[HN Gopher] In two moves, AlphaGo and Lee Sedol redefined the fu...
___________________________________________________________________
In two moves, AlphaGo and Lee Sedol redefined the future (2016)
Author : kaycebasques
Score : 85 points
Date : 2023-11-17 16:45 UTC (6 hours ago)
(HTM) web link (www.wired.com)
(TXT) w3m dump (www.wired.com)
| taneq wrote:
| For me, that move in game 2 marked the official start of the
| Singularity, although in one sense it's all the same exponential
| curve we've been riding since, well...
|
| That's the neat thing about exponential curves, you always feel
| like you're at the fun part of them.
| Gud wrote:
| Maybe for you it did, but not for the rest of the world.
|
| 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.
| bondarchuk wrote:
| I agree with taneq actually, just after the match I attended
| an impromptu lecture by a professor who also had some go
| knowledge, at the time I really felt like I was witnessing
| something new and important. In retrospect I still think of
| that as the kickoff of the current AI wave.
| vecter wrote:
| 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 would destroy them in the same way. The marginal value of
| each additional human brain quickly approaches zero (or
| perhaps even negative as the team tries to
| communicate/collaborate).
|
| 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.
| blaufuchs wrote:
| >How would this computer fare against the top 10 best players
| collaborating(or even top 90-100)?
|
| 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)
| toolz wrote:
| I don't know much about go, but AI is so much better at chess
| than humans there is no number of humans you could throw at
| the problem to beat the engine.
| Kranar wrote:
| You are correct. The closest thing there is is called
| Centaur Chess where a human and computer work together. At
| least as of 2021, a human and computer combination could
| outperform just a computer indicating that a human still
| provides value to a chess engine.
|
| I believe in Go that is no longer the case, however. A
| human provides no additional value to a Go engine.
| helpfulmountain wrote:
| There is no chance that humans can beat the best Go AI
| anymore, since the paradigm of AlphaZero (which was trained
| in the absence of human game records, and beat the version
| which beat Lee Sedol essentially 100-0)
|
| 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
| the8472 wrote:
| It has been tried in chess at least.
| https://en.wikipedia.org/wiki/Kasparov_versus_the_World
| cool_dude85 wrote:
| This is a different kind of setup. I'm not sure if the
| idea of 2-3 super GMs able to consult with one another
| has been tried but given the estimated rating difference
| I doubt it would matter. The difference is estimated
| around 800 points, or the difference between a strong
| untitled player and Magnus.
| hosh wrote:
| Like many other crafts and arts where machines can do
| better, Go has a deeper role in being transformative for
| the human learning it -- in the case of Go, developing
| strategic thinking, being able to make decisions balancing
| long term and short term gain, uniting reasoning and
| intuition, an arena for exercising emotional equanimity.
|
| 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.
| SonOfLilit wrote:
| 4-vs-1 games have been played by the strongest players in
| my club. They say it added around one stone of strength.
| kadoban wrote:
| At Go? Humans cannot win anymore, the AIs are _very_ good.
|
| 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.
| PaulRobinson wrote:
| Deep Mind's big thing with the game of go, and in general to
| be honest, is Reinforcement Learning (RL), a branch of ML
| that until very recently was mostly ignored by industry, and
| only now gets love because of its perceived utility in some
| parts of the GenAI tooling chain.
|
| 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.
| raincole wrote:
| > 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.
|
| That's why you shouldn't bet money on things you don't know
| about...
| tekla wrote:
| It's hard to describe the insanity that took place in Korea
| during this game.
|
| The beauty in a computer saying "fuck you, I'm going to win, this
| isn't a poetry slam, all I need to do is beat you by a single
| point" and demolishing a the best opponent humanity had to offer.
| taneq wrote:
| See, that's the other essential aspect of this moment that most
| people miss, or dismiss as a weird quirk or whatever. AlphaGo's
| utility function was to maximize its chance at winning Go, NOT
| to win _quickly_. So it got into a position where it knew it
| would win, and then dicked around indefinitely because why not.
| Honestly, more than a few people here probably find this too
| relatable.
| bondarchuk wrote:
| Would be nice to have a diagram of the moves in question in the
| article lol
| lvl102 wrote:
| Katago (and Leela) and "blue dot" is changing human vs human
| games too. Interestingly enough, I will say this about Katago:
| you can consistently beat it with +6 handicap. I don't think you
| can say that about pro players.
| helpfulmountain wrote:
| Yeah this speaks to the fragility of current machine learning
| techniques. It wasn't trained to play handicap go, so it's
| quite bad at it.
