81–90 of 387 posts
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.
Honestly, having gone through the slides, it's a bit painful to see Carmack "rediscover" stuff I've learned in a reinforcement learning lecture like ten years ago. But don't get me wrong! Since this is a long-term research endeavor of his, I believe really starting from the basics is good for him and will empower him to bring something new to the table eventually. I'm surprised though that he "only" came so far as of…
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."
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…
Interesting reply from an openai insider: https://x.com/unixpickle/status/1925795730150527191
Earlier quoted context omitted.
> But it still feels like some key ingredient is missing. Continuous training is the key ingredient. Humans can use existing knowledge and apply it to new scenarios, and so can most AI. But AI cannot permanently remember the result of its actions in the real world, and so its body of knowledge cannot expand. Take a toddler and an oven. The toddler has no concept of what an oven is other than maybe that it smells nice…
> Humans can use existing knowledge and apply it to new scenarios, and so can most AI Doesn't the article states that this is not true? AI cannot apply to B what it learned about A.
I feel top level AI creation is beyond his skill set. He’s a AAA software engineer but the prerequisites to build out cutting edge AI require deep formal math that is beyond his education and years at this point. Nothing to stop him playing around with AI models though.
So I asked Ilya, their chief scientist, for a reading list. This is my path, my way of doing things: give me a stack of all the stuff I need to know to actually be relevant in this space.
And he gave me a list of like 40 research papers and said, 'If you really learn all of these, you'll know 90% of what matters today! And I did. I plowed through all those things and it all started sorting out in my head.
Honestly, having gone through the slides, it's a bit painful to see Carmack "rediscover" stuff I've learned in a reinforcement learning lecture like ten years ago. But don't get me wrong! Since this is a long-term research endeavor of his, I believe really starting from the basics is good for him and will empower him to bring something new to the table eventually. I'm surprised though that he "only" came so far as of…
https://x.com/unixpickle/status/1925795730150527191
I'm nowhere as good at my craft as someone who works for openai, which the author of that tweet seems to be, but if even I can see this, then it's bad, isn't it?
Bro went his whole career and managed to somehow create a gig for himself where he gets the AI money while playing Atari. It's hard to increase the respect for someone who you already maxed out on but there we go. Carmack is a cool guy.
Although Carmack is the quintessential not-a-brogrammer.
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."
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…
Interesting reply from an openai insider: https://x.com/unixpickle/status/1925795730150527191
And I say this while most certainly not being as knowledgeable as this openai insider. So it even I can see this, then it's kinda bad, isn't it?