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John Carmack talk at Upper Bound 2025

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Re: John Carmack talk at Upper Bound 2025

#221

Post by Jensson »

lo0dot0 wrote: post #163
tschillaci wrote: post #37

Earlier quoted context omitted.

You will find many agents that solved (e.g., finished, reached high score) atari games, but there is still so much more work to do in the field. I wrote my Master's thesis on how to learn from few interactions with the game, so that if the algorithm is ported to actual robots they don't need to walk and fall for centuries before learning behaviors. I think there is more research to do on higher levels of generalizati…

I can tell you right now without any research that video game designers reuse interface patterns and game mechanics that were already known when making new games. Those patterns and mechanics are also often analogies for real life allowing humans to intuitively play the games. If people can't play your game intuitively, they might say it's a bad game.

So why can't AI learn those and reapply the same understanding to new games?

Re: John Carmack talk at Upper Bound 2025

#222

Post by lostmsu »

floren wrote: post #207
dusted wrote: post #55

Earlier quoted context omitted.

"in the terms of bros" what does that even mean? I think bro is a term that's used pretty widely, for different things, in different cultures and contexts, I call my brother bro.. I've heard people call their friends bro.. I've heard someone tell a police officer "don't tase me, bro"..

My co-worker's 7 year old daughter calls him "bruh"

I call my 4yo daughter bro

Re: John Carmack talk at Upper Bound 2025

#223

Post by Jensson »

mindwok wrote: post #160
steveBK123 wrote: post #105

Another thought experiment - if OpenAI AGI was right around the corner, why are they wasting time/money/energy buying a product-less vanity hardware startup run by Ive? Why not tackle robotics if anything. Or really just be the best AGI and everyone will be knocking on your door to license it in their hardware/software stacks, you will print infinite money.

AGI is not enough. Seriously, imagine if they had an AGI in their ChatGPT interface. It’s not enough to do anything truly meaningful. It’s like a genius in the woods somewhere. For AGI to have an impact it needs to be everywhere.

> Seriously, imagine if they had an AGI in their ChatGPT interface. It’s not enough to do anything truly meaningful

If they had that people would make agents with it and then it can do tons of truly meaningful things.

People try to make agents with the current one but its really difficult since its not AGI.

Re: John Carmack talk at Upper Bound 2025

#224

Post by alexey-salmin »

qoez wrote: post #76

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

Each of these games is low-dimensional and require not the "intelligence" but more like "reflexes", I tend to agree.

However making a system that can beat an unknown game does require generalization. If not real a intelligence (whatever that means) but at the level of say "a wolf".

Whether it can arise from RL alone is not certain, but it's there somewhere.

Re: John Carmack talk at Upper Bound 2025

#225

Post by bluefirebrand »

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.

> He then called me to tell me this, rather then call me to come stop by and program the thermostat.

Sounds like AI robbed you of an opportunity to spend some time with your Dad, to me

Re: John Carmack talk at Upper Bound 2025

#226

Post by Jensson »

foldr wrote: post #131
RetroTechie wrote: post #119

Earlier quoted context omitted.

You're forgetting that a whole string of breakthroughs are all fairly recent (like in the last decade). Everyone , including the pro's, is treading new ground. In that context anyone can make progress in the field, as long as they understand what they're dealing with. Better regard mr. Carmack as an X factor. Maybe the experts will leave him in the dust. Or maybe he'll come up with something that none of the experts…

Lots of scientific fields have seen breakthroughs in the past decade. Doesn’t mean that any random smart person can jump in and start doing groundbreaking research.

But a random smart person will jump in and make groundbreaking research.

Re: John Carmack talk at Upper Bound 2025

#227

Post by alickz »

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.

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

Re: John Carmack talk at Upper Bound 2025

#228

Post by Jensson »

charcircuit wrote: post #217
nightski wrote: post #208

Earlier quoted context omitted.

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?

AGI is transformative in that it lets us replace knowledge workers completely, specialized AI requires knowledge workers to train them for new tasks while AGI doesn't.

Re: John Carmack talk at Upper Bound 2025

#229

Post by Nopoint2 »

Jensson wrote: post #216
Nopoint2 wrote: post #185

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? 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…

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.

Re: John Carmack talk at Upper Bound 2025

#230

Post by lostmsu »

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 requires random search in a massive state space. But in the vast sea of scenarios that you can find in Common Crawl there's probably one, where you are 1 step from the key, and the key is 1 step from the door, so you get the reward signal from it without having to search an enormous state space.

You might say "but you have to search through the giant Common Crawl". Well yes, but while doing so you will get reward signal not just for the key and door problem, but for nearly every problem in the world.

The point is: pretraining teaches models to extract signal that can be used to explore solutions to hard search problems, and if you don't do that you are wasting your time enumerating giant state spaces.

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