|
| Similar to what is being called hallucination in LLM area
| BlueTemplar wrote:
| How would a pro fare that never played handicap go ?
| scott_w wrote:
| Probably the same way top 10 GMs do giving Queen odds.
| They'll still stomp most lesser players.
| thmt wrote:
| Nit: KataGo does train on handicap games up to 5 handicap
| stones. In the KataGo write-up "Accelerating Self-Play
| Learning in Go" from 2020, Appendix D says that KataGo trains
| on handicap games with up to 3 handicap stones. Looking at
| the current version of the KataGo code, nowadays it trains
| with handicap up to 5.
| kadoban wrote:
| If you're 2d or so you can beat pros at 6 stones. Is katago
| more beatable than that? I know it's not amazing at high
| handicap, but I wouldn't think so.
| cjfd wrote:
| I went to a talk by Rob van Zeijst about the match of Lee Sedol
| and Alphago and he was saying that after move 37, the push along
| the fourth line would have been better for Lee Sedol. And also,
| move 78 should not have worked, or at least not that well. This
| was also noticed by the real time commentary at the time, IIRC.
| Matumio wrote:
| For those who missed what happened back then, the AlphaGo Movie
| is really worth watching:
| https://www.youtube.com/watch?v=WXuK6gekU1Y
|
| Not very technical, not about Go tactics either, but it's just a
| very well-done movie about the people involved.
| sdfghswe wrote:
| I found it very not worth watching. It seemed just Deepmind PR.
| Very little substance, it was just soap opera grade material.
|
| If a person likes soap operas, they could enjoy the movie.
| tekla wrote:
| Only on HN will you see a recounting of a massive achievement
| of humankind dismissed offhandedly like this.
| dragontamer wrote:
| I'd say Zero Dark Thirty was a bad movie about a major and
| important event.
|
| Calling a movie bad doesn't diminish the original event. It
| just criticizes the movie itself.
| yCombLinks wrote:
| In the long run the development of AI is far more
| significant than relatively minor skirmishes of American
| Imperialism.
| jasonwatkinspdx wrote:
| Eh, the barb about "maybe you like soap operas" wasn't
| necessary and doesn't do the comment any favors.
| sdfghswe wrote:
| In that phrase when I said "you" I didn't mean the person
| I was responding to. I mean the "general you" - a
| hypothetical person. I didn't occur to me it could be
| interpreted differently. I've edited it.
| sdfghswe wrote:
| > tekla 10 minutes ago
| https://news.ycombinator.com/user?id=tekla
|
| > Only on HN will you see a recounting of a massive
| achievement of humankind dismissed offhandedly like this.
|
| I'm not dismissing an achievement of humankind. I'm
| dismissing the PR piece they put out about it.
|
| Do you struggle to see the distinction?
| melling wrote:
| I've seen it twice. It was great. It is a documentary
|
| Sure, I'd like it if they discussed the algorithm and the
| code but you need to entertain a regular audience.
| thefourthchime wrote:
| Same, I've seen it twice. It's all about that moment when
| they realize that "mistake" and then, it's a "God" move,
| and they can't believe it. History was made in that moment.
| They realized computers can have intuition and think like
| they do.
|
| I started showing people ChatGPT when it first came out,
| they shrugged, they didn't get it. Most people still don't
| get how important generative AI is and will be. Eventually,
| they'll have that moment too.
| olddustytrail wrote:
| I enjoyed it too. Surprisingly good, considering it was
| basically about a computer program, they managed to make it a
| human story.
|
| (I wouldn't worry about the criticism from the know-nothings
| below; I doubt a single one has ever had the slightest
| involvement in making a film so they're just ignorant
| loudmouths)
| corndoge wrote:
| > Hassabis and Silver and their fellow researchers have built a
| machine capable of something super-human. But at the same time,
| it's flawed. It can't do everything we humans can do. In fact, it
| can't even come close. It can't carry on a conversation. It can't
| play charades. It can't pass an eighth grade science test. It
| can't account for God's Touch.
|
| That didn't age well
| wslh wrote:
| I understand that the next test is about passing an elementary
| school science test? It is good to put cincrete goals. A few
| time ago computers couldn't beat amateur Go players.
|
| Not saying that computers will think or not, just saying we
| have new challenges before the Turing test.
| codedokode wrote:
| But humans failed to find an algorithmic solution for Go. All
| they could do is to throw a lot of data and get a bunch of
| coefficients without discovering underlying rules.
|
| Same with drawing images and understanding language: this is
| not solved yet.
