I'll risk assumption that somebody from Deepmind team is reading this.

Guys, please, publish charts of win prob estimated by alpha go in time during these games. Some heatmap telling which moves did it consider as best for both sides during the games would also be cool, but that's surely more time consuming to prepare.

It would be great to be able to have such things for top pro tournaments in the future.

Actually, it's a tradition that both Players should replay the game after the match, discuss about good moves, bad moves and what they were thinking during the match.

I felt so sorry for Lee Sedol when I saw him lose the second match, facing an empty chair ,and he could only ask one of his friend to review the game.

https://zh.wikipedia.org/wiki/%E5%A4%8D%E7%9B%98

Or the helpless look of Aja Huang... like "I have no idea how to decipher that neural network, that's part of why you are here".

He made $30k for losing that game, so I don't feel too sorry for him.

If it really was about money, I don't think he would have spent so much of his life dedicated to Go ...

yeah, not to belabor it, but if you can do something like be a champion in go or chess, chances are you have the mental skillset to do something exponentially more lucrative.

This is not true. Scientific studies have shown that skills in abstract strategy games are so specific to the game that they do not transfer to other tasks. The urban legend about Chess grandmasters all being geniuses is false, in other words. They're actually worse at most jobs than people who've been doing those jobs for awhile, because they lack the experience, and they aren't more predisposed to having a genius intellect that would let them overcome that.

A Chess or Go champion is probably doing the single-most lucrative activity that they are capable of.

What scientific studies are you referring to?

Of course chess grandmasters aren't all-around geniuses, but many traits that are prerequisites for a successful chess player certainly are translatable into careers in other fields, and correlate with above average brainpower (good memory, discipline, long attention span, spatial intelligence etc.)

Botvinnik was an accomplished engineer, Euwe had PhD in mathematics, Anatoly Karpov is a millionaire, interestingly enough a lot of recognized chess players had careers in music (like Taimanov or Smyslov)...

Being a grandmaster surely requires an above average intellect, there is no such thing as a chess savant. While it's an urban legend that Kasparov's (arguably the greatest chess player ever) IQ was in the ballpark of 190, he did clock at 135. Such a result is not unheard of, yet still placing him in top 1% or so.

There's a whole body of research out there, but I just scratched the surface of it. Here's the first result that's coming up from a random Google search. https://psy.fsu.edu/faculty/ericsson/ericsson.exp.perf.html The references should be worth exploring, and I bet there's more recent research that expands on it as well. Here's a quote from the paper:

> In a recent review, Ericsson and Lehmann (1996) found that (1) measures of general basic capacities do not predict success in a domain, (2) the superior performance of experts is often very domain specific and transfer outside their narrow area of expertise is surprisingly limited and (3) systematic differences between experts and less proficient individuals nearly always reflect attributes acquired by the experts during their lengthy training.

I will say this for Chess or Go grandmasters: They have drive and dedication (and in some cases, compulsiveness). That alone would probably allow them to do better than the average person in another field if they had pursued that field from the get-go. Also, I'd caution you against relying on hand-picked anecdotes; I could just as easily pick out a bunch of Chess players who weren't good for anything else. You'd need broad-based statistics.

You seem to be confusing two different claims:

1. A champion Go/Chess player could retire, and jump a successful career as <Something else>. You refute 1.

2. A champion Go/Chess player could have pursued a career in <Something else> from the start and made more money. You have not refuted 2.

For an example, many physics PhDs become successful software engineers and quants, making a mid-career jump to a different field.

Thanks for the link. Well, of course I just quoted a few examples without pretending it's legitimate piece of statistics, however, there hasn't been all that many world chess champions so far (and Botvinnik, Smyslov, Euwe, Karpov, belong in that category), and thus a few PhDs or successful intellectual careers is already enough to show that something clearly sets this bunch apart from the general public. You're less likely to find a plumber or a shelf-stacker in that bus (no disrespect for people in these professions). Whatever causes that is another matter. I agree with you that drive and dedication - and not necessarily some innate talents - could be the crucial factor in this.

I'm not sure you're disagreeing with the person you're responding to. Just because the skills involved are very specific doesn't imply that the people with those skills only are capable of obtaining said skill.

What the person you're responding to means is that if they have the mental capacity (and also discipline) to play the game at such a high level, they could probably also excel in other professions if their goal was to make money instead of doing something they loved.

Of course we can debate whether they would achieve such success if they were doing something they didn't enjoy as much, but I think most people would argue that most chess or go champions could make more money or in other words do more "lucrative" activities if they chose to do them instead of dedicated all their time to the game.

