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John Carmack talk at Upper Bound 2025

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Re: John Carmack talk at Upper Bound 2025

#231

Post by handsclean »

epr wrote: post #107
qoez wrote: post #76

Interesting reply from an openai insider: https://x.com/unixpickle/status/1925795730150527191

Actually no, it's not interesting at all. Vague dismissal of an outsider is a pretty standard response by insecure academic types. It could have been interesting and/or helpful to the conversation if they went into specifics or explained anything at all. Since none of that's provided, it's "OpenAI insider" vs John Carmack AND Richard Sutton. I know who I would bet on.

It seems that you’ve only read the first part of the message. X sometimes aggressively truncates content with no indication it’s done so. I’m not sure this is complete, but I’ve recovered this much:

> I read through these slides and felt like I was transported back to 2018.

> Having been in this spot years ago, thinking about what John & team are thinking about, I can't help but feel like they will learn the same lesson I did the hard way.

> The lesson: on a fundamental level, solutions to these games are low-dimensional. No matter how hard you hit them with from-scratch training, tiny models will work about as well as big ones. Why? Because there's just not that many bits to learn.

> If there's not that many bits to learn, then researcher input becomes non-negligible.

> "I found a trick that makes score go up!" -- yeah, you just hard-coded 100+ bits of information; a winning solution is probably only like 1000 bits. You see progress, but it's not the AI's.

> In this simplified RL setting, you don't see anything close to general intelligence. The neural networks aren't even that important.

> You won't see _real_ learning until you absorb a ton of bits into the model. The only way I really know to do this is with generative modeling.

> A classic example: why is frame stacking just as good as RNNs? John mentioned this in his slides. Shouldn't a better, more general architecture work better?

> YES, it should! But it doesn't, because these environments don't heavily encourage real intelligence.

Re: John Carmack talk at Upper Bound 2025

#232

Post by lostmsu »

lostmsu wrote: post #230

I'm with OpenAI folks on this one: Atari just won't cut it for AGI. My layman intuition is that RL works well when rewards give good signal all the time. Until it does RL is basically random search. That's where massive data diversity like we have in text comes in handy. In a game there might be a level with a door and a key, and because there's no reward for getting the key closer to the door, bridging this gap requ…

You can actually easily test and overcome this by training a model simultaneously on a massive of text and Atari while carefully balancing learning rates between the two.

Re: John Carmack talk at Upper Bound 2025

#233

Post by Jensson »

Nopoint2 wrote: post #229
Jensson wrote: post #216

Earlier quoted context omitted.

> There is just no reason to believe that we are born with some insanely big library of knowledge, and it sounds completely impossible. How would it be stored, and how would we even evolve it? We do have that, ever felt fear of heights? That isn't learned, we are born with it. Same with fear of small moving objects like spiders or snakes. Such things are learned/stored very different from memories, but its certainly…

Of course it is learned, and fear is triggered by anything unfamiliar, that causes a high reconstruction error. Because it means you don't understand it, and it could be dangerous. We are just not used to encoding anything so deep below the eye level, and it freaks us out.

Do you really think every single ant is learning all that on its own? And if ants can store that in their DNA, why don't you think other animals can? DNA works just fine as generic information storage, there are obviously a ton of behaviors and information encoded there from hundreds of millions of years of survival of the fittest.

Re: John Carmack talk at Upper Bound 2025

#234

Post by mike_hearn »

albertzeyer wrote: post #50
kamranjon wrote: post #2

I was really excited when I heard Carmack was focusing on AI and am really looking forward to watching this when the video is up - but just from looking at the slides it seems like he tried to build a system that can play the Atari? Seems like a fun project, but curious what will come out of it or if there is an associated paper being released.

His goal was not just to solve Atari games. That was already done. His goal is to develop generic methods. So you could work with more complex games or the physical world for that, as that is what you want in the end. However, his insight is, you can even modify the Atari setting to test this, e.g. to work in realtime, and the added complexity by more complex games doesn't really give you any new additional insights…

But how is this different to what NVIDIA have already done? They have robots that can achieve arbitrary and fluid actions in the real world by training NNs in very accurate GPU simulated environments using physics engines. Moving a little Atari stick around seems like not much compared to sorting through your groceries etc.

The approach NVIDIA are using (and other labs) clearly works. It's not going to be more than a year or two now before robotics is as solved as NLP and chatbots are today.

Re: John Carmack talk at Upper Bound 2025

#235

Post by Jensson »

alickz wrote: post #227
ferguess_k wrote: post #133

Earlier quoted context omitted.

We don't really need AGI. We need better specialized AIs. Throw in a few specialized AIs and they will leave some impact in the society. That might not be that far away.