|
| This is like showing an answer on an exam but failing to
| explain how you got it. I doubt you can get away with this.
| 317070 wrote:
| Wait, we know the underlying rules, we have an explanation.
| You can read all the coefficients.
|
| We don't understand the explanation, though it is correct.
| Not sure if the problem here is with the capabilities of
| the examinee or with the examiner.
| codedokode wrote:
| Imagine if you go to your work at the bank tomorrow and
| instead of a well documented, maintainable and formatted
| code see a gibberish. And your neural coworker tells you
| that it is just a problem with your capabilities if you
| cannot understand it. He just refactored it to improve
| performance. That's the situation with machine learning
| today.
| Jack000 wrote:
| The thing is, it's not gibberish. A sufficiently small
| language model can be understood by humans:
| https://twitter.com/karpathy/status/1645115622517542913
|
| The explanation is perfectly sensical, just too complex
| for humans to understand as the model scales up.
|
| The thing you're looking for - a reductive explanation of
| the weights of a ANN that's easy to fit in your head,
| does not exist. If it were simple enough to satisfy your
| demands, it wouldn't work at all.
| pixl97 wrote:
| Banks don't typically attempt to solve P=NP problems.
|
| Meanwhile things like stock markets attempt to with
| things like partial future prediction, which means all
| possible outcomes are not calculable in finite time,
| hence they use things like ML/AI.
| stefs wrote:
| i'm not sure i understand you there.
|
| > But humans failed to find an algorithmic solution for Go.
|
| sure we have algorithmic solutions for go, they're just not
| very good.
|
| > All they could do is to throw a lot of data and get a
| bunch of coefficients without discovering underlying rules.
|
| that's not completely true either, the special thing about
| ~alphago~ alphazero* was that it learned by playing itself
| instead of learning from a pre-recorded catalog of human
| games (which is the reason for its - for humans - peculiar
| playstyle).
|
| now i'm not sure how you're arguing a neural network
| trained to play go doesn't understand the "underlying
| rules" of the game. to the contrary, it doesn't understand
| ANYTHING BUT the underlying rules.
|
| explaining why you did something isn't always easy for a
| human either. most times they couldn't say anything more
| concrete than "well it's obviously the best move according
| to my experience" without just making stuff up.
|
| *edit: mixed up alphago and alphazero
| codedokode wrote:
| By "underlying rules" I meant not rules of Go, but a
| detailed, commented algorithm that can win against human.
| Not a bunch of weights without any explanation.
| wslh wrote:
| It is possible that there is no algorithm that is
| understandable by normal humans or humans at all in the
| sense of the typical algorithmic approach of quick sort,
| etc.
|
| In other words, the algorithm is very long for a
| relatively reduced programming language.
| wslh wrote:
| Well, we humans also failed to find an algorithmic solution
| for our brain playing Go. I mean, the way AI and our brain
| work are mysterious. Surely at different level/layers but
| both share the mistery.
| reducesuffering wrote:
| Not only has GPT4 passed an elementary school science test,
| it is outperforming on tests better than 95% of the world. ht
| tps://twitter.com/emollick/status/1635700173946105856?lang...
| __loam wrote:
| I think this still holds some water. The go bot was excellent
| at beating really good go players because it had a ton of data
| on high level go games. When it encountered someone
| intentionally doing a moronic strategy, it was trounced. It
| just didn't have enough data on bad players, so it lost to an
| obviously flawed strategy.
|
| I think that's the huge flaw in all of these ml systems. They
| don't build fundamental understanding. We're brute forcing it
| in a way, but perhaps we're losing something in the long tail.
|
| E: https://arstechnica.com/information-
| technology/2022/11/new-g...
| joshfee wrote:
| This was a flaw in the original AlphaGo, but the subsequent
| AlphaZero (https://en.wikipedia.org/wiki/AlphaZero) trained
| entirely from self play with no prior information. So
| essentially it _does_ build fundamental understanding.
|
| I think the ability to learn by self play (essentially in a
| closed room without external training data) is where the line
| between "fundamental understanding" and "regurgitating
| information" from these AIs lie.
| og_kalu wrote:
| There isn't really any difference between self play and no
| self play in terms of "fundamental understanding" and
| "regurgitation". It's the same training scheme just with
| different data.
| white_beach wrote:
| more recently
| https://www.science.org/doi/10.1126/sciadv.adg3256
| taneq wrote:
| Will Smith's memorable character in I, Robot: Can you compose a
| symphony? Can you turn a blank canvas into a masterpiece?
|
| Sonny: Uh... yes?
