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How much did AlphaGo Zero cost? (2018)

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Re: How much did AlphaGo Zero cost? (2018)

#171

Post by tuxiano »

JamesBarney wrote: post #167
tuxiano wrote: post #163

Earlier quoted context omitted.

I don't know the last one but I recall the matches of Hydra chess machine [0] in the early 2000s against GM Adams in tournament condition (5½ to ½ for the machine) and against GM Nickel in correspondence condition (2 to 0 for the human). Both Grandmaster were top players in their relative field so it showed very clearly how the time limitation impacted the competitive results. Nobody in the chess elite would claim th…

But wasn't Hydra 2005 ~2800 ELO where as the current best chess engines like Leela Chess Zero or Stockfish are ~4000 ELO? Just realized that correspondence chess is cyborg chess, I didn't know computers were legal in correspondence chess, but it makes sense now. Reading about it, it sounds like it's less about knowing chess, and more about understanding the applications you're using.

Chess engine ratings are not immediately comparable to human ratings as they are extracted from different pools. Hydra played relatively few games so its rating estimation was somewhat approximate but it was clearly "superhuman" (GM Adams was n°7 in the world and only scored one draw in 6 games). Today Stockfish is awarded a rating of about 3500 [0] with a typical PC hardware but this rating comes from matches between engines and not with humans.

Regarding the argument of "knowing chess", it depends on you definition. I often use this analogy. Correspondence chess is to tournament chess what the marathon is to track running. They require different skills and training but I guarantee to you that a lot of understanding is involved in correspondence chess, possibly more than in tournament chess.

[0] https://ccrl.chessdom.com/ccrl/4040/

Re: How much did AlphaGo Zero cost? (2018)

#172

Post by tuxiano »

nl wrote: post #168
tuxiano wrote: post #157

Earlier quoted context omitted.

You are right if by "better" you mean "competitively stronger at tournament or rapid conditions". Humans are still way stronger strategically and competitively if given enough time and resources to avoid tactical mistakes. So yes, humans still provide unique insight into chess every day in correspondence chess or analytic research.

Humans aren't stronger strategically anymore either, under any conditions. In 2014 a heavily handicapped Stockfish beat the 5th ranked player in the world (Nakamura) under tournament conditions despite no access to its opening or closing books and a one pawn handicap.

The match you are referring to was played under tournament conditions that clearly handicapped the human Grandmaster. I read from the report of the match [0] that "The total time for the match was more than 10 hours [...] The two decisive games lasted 147 and 97 moves." This unfavourable conditions clearly penalized the human and so the result can hardly be taken as meaningful regarding the strategic superiority. From the quietness of my room I instead regularly find strategic plans that overcome my and my opponent's computers. Feel free to join the correspondence chess federation [1] to experience the joy and pain of strategic research!

[0] https://www.chess.com/news/view/stockfish-outlasts-nakamura-... [1] www.iccf.com

Re: How much did AlphaGo Zero cost? (2018)

#173

Post by JamesBarney »

tuxiano wrote: post #171
JamesBarney wrote: post #167

Earlier quoted context omitted.

But wasn't Hydra 2005 ~2800 ELO where as the current best chess engines like Leela Chess Zero or Stockfish are ~4000 ELO? Just realized that correspondence chess is cyborg chess, I didn't know computers were legal in correspondence chess, but it makes sense now. Reading about it, it sounds like it's less about knowing chess, and more about understanding the applications you're using.

Chess engine ratings are not immediately comparable to human ratings as they are extracted from different pools. Hydra played relatively few games so its rating estimation was somewhat approximate but it was clearly "superhuman" (GM Adams was n°7 in the world and only scored one draw in 6 games). Today Stockfish is awarded a rating of about 3500 [0] with a typical PC hardware but this rating comes from matches betwee…

Oh I assumed it required quite a bit of chess knowledge and skill. But I assume what differentiates a good from great player isn't unassisted chess ability. Basically I'm wondering how well do correspondence ratings track with unassisted ratings. It was my understand they don't track really well at the higher levels of correspondence chess.

Re: How much did AlphaGo Zero cost? (2018)

#174

Post by ajnin »

__s wrote: post #131
ipsum2 wrote: post #2

Alpha Go Zero*, which was trained from scratch, without human games. I've also heard rumors that AlphaStar ( https://deepmind.com/blog/article/alphastar-mastering-real-t... ) was essentially put on hold because it was too expensive to improve/train. The bot wasn't able to beat StarCraft champions and _only_ got to a grandmaster level.

https://www.youtube.com/watch?v=nbiVbd_CEIA At the last Blizzcon they had it around. The setup wasn't ideal, so Serral (won world finals in 2018, reached semifinals in 2019) wasn't really happy with how he played, but it won This was also a version where they'd worked on preventing its ability to micro at quadruple digit apm

That match was still arguably not fair for the human because of the imperfect input and outputs he had to deal with. In the end I'm not sure it makes sense to put artificial handicaps on the machine to leave the human a chance. It's like a swimming race between a fish and some land animal but the fish is not allowed to use its fins. Sure the other guy has a better chance to win, but, what does that measure really?

Re: How much did AlphaGo Zero cost? (2018)

#175

Post by andbberger »

PeterisP wrote: post #62
andbberger wrote: post #32

Earlier quoted context omitted.

