriate model failed?

Re: There are no new ideas in AI, only new datasets

#107

Post by 317070 »

vladimirralev wrote: post #48
EternalFury wrote: post #30

What John Carmack is exploring is pretty revealing. Train models to play 2D video games to a superhuman level, then ask them to play a level they have not seen before or another 2D video game they have not seen before. The transfer function is negative. So, in my definition, no intelligence has been developed, only expertise in a narrow set of tasks. It’s apparently much easier to scare the masses with visions of ASI…

He is not using appropriate models for this conclusion and neither is he using state of the art models in this research and moreover he doesn't have an expensive foundational model to build upon for 2d games. It's just a fun project. A serious attempt at video/vision would involve some probabilistic latent space that can be noised in ways that make sense for games in general. I think veo3 proves that ai can generaliz…

What you're thinking of is much more like the Genie model from DeepMind [0]. That one is like Veo, but interactive (but not publically available)

[0] https://deepmind.google/discover/blog/genie-2-a-large-scale-...

Re: There are no new ideas in AI, only new datasets

#108

Post by keerthiko »

pdabbadabba wrote: post #82
0xWTF wrote: post #65

Earlier quoted context omitted.

> You can trivially prove this yourself. Given the long list of dead philosophers of mind, if you have a trivial proof, would you mind providing a link?

It’s really easy: go to Claude and ask it a novel question. It will generally reason its way to a perfectly good answer even if there is no direct example of it in the training data.

When LLM's come up with answers to questions that aren't directly exampled in the training data, that's not proof at all that it reasoned its way there — it can very much still be pattern matching without insight from the actual code execution of the answer generation.

If we were taking a walk and you asked me for an explanation for a mathematical concept I have not actually studied, I am fully capable of hazarding a casual guess based on the other topics I have studied within seconds. This is the default approach of an LLM, except with much greater breadth and recall of studied topics than I, as a human, have.

This would be very different than if we sat down at a library and I applied the various concepts and theorems I already knew to make inferences, built upon them, and then derived an understanding based on reasoning of the steps I took (often after backtracking from several reasoning dead ends) before providing the explanation.

If you ask an LLM to explain their reasoning, it's unclear whether it just guessed the explanation and reasoning too, or if that was actually the set of steps it took to get to the first answer they gave you. This is why LLMs are able to correct themselves after claiming strawberry has 2 rs, but when providing (guessing again) their explanations they make more "relevant" guesses.

Re: There are no new ideas in AI, only new datasets

#109

Post by hluska »

EternalFury wrote: post #30

What John Carmack is exploring is pretty revealing. Train models to play 2D video games to a superhuman level, then ask them to play a level they have not seen before or another 2D video game they have not seen before. The transfer function is negative. So, in my definition, no intelligence has been developed, only expertise in a narrow set of tasks. It’s apparently much easier to scare the masses with visions of ASI…

When I finished my degree, the idea that a software system could develop that level of expertise was relegated to science fiction. It is an unbelievable human accomplishment to get to that point and honestly, a bit of awe makes life more pleasant.

Less quality of life focused, I don’t believe that the models he uses for this research are capable of more. Is it really that revealing?

Re: There are no new ideas in AI, only new datasets

#110

Post by IshKebab »

0xWTF wrote: post #65
IshKebab wrote: post #53

Earlier quoted context omitted.

This has been disproven so many times... They clearly do both. You can trivially prove this yourself.

> You can trivially prove this yourself. Given the long list of dead philosophers of mind, if you have a trivial proof, would you mind providing a link?

Just go and ask ChatGPT or Claude something that can't possibly be in its training set. Make something up. If it is only memorising answers then it will be impossible for it to get the correct result.

A simple nonsense programming task would suffice. For example "write a Python function to erase every character from a string unless either of its adjacent characters are also adjacent to it in the alphabet. The string only contains lowercase a-z"

That task isn't anywhere in its training set so they can't memorise the answer. But I bet ChatGPT and Claude can still do it.

Honestly this is sooooo obvious to anyone that has used these tools, it's really insane that people are still parroting (heh) the "it just memorises" line.

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