The singularity is defined as a moment in time when the A.I. improves itself to such a degree that humanity can no longer keep up.
Throwing more compute power vs a single opponent is not the same thing. How would this computer fare against the top 10 best players collaborating(or even top 90-100)? I would bet it would lose big time.
It is unlikely, also, that a committee of players would be significantly better than a single master, due to lack of coherence -- but that's an interesting idea! I wonder if a committee of the top 100 go players playing a game by vote could beat someone in the top 10 more than 20-0 or something; i doubt it -- it might even go the other way (that the single player would win the series)
I don't think this counts as the real "start of the singularity" because Alphazero was not able to (or capable of) altering its own algorithm, but rather just adjusting its weights.
Something more akin to being in the long march toward general AI.
As a personal note the whole issue of large LLM's capacity for intelligence, beauty, humanity, morality, logic, etc etc was softened in my mind and heart by witnessing with rapt attention this epochal shift in computing.
I had held Go up as a paragon of human brilliance and beauty -- to see that standard fall was a complex process of grief and discovery for me, which I feel has better prepared me for understanding and appreciating the emergence of LLMs
Winning, I think, is secondary to this. It's a useful measure of how one has progressed in that transformation, but I think the lessons and principles from Go that I can apply in guiding my my day-to-day life are more valuable.
How would this computer fare against the top 10 best players collaborating(or even top 90-100)? I would bet it would lose big time.
The top 10 chess grandmasters in the world working together could not beat the best (or even "mediocre") chess engine. Not even close. They're practically playing different games.
Against the AlphaGo of 2015? They might win, but probably not (I think you're overestimating how much collaboration would help). Against today's AlphaGo/KataGo/FineArt/etc there's literally zero chance, even with a two stone handicap. Same goes for 100 GMs playing collaborative chess against Stockfish.
(that said, I agree calling this the singularity is overkill)
I think even with that in account, RL has only reached a tiny fraction of its potential. We have focused so much on supervised and unsupervised learning for so many years, and then been wow'ed by LLMs we have only see RL start to impact industries in self-driving/flying vehicles, and forget about all the other potential.
The thing about RL that people don't seem to understand is that it is mathematically proven to find the optimal control policy.
In the context of go, that means the only way it can be beaten is through variance (or "luck", if you prefer). As there is no dice or random element in go, the top players in the World basically have to be optimal in every move to get a draw. And then again, and again, and again.
And that's the best they can do if the RL algorithm has stopped learning - it's found an optimal strategy, and it can't be beaten, only matched.
Think about all the optimisation and control problems out there that could benefit from this. And yet still we seem to think it's like supervised/unsupervised learning and only "accurate" to ~90+%, and so it doesn't get the attention it deserves.
Or perhaps I'm a dreamer and an optimist and you're right.
I would happily take the other side of that bet though. At even money, I have all the EV, I'm confident of it.
Katago can give handicap stones to pros and win. It's as much better than pros as pros are better than unserious amateurs.
It's not even a matter of compute power, katago is very good with 0 playouts.
I believe in Go that is no longer the case, however. A human provides no additional value to a Go engine.
That's why you shouldn't bet money on things you don't know about...