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Amazing! Anyone has ideas on how to: 1. Bet on AGI, 2. Encourage AGI? I have a strong belief that it could grow and I’d like to contribute (and join the development)
Whoa, this is extremely impressive. Quotes from the BBC article: > "For the first time, we actually have a system which is able to build its own understanding of how the world works, and use that understanding to do this kind of sophisticated look-ahead planning that you've previously seen for games like chess. > "[It] can start from nothing, and just through trial and error both discover the rules of the world and u…
Unless they've changed a lot of things since the original paper, this is a bit exaggerated.
MuZero learns what moves are allowed in a given position/situation, but it still needs to know a finite overall set of possible actions.
E.g. for chess, it isn't told which fourty moves a available at each point in its search tree, but it still knows to only consider 64x64 discrete options.
Amazing! Anyone has ideas on how to: 1. Bet on AGI, 2. Encourage AGI? I have a strong belief that it could grow and I’d like to contribute (and join the development)
Buy Alphabet or OpenAI stock. Or even Tesla, which also helps us to get closer to self driving cars. Although I can't comment on whether the trades themselves will give you profit or not, as that's impossible to say at this point :)
Earlier quoted context omitted.
It's not obvious this has much to do with AGI in the sense of human level sentience.
I think it definitely does. Is this AGI, or even close to it? No. But is it in the direction of AGI, or otherwise some small building block of it, that when worked on for decades, may contribute? Definitely
It's an old discussion, and while a few of the deep learning results are really impressive I don't think any of them have fundamentally changed that discussion, yet.
Is there a way to learn Go from scratch using these AIs? I wonder if it would pay off in the long run to be fully trained by one.
What you can do is checkout the algorithm at particular stages of development. AlphaZero&Friends start out not being very good at the game, then over time they learn and eventually become super human. You typically checkpoint the weights for the model at various stages. So early on, the algo would be like a 600 elo player for chess and then eventually get to superhuman elo levels. If you wanted to train using an Alph…
Whoa, this is extremely impressive. Quotes from the BBC article: > "For the first time, we actually have a system which is able to build its own understanding of how the world works, and use that understanding to do this kind of sophisticated look-ahead planning that you've previously seen for games like chess. > "[It] can start from nothing, and just through trial and error both discover the rules of the world and u…
>> "[It] can start from nothing, and just through trial and error both discover the rules of the world Unless they've changed a lot of things since the original paper, this is a bit exaggerated. MuZero learns what moves are allowed in a given position/situation, but it still needs to know a finite overall set of possible actions. E.g. for chess, it isn't told which fourty moves a available at each point in its search…
It wouldn't know that moving its King from e1 to g1 must be accompanied by moving its rook from h1 to f1.
Or that moving a white pawn from e5 to d6 must in some cases be accompanied by removing the black pawn on e6.
I guess the environment does these in response. That doesn't suffice for
moving its pawn from b7 to b8 must be accompanied by replacing said pawn by some other piece.
Is there a way to learn Go from scratch using these AIs? I wonder if it would pay off in the long run to be fully trained by one.
You can play against open source reimplementations of some of the ideas behind AlphaGo family AIs. LeelaZero was one of the early ones, KataGo is probably your best bet right now. Sai is also in the mix. All are _very_ strong. KataGo is ungodly strong, it beats pros. Learning Go is about more than just playing against strong players, but it could help. The biggest difficulty is that the strong AIs aren't actually tha…
You wouldn't know that from watching JBXKataBot playing on KGS with a typical 5-7 stone handicap.
Is there a way to learn Go from scratch using these AIs? I wonder if it would pay off in the long run to be fully trained by one.
You can play against open source reimplementations of some of the ideas behind AlphaGo family AIs. LeelaZero was one of the early ones, KataGo is probably your best bet right now. Sai is also in the mix. All are _very_ strong. KataGo is ungodly strong, it beats pros. Learning Go is about more than just playing against strong players, but it could help. The biggest difficulty is that the strong AIs aren't actually tha…
https://deepmind.com/research/publications/Mastering-Atari-G... https://arxiv.org/pdf/1911.08265.pdf
Earlier quoted context omitted.
I think it definitely does. Is this AGI, or even close to it? No. But is it in the direction of AGI, or otherwise some small building block of it, that when worked on for decades, may contribute? Definitely
It's still not that obvious. There has been a lot of interesting stuff in this current iteration of "AI", but the overall approach could still end up being a dead end with respect to AGI itself. It's an old discussion, and while a few of the deep learning results are really impressive I don't think any of them have fundamentally changed that discussion, yet.