I'm surprised there's as much interest in looking at the structure/behavior of the biological brain, and less interest in considering the behavior of our vision system. Our brains are not CPUs, and our eyes are definitely not a grid of pixels with a fixed framerate.
John Carmack talk at Upper Bound 2025
211–220 of 387 posts
Re: John Carmack talk at Upper Bound 2025
#212Earlier quoted context omitted.
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.
Do you have an X account, if you're not logged in you'll only see the first post in the thread.
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Re: John Carmack talk at Upper Bound 2025
#213Earlier quoted context omitted.
I agree that restricting the hero pool is a huge simplification. But they did play full 5v5 standard dota with just a restricted hero pool of 17 heroes and no illusions/control units according to theverge ( https://www.theverge.com/2019/4/13/18309459/openai-five-dota... ). It destroyed the professionals. As an ex dota player, I don't think this is that far off from having full on, all heroes dota. Certainly not as fa…
> It destroyed the professionals. Only the first time, later when it played better players it always lost. Players learned the faults of the AI after some time in game and the AI had very bad late game so they always won later.
Not on the last iteration.
Re: John Carmack talk at Upper Bound 2025
#214Earlier quoted context omitted.
I agree that restricting the hero pool is a huge simplification. But they did play full 5v5 standard dota with just a restricted hero pool of 17 heroes and no illusions/control units according to theverge ( https://www.theverge.com/2019/4/13/18309459/openai-five-dota... ). It destroyed the professionals. As an ex dota player, I don't think this is that far off from having full on, all heroes dota. Certainly not as fa…
Another issue with the approach is that the model had direct access to game data, that is simply an unfair competitive advantage in dota, and it is obvious why that advantage would be unfair in CS. It is certainly possible, but i won't be impressed by anything "playing CS" that isn't running a vision model on a display and moving a mouse, because that is the game. The game is not abstractly reacting to enemy position…
Did you read the paper? It had access to the dota 2 bot API, which is some gamestate but very far from all gamestate. It also had artifially limited reaction to something like 220ms, worse then professional gamers.
But then again, that is precisely the point. A chess bot also has access to gigabytes of perfect working memory. I don't see people complaining about that. It's perfectly valid to judge the best an AI can do vs the best a human can do. It's not really fair to take away exactly what a computer is good at from an AI and then say: "Look but the AI is now worse". Else you would also have to do it the other way around. How well could a human play dota if it only had access to the bot API. I don't think they would do well at all.
Re: John Carmack talk at Upper Bound 2025
#215Earlier 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.
There are clearly a lot of useful things about LLMs. However there is a lot of hype as well. It will take time to separate the two.
Re: John Carmack talk at Upper Bound 2025
#216Earlier quoted context omitted.
It's because humans (and other animals) have enormous innate capacities and knowledge which makes learning new things much much simpler than if you start from scratch. It's not really because of human's computational capacity.
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? It just isn't needed. Just like you can find let's say kangaroos in the latent space of an image generator, so we learn abstract concepts and principles of how things work as a bonus of learning to process the senses. Maybe a way…
> 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 there and we can see animals also have those. Like cats gets very scared of objects that are long and appear suddenly, like a cucumber, since their genetic instincts thinks its a snake.
Re: John Carmack talk at Upper Bound 2025
#217Earlier 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.
Saying we don't "need" AGI is like saying we don't need electricity. Sure life existed before we had that capability, but it would be very transformative. Of course we can make specialized tools in the mean time.
Can you give an example how it would be transformative compared to specialized AI?
Re: John Carmack talk at Upper Bound 2025
#218Earlier quoted context omitted.
> (100x matmul+tanh?) Biological neurons are way more complex than that. A single neuron has dentritic trees with subunits doing their own local computations. There are temporal dynamics in the firing sequences. There is so much more complexity in the biological networks. It's not comparable.
You could implement a Turing-machine with humans acting physically operating as logic gates. Then, every human is just a boolean function.
Neurons are stateful though, it is core to their function and how they learn.
Re: John Carmack talk at Upper Bound 2025
#219Earlier quoted context omitted.
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's a OpenAI researcher that's worked on some of their most successful projects, and I think the criticism in his X thread is very clear. Systems that can learn to play Atari efficiently are exploiting the fact that the solutions to each game are simple to encode (compared to real world problems). Furthermore, you can nudge them towards those solutions using tricks that don't generalize to the real world.
That sounds like an extremely useful insight that makes this kind of research even more valuable.
Re: John Carmack talk at Upper Bound 2025
#220Earlier 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."
This sounds like a problem that could be solved around the corner with a caveat. Games generally are solvable for AI because they have feedback loops and a clear success or failure criteria. If the "picking up a Joystick" part is the limiting factor, sure. But why would we want robots to use an interface (especially a modern controller) heavily optimized for human hands; that seems like the definition of a horseless…
> But why would we want robots to use an interface (especially a modern controller) heavily optimized for human hands; that seems like the definition of a horseless carriage.
Elon's response to this is that if we want these androids to replace human jobs then the lowest friction alternative is for the android to be able to do anything a human can do in a human amount of space. A specialized machine is faster and more efficient, but comes with engineering and integration costs that create a barrier to entry. Elon learned this lesson the hard way when he was building out the gigafactories and ended up having to hire a lot of people to do the work while they sorted out the issues with the robots. To someone like Elon a payroll is an ever growing parasite on a companies bottom line, far better if the entire thing is automated.