That's a pretty big claim. One could argue that the topology of the brain is a prior, analogous to the architecture of a neural net. But considering that we really have no idea how learning happens in the brain on a large scale, you really can't say.

I believe that there's a reasonable (but unprovable) assumption that any games which humans usually play - because the rulesets are learnable and interesting for humans - implicitly rely on priors of human brains and behavior. The space of possible games is huge (infinite?), but only a tiny subset of these games could reasonably become a popular game for humans. E.g. it's not an arbitrary random coincidence that the…

Games are designed to be fun and playable by humans, this doesn't seem surprising

Re: How much did AlphaGo Zero cost? (2018)

#176

Post by andbberger »

yamrzou wrote: post #66
andbberger wrote: post #32

Earlier quoted context omitted.

That's a pretty big claim. One could argue that the topology of the brain is a prior, analogous to the architecture of a neural net. But considering that we really have no idea how learning happens in the brain on a large scale, you really can't say.

Does anyone have an idea about the advances in research about this topic i.e. human intelligence and how learning happens in the brain? I know Josh Tenenbaum from MIT [1] works on this, see for example : - How to Grow a Mind: Statistics, Structure and Abstraction [2] - Steps towards more human-like learning in machines [3] Wondering if there are other researchers exploring similar questions. [1] http://web.mit.edu/co…

There is very little that we understand about the larger picture of how learning happens in the brain. We have some understanding of how learning happens on very small scales, I'm talking plasticity at a single synapse. But even restricting ourselves to a single synapse, there is much we don't know. At the least, it's clear that synapses and dendrites have impressive computational capacity but making detailed measurements is currently beyond the reach of our experimental apparati. We can measure signals in dendrites and synapses, but not at a high enough spatiotemporal resolution to answer the big questions.

And we're starting to bump against fundamental limits of these apparati. Most modern neurobiology uses genetically encoded fluorescent sensors read out by rather expensive 2-photon microscopes. The sensors aren't as crisp as one wishes - there is a huge subfield dedicated just to deconvolving these fluorescent sensor readings into what the neurons are actually doing. And there's only so much further the 'scopes can be pushed.

The point being: it's really quite difficult to overstate just how overwhelmingly complex the brain is and how far we are from understanding even little really specific bits of it, let alone the whole thing.

That being said, the redwood center for theoretical neuroscience does some excellent work bridging the cutting edge of theory neuro and machine learning - towards the larger picture of how the brain works. You might be surprised at how 'rudimentary' the questions we're trying to solve in that domain are. Most work focuses on the visual system - far easier to study something when you have a good idea of what it's supposed to do (as opposed to, say, cortex).

I am not aware of anything resembling a grand theory that makes experimentally verifiable predictions. I am pretty sure I would have heard of such a thing if it existed.

Re: How much did AlphaGo Zero cost? (2018)

#177

Post by andbberger »

amelius wrote: post #58
andbberger wrote: post #32

Earlier quoted context omitted.

That's a pretty big claim. One could argue that the topology of the brain is a prior, analogous to the architecture of a neural net. But considering that we really have no idea how learning happens in the brain on a large scale, you really can't say.

True, but a spider doesn't figure out how to build a web all by itself. That's to say, there is a lot that evolution can provide us with as a prior.

Yes it is clearly possible to encode behavioral priors, there are many examples from different species.

But humans aren't spiders. We've got the big brain, it's kind of our thing

Re: How much did AlphaGo Zero cost? (2018)

#178

Post by visarga »

sukilot wrote: post #116
visarga wrote: post #60

Earlier quoted context omitted.

> In other words, machines required 137 times longer to learn the game, and at twice the power consumption! This comparison is a bit unfair. Humans are the result of evolution on a grand scale. Human Go is the result of millennia of gameplay. A human does not become grand master in isolation. AlphaGo is the result of an evolutionary tournament style competition of a much smaller duration and breadth. AG is also a pop…

AlphaGo is the result of human evolution too.

Human evolution is a result of mammal evolution, and so on. The question is how to compare in a fair way?

Re: How much did AlphaGo Zero cost? (2018)

#179

Post by scheveningen »

roenxi wrote: post #154
scheveningen wrote: post #140

Earlier quoted context omitted.

It's much more difficult than it used to be, but I think there is still some value to human guidance, more as a "referee" than anything else. Right now we have essentially two top tier engines -- traditional brute force with alpha beta pruning (stockfish), and ML (leela). Both alone are incredibly strong, but they are strongest and weakest in different types of positions. A computer chess expert, who knows what kind…

Computer mastery of Go has reached the point where it is a difficult task for an expert (read: grandmaster level) human to even follow what is happening. It is totally implausible that a human could resolve a conflict between top engines in a meaningful way. It is unlikely that Chess is any different. Any superficial understanding by a human of which move is 'better' is just ignorance of the issues around evaluating…

I don't even know the rules of Go, but I am a long-time chess enthusiast, and I have a decent, but not top-level, understanding of chess (I am a FIDE master and I also play correspondence chess (which is human+engine) and have an interest in computer chess heavily).

I can absolute guarantee you that a human (who is an expert in computer chess, someone like Larry Kaufman) + engines will beat a single engine over the long run. With current tech and computing power, this is ONLY because we have brute force (with alpha-beta pruning) and ML engines that are at near-equal strength, and have strengths and weaknesses in different types of positions, and that those strengths and weaknesses are understandable.

If we did not have AlphaZero, I don't think the human would be able to add anything at all currently.

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