| markwkw wrote:
| Sonny: Yes! Rapidly and repeatedly. [then add the actual
| quote:] Can _you_?
|
| Human: ...
|
| Oh how the tables have turned.
| beepbooptheory wrote:
| 2/4 (generously) is not bad for 7 years! And its not like we
| are ever going to get to 4/4... I give it a C- minus on the
| Evergreen Scale.
| david927 wrote:
| An artist's work based on Move 37:
|
| https://9f765bbf23b9b8d6bfe4-3415b861f2c980c0332d9442f10f87d...
| carabiner wrote:
| Honestly that's pretty bad.
| yawboakye wrote:
| i recently watched a video where chess grandmaster magnus carlsen
| seemed to be extremely adept at recalling previous games played
| by previous master. prima facie it appears he's the most advanced
| at recalling and computing potential future moves (in parallel).
| that seems to be something computers will definitely beat you at.
| especially given that chess (and most rules, move-based games)
| are path dependent, aka the space closes down quickly aka moves
| towards the end are more critical than at start of the game.
| Upvoter33 wrote:
| In one release, OpenAI made all the people at DeepMind feel
| forgotten about
| dyoo1979 wrote:
| I'm sure the folks working on protein folding are losing sleep
| over role-playing chatbots.
| ComplexSystems wrote:
| Can someone explained the move it made and why it was such a
| great move?
| mensetmanusman wrote:
| The Alphago move seemed like a bad move to humans but then
| ended up being amazing many steps later.
|
| The human move seemed like an incredibly improbable move by
| Alphago, and ended up giving the human an upper hand.
| jchoksi wrote:
| A winning strategy against the AI that Ender Wiggin could have
| thought off and executed would be:
|
| 1. The human has to play perfectly. 2. The human has to play
| perfectly and quickly.
|
| The premise being that an AI with less time to calculate its
| moves could result in an advantage to the human.
|
| https://en.wikipedia.org/wiki/Time_control#Byo-yomi
| bitshiftfaced wrote:
| My favorite part of watching the match was how the computer
| tripped everybody up with its endgame. It would have a large
| lead, but slowly it would concede one point after another, which
| no human would do. At some point someone explained that it does
| this because its goal is not to win by a large margin but instead
| to win by any margin no matter how low but with maximum
| probability.
| pixl97 wrote:
| "In the last days of humanity we came to the bitter realization
| that there had never been any chance of winning against the
| machines. We thought we were just one breakthrough away from
| winning at any time, one brilliant inspiration and we would
| win. And that's when we realized how truly evil the machines
| were, they let us have hope where there was none"
| radford-neal wrote:
| The commenters here saying "humans cannot win anymore", "there is
| no chance that humans can beat the best Go AI anymore" are
| apparently unaware that _this is no longer true_.
|
| See https://arxiv.org/abs/2211.00241 and https://goattack.far.ai/
|
| The best Go programs have a flaw that allows a good, but not
| championship-level, human to defeat them, by creating a group
| that encircles another group, which apparently confuses the AI's
| method of counting "liberties", which determine whether the group
| lives or not.
|
| Some appear to dismiss this as just a "trick", but it seems to me
| to point to a more fundamental deficiency in the architecture or
| training method.
| Recursing wrote:
| Afaik this is already mitigated in the newest KataGo networks,
| and Chinese engines are much stronger and plausibly don't have
| this issue. Also, if I remember correctly, that attack only
| works on KataGo because the weights are public, so it would not
| work against the strongest closed-source engines.
|
| They achieved a <10% win rate against other engines
| https://goattack.far.ai/transfer#contents, so the strategy is
| not that generic. Edit: actually it was 66% against another
| bot, https://goattack.far.ai/human-evaluation#human_vs_lz4096
| but they had to bring the visits down to 4096, which I assume
| means that at a "normal" visit count the bot would still win.
|
| Still, that paper is extremely interesting, consistently
| triggering suicidal behaviour in a super-human bot.
| roenxi wrote:
| Although technically correct (the best kind), that is a weak
| point. In a more formal sense, "playing" a 2 player game means
| something like approximating the move in a game between 2 min-
| maxing oracles. Humans can't do that anywhere near as well as
| KataGo.
|
| A human can, technically, beat a superhuman Go AI. But the
| process is clearly playing the opponent rather than the game,
| the moves are obvious weak moves. Humans aren't winning by
| playing good moves, the challenge being posed to the AIs isn't
| intimidating at all and they will defend against it sooner or
| later.
___________________________________________________________________
(page generated 2023-11-17 23:01 UTC)