What if AGI is just a bunch of specialized AIs put together? It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes I wonder if AI is the same

> It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes

You can say that about other animals, but about humans it is not so sure. No animal can be taught as general set of skills as a human can, they might have some better specialized skills but clearly there is something special that makes humans so much more versatile.

So it seems there was this simple little thing humans got that makes them general, while for example our very close relatives the monkeys are not.

Re: John Carmack talk at Upper Bound 2025

#236

Post by ferguess_k »

Workaccount2 wrote: post #164
bluGill wrote: post #138

Earlier quoted context omitted.

Specialized AIs have been making an impact on society since at least the 1960s. AI has long suffered from every time they come up with something new it gets renamed and becomes important (where it makes sense) without giving AI credit. From what I can tell most in AI are currently hoping LLMs reach that point quick just because the hype is not helping AI at all.

Yesterday my dad, in his late 70's, used Gemini with a video stream to program the thermostat. He then called me to tell me this, rather then call me to come stop by and program the thermostat. You can call this hype, maybe it is all hype until LLMs can work on 10M LOC codebases, but recognize that LLMs are a shift that is totally incomparable to any previous AI advancement.

Yeah. As a mediocre programmer I'm really scared about this. I don't think we are very far from AI replacing the mediocre programmers. Maybe a decade, at most.

I'd definitely like to improve my skills, but to be realistic, most of the programmers are not top-notch.

Re: John Carmack talk at Upper Bound 2025

#237

Post by fennecfoxy »

Jensson wrote: post #235
alickz wrote: post #227

Earlier quoted context omitted.

What if AGI is just a bunch of specialized AIs put together? It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes I wonder if AI is the same

> It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes You can say that about other animals, but about humans it is not so sure. No animal can be taught as general set of skills as a human can, they might have some better specialized skills but clearly there is something special that makes humans so much more versatile. So it seems there was this simple little t…

Humans are the ceiling at the moment yes, but that doesn't mean the ceiling isn't higher.

Science is full of theories that are correct per our current knowledge and then subsequently disproven when research/methods/etc improves.

Humans aren't special, we are made from blood & bone, not magic. We will eventually build AGI if we keep at it. However unlike VCs with no real skills except having a lot of money™, I couldn't say whether this is gonna happen in 2 years or 2000.

Re: John Carmack talk at Upper Bound 2025

#238

Post by gregdeon »

koolala wrote: post #189
gregdeon wrote: post #97

Earlier quoted context omitted.

I watched the talk live. I felt that his main argument was that Atari _looks_ solved, but there's still plenty of value that could be gained by revisiting these "solved" games. For one, learning how to play games through a physical interface is a way to start engaging with the kinds of problems that make robotics hard (e.g., latency). They're also a good environment to study catastrophic forgetting: an hour of traini…

Is a highly specialized bespoke robot for a Atari controller really that different? If anyone cared about latency they could have added it to the emulated controls and video with random noise.

I think it is. Latency was just one of the problems he described. A physical controller sometimes adds "phantom inputs" as the joystick transitions between two inputs. Physical actuators also slow down with wear. A physical Atari-playing robot needs to learn qualitatively different strategies that are somewhat more robust to these problems. Emulators also let the bot take as much time as it needs between frames, which is much easier than playing in real time. To me, all of this makes a physical robot seem like a decent way to start engaging with problems that come up in robotics but not simulated games.

Re: John Carmack talk at Upper Bound 2025

#239

Post by babyent »

ferguess_k wrote: post #133
johnb231 wrote: post #52

Earlier quoted context omitted.

From the notes: "A reality check for people that think full embodied AGI is right around the corner is to ask your dancing humanoid robot to pick up a joystick and learn how to play an obscure video game."

We don't really need AGI. We need better specialized AIs. Throw in a few specialized AIs and they will leave some impact in the society. That might not be that far away.

Why not just hire like 100 of the smartest people across domains and give them SOTA AI, to keep the AI as accurate as possible?

Each of those 100 can hire teams or colleagues to make their domain better, so there’s always human expertise keeping the model updated.

Re: John Carmack talk at Upper Bound 2025

#240

Post by mike_ivanov »

Jensson wrote: post #235
alickz wrote: post #227

Earlier quoted context omitted.

What if AGI is just a bunch of specialized AIs put together? It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes I wonder if AI is the same

> It would seem our own generalized intelligence is an emergent property of many, _many_ specialized processes You can say that about other animals, but about humans it is not so sure. No animal can be taught as general set of skills as a human can, they might have some better specialized skills but clearly there is something special that makes humans so much more versatile. So it seems there was this simple little t…

It may be a property of (not only of?) humans that we can generate specialized inner processes. The hardcoded ones stay, the emergent ones come and go. Intelligence itself might be the ability to breed new specialized mental processes on demand.
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