You shouldn’t worry about whether something “is AGI”; it’s an I’ll-defined concept. I agree that current models are lacking the ability to accomplish long-term tasks in the real world, and this keeps them safe. But I don’t think this is permanent, for two reasons.
Current large-language-model type AI is not capable of continuous learning, it is true. But AIs which are capable of it have been built. AlphaZero is perhaps the best example; it learns to play games to a superhuman level in a few hours. It’s a topic of current research to try to combine them.
Moreover, tool-type AIs tend to be developed to provide agency, because it’s more useful to direct an agent than it is a tool. This is a more fully fleshed out here: https://gwern.net/tool-ai
Much of my probability of non-doom is resting on people somehow not developing agents.
MuZero doesn’t seem categorically different from AlphaZero. It has to do a little bit more work at the beginning, but if you don’t get any reward for breaking the rules: you will learn not to break the rules. If MuZero is continuously learning then so is AlphaZero. Also, the games used were still computationally simple, OOMs more simple than an open-world game, let alone a true World-Model. AFAIK MuZero doesn’t work on open-ended, open-world games. And AlphaStar never got to superhuman performance at human speed either.
I am in violent agreement. Nowhere did I say that MuZero could learn a world model as complicated as those LLMs currently enjoy. But it could learn continuously, and execute pretty complex strategies. I don’t know how to combine that with the breadth of knowledge or cleverness of LLMs, but if we could, we’d be in trouble.
You shouldn’t worry about whether something “is AGI”; it’s an I’ll-defined concept. I agree that current models are lacking the ability to accomplish long-term tasks in the real world, and this keeps them safe. But I don’t think this is permanent, for two reasons.
Current large-language-model type AI is not capable of continuous learning, it is true. But AIs which are capable of it have been built. AlphaZero is perhaps the best example; it learns to play games to a superhuman level in a few hours. It’s a topic of current research to try to combine them.
Moreover, tool-type AIs tend to be developed to provide agency, because it’s more useful to direct an agent than it is a tool. This is a more fully fleshed out here: https://gwern.net/tool-ai
Much of my probability of non-doom is resting on people somehow not developing agents.
Whoops, meant MuZero instead of AlphaZero.
MuZero doesn’t seem categorically different from AlphaZero. It has to do a little bit more work at the beginning, but if you don’t get any reward for breaking the rules: you will learn not to break the rules. If MuZero is continuously learning then so is AlphaZero. Also, the games used were still computationally simple, OOMs more simple than an open-world game, let alone a true World-Model. AFAIK MuZero doesn’t work on open-ended, open-world games. And AlphaStar never got to superhuman performance at human speed either.
I am in violent agreement. Nowhere did I say that MuZero could learn a world model as complicated as those LLMs currently enjoy. But it could learn continuously, and execute pretty complex strategies. I don’t know how to combine that with the breadth of knowledge or cleverness of LLMs, but if we could, we’d be in trouble.