AlphaGo Zero: Learning from scratch
deepmind.com
AlphaGo Zero: Learning from scratch
1–10 of 324 posts
Re: AlphaGo Zero: Learning from scratch
#2This is pretty incredible, especially the power dissipation results. Only 4 TPUs? Humans are toast.
Re: AlphaGo Zero: Learning from scratch
#3> Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play.
So technically this version has lost every game it's ever won.
Jokes aside, it's pretty interesting to note that they were able to combine the "policy" and "value" networks. Good SO answers on the difference (https://datascience.stackexchange.com/questions/10932/differ...)
> accumulating thousands of years of human knowledge during a period of just a few days
It'd be interesting for what this would mean when things like a neural lace become a reality.
As an aside, anyone have any other links or references to others investigating learning algorithms with a 'tabula rasa' approach?
Re: AlphaGo Zero: Learning from scratch
#4"It uses one neural network rather than two."
and
"AlphaGo Zero only uses the black and white stones from the Go board as its input, whereas previous versions of AlphaGo included a small number of hand-engineered features."
This is amazing! The technology they came up with must be super generic.
Re: AlphaGo Zero: Learning from scratch
#5Comparing the top player's ELO with Zero's ELO (assuming numbers are accurate, etc):
Your rating: 3664
Opponent's rating: 5000
Probability of winning: 0.000456879355457417
So 1 in 2,200 games... ouch
Re: AlphaGo Zero: Learning from scratch
#6Is this evidence of a broader leap forward in machine learning, or are these advancements domain-specific? In other words, could these innovations be applied to other fields and applications?
Re: AlphaGo Zero: Learning from scratch
#7I'm reminded of Eliezer Yudkowski's article "There is no fire Alarm for Artificial General Intelligence." Is this smoke?
https://intelligence.org/2017/10/13/fire-alarm/
Yes, this is not an AGI. But the hockey-stick takeoff from defeats some players, to defeats an undefeated world-champion, to defeats the version of itself that beat the world champion 100% of the time is nuts. If this happens in other domains, like finance, health, paper clip collection, the word singularity is really well chosen--we can't see past this.
Re: AlphaGo Zero: Learning from scratch
#8Is this evidence of a broader leap forward in machine learning, or are these advancements domain-specific? In other words, could these innovations be applied to other fields and applications?
I haven't read the paper yet but "AlphaGo Zero only uses the black and white stones from the Go board as its input, whereas previous versions of AlphaGo included a small number of hand-engineered features."
This sound super generic, so yes.
Re: AlphaGo Zero: Learning from scratch
#9Anyone happen to have a link (or can PM one to me) to a copy that isn't behind a paywall?
Re: AlphaGo Zero: Learning from scratch
#10Is this evidence of a broader leap forward in machine learning, or are these advancements domain-specific? In other words, could these innovations be applied to other fields and applications?
It's further advancement of reinforcement learning which is notoriously difficult to train into usefulness.