> 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.
Give the same challenge to DeepMind’s “superhuman” game-playing machine and it will be an absolute patzer.
This is an obvious indicator that the state of the art in so-called “machine learning” doesn’t involve any actual learning in the way it is normally applied to intelligent systems like humans or animals.
I am continually amazed by the failure of otherwise exceedingly intelligent tech people to grasp this problem.
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.
Give the same challenge to DeepMind’s “superhuman” game-playing machine and it will be an absolute patzer.
This is an obvious indicator that the state of the art in so-called “machine learning” doesn’t involve any actual learning in the way it is normally applied to intelligent systems like humans or animals.
I am continually amazed by the failure of otherwise exceedingly intelligent tech people to grasp this problem.