We can’t trust AI systems built on deep learning alone • Hacker News Board

Re: We can’t trust AI systems built on deep learning alone

#131

Post by inimino » Mon, Sep 30, 2019, 7:53 PM UTC

Isinlor wrote: post #114

mindgam3 wrote: post #58

> AlphaGo can play very well on a 19x19 board but actually has to be retrained to play on a rectangular board. This right here is the soft underbelly of the entire “machine learning as step towards AGI” hype machine, fueled in no small part by DeepMind and its flashy but misleading demos. Once a human learns chess, you can give it a 10x10 board and she will perform at nearly the same skill level with zero retraining.…

Try learning to ride bike with inverted steering, try to navigate world with your vision flipped over or use your non-dominant hand to do things that you normally do. Well, try to write on Azerty keyboard if you are Qwerty native (really, f k Azerty :P). Humans are also not a general intelligence. In certain sense Deep Reinforcement Learning is actually more general than human intelligence. For example, when playing…

This is true too, we are adapted to our environment, in particular the things that we do automatically (System I).

Playing chess well is a combination of both conscious and unconscious skills. However when deep learning systems play, it is all the unconscious, automatic application of statistical rules. They are playing a very different game from the human chess game.

Because there is no abstract reasoning involved here, these systems cannot apply the lessons learned from chess to another board game, or to something completely different in life, which humans can and do. So even though they are much stronger than human players, they aren't strong in the same way.

Re: We can’t trust AI systems built on deep learning alone

#132

Post by kchamplewski » Mon, Sep 30, 2019, 9:18 PM UTC

mindgam3 wrote: post #127

kchamplewski wrote: post #123

Earlier quoted context omitted.

> Their “general learning” tech doesn’t even generalize to barely modified variants of the original games it has claimed to master. I call bullshit. But the point I was making is precisely that the "general learning" tech is in fact somewhat general. AlphaGo and certainly AlphaZero's learning tech generalises to Go, chess, and a few other games. That's relatively general in the domain of board games, in my humble opi…

You appear to be completely missing the point of my root comment, which is that AlphaGo’s tech isn’t nearly as general as it’s made out to be, even if you stick to Go. > AlphaGo can play very well on a 19x19 board but actually has to be retrained to play on a rectangular board. It doesn’t even generalize to the same game with a different board shape. Whereas a human Go master could easily do so. DeepMind is essential…

But the training process does generalise. The same training process produces an agent that works on a 19x19 board, or a standard Go board, or even a game of chess.

How is that not general? Sure it doesn't work for all problems but in the domain of board games it definitely feels very general.

The agent the training algorithm produces may not be general, but out of what I've read I've only ever seen DeepMind claim generality of the learning algorithm, not the agent.

Re: We can’t trust AI systems built on deep learning alone

#133

Post by newen » Wed, Oct 02, 2019, 2:47 AM UTC

m0zg wrote: post #112

newen wrote: post #109

Earlier quoted context omitted.

No, huge majority of those patterns are going to transfer over to the 10x10 board.

How? Remember, there'd have to be more pieces, and the new pieces could have different moves. The game would also be dramatically more difficult, combinatorially.

Chess is already very difficult, combinatorially. Chess players learn patterns with the current pieces. Those patterns include patterns that work both locally and globally. When learning a particular pattern, chess players typically can generalize that pattern to other cases. (This is what tactics training is all about. You're almost never going to find the exact same pattern that you learn in tactics training in the real world but tactics training will help you recognize similar patterns.) New pieces are going to give you new patterns you have to learn. But ranks, files, and diagonals are not going away. New pieces will likely be a bishop-knight combo piece and a rook-knight combo piece as in Seirawan chess. Therefore, they will still have common patterns you can recognize. The larger board is not a non-issue but it's not anywhere near as drastic a change as you're making it out to be. Most tactics in chess don't make use of the fact that the board is 8x8 rather than 10x10. They'll work in both boards.