You are relying too much on the concept of a generalized mental capacity, which many researchers (maybe even most) would say does not exist. You seem to be assuming that grandmasters are just amazingly smart and they happen to apply those smarts to one particular skill, but what's closer to the truth is that they happen to be particularly amazing at that one skill, in a way that doesn't really correlate strongly with having amazingly high skill in other areas.

If you took the people who would have grown up to be chess grandmasters, intercepted them just before they started spending significant amounts of time studying chess, and had them instead spend all that time studying programming or physics or something, how do you think they would rank up?

You seem to be arguing against the idea, "A chess grandmaster is a genius and therefore can walk into Google and immediately start doing more and better work than most of their senior programmers". I don't think anyone believes this (correct me if I'm wrong).

I think a more serious idea is, "A chess grandmaster is a genius and therefore learns faster and has a higher performance ceiling and such than most people, and if they spent a couple of years learning to program, they could become an entry-level Google programmer, after which they would rise more quickly than most hires, and eventually would outperform most of Google's senior programmers."

By the way, I think most of the best chess players were extreme chess prodigies. (Just looked at Kasparov, Karpov, Shirov, Kramnik, Anand, and Carlsen's Wiki pages; all but Kramnik had the year listed, and they all became grandmasters around age 17-19, except Carlsen, who was around 14. Kramnik's page mentioned winning a gold medal for the Russian team at age 16, and that he wasn't a grandmaster when selected for the team and this was unusual.) I think this is consistent with them being highly gifted children, who choose to spend their time doing chess.

>I don't think anyone believes this (correct me if I'm wrong).

While not exactly what you wrote, people do think that someone is a genius at some subject can become a genius at another area with less work than it took for someone in either field to originally become a genius at that field, especially society groups the areas together (so sports star becoming master programmer is far less likely to be believed than chess master becoming master programmer).

But what about https://en.wikipedia.org/wiki/G_factor_(psychometrics)?

> Scientific studies have shown that skills in abstract strategy games are so specific to the game that they do not transfer to other tasks

Do you have a reference for that please? I'm interested in the subject.

Though being able to compel yourself to do great things seems like a completely different skill set from being able to do great things on someone else's dime or on a team.

For example, my brilliant programmer friend that can't hold a job. Or the artist that can only paint their own inspirations. Or the savant that doesn't get along with anybody.

I dunno, Bobby Fischer was kinda deranged, for instance, and that often hurts outcomes in otherwise "lucrative" positions. Incidentally, he is credited with raising chess player compensation through his demands.

Generally I'd guess you're right though.

Maybe not a leadership position but I've worked on the engineering side of quant work and am familiar enough with fairly advanced Go / Chess players (e.g. national youth champions for age brackets for the US) to know that most of them could make enough to retire off one years salary during the boom years of algorithmic trading (~2003-2007ish).

I'm not sure how you define "deranged" (AFAIK, that's not a medically defined term within the DSM-IV) but most of those brilliant people end up being a little 'off'. My father was an academic, one of the people he went to graduate school with was working in Boston while I was a child. He was absolutely groundbreaking work but he's so difficult to collaborate with (think: the mannerisms of Richard Stallman) that he's been floating around universities until his welcome is worn out. He can figure out remarkable things in higher level computational chemistry, but he can't really figure out humans. Had he decided instead during the 80s to work at Renaissance instead of pursuing academic research, he almost certainly would be worth in the low hundreds of millions.

Well, mental issues did break his chess career just the same.

With the number of tournaments he has won (many of which have a winner's purse of <$100 000) I suspect he is already a millionaire.

Those are the big tournaments -- do the little tournaments stack up, or is it a year of practice leading up to an annual big win?

I can not find it using google, but there was a Go champion who had stop playing go during one year to earn money playing mah jong.

False dichotomy? It is quite possible to enjoy an activity and gain money at the same time.

The best (like absolute best) football|basketball|baseball players in the world make approximately what per game?

Well, defensive end Olivier Vernon just signed a deal with the New York Giants which will pay him an average annual salary of around 17 million dollars. And there was a huge signing bonus as well.[1]

NFL seasons are 16 regular season games, plus 4 pre-season games. And then there are the playoffs, which a given team might or might not make or advance in.

All told, given that the signing bonus is amortized over all the games he plays, the annual salary, etc., I think it would be fair to say that Vernon will make around a million dollars a game.

Aside: Vernon isn't necessarily "the best" DE in the NFL, but due to market forces and the way things work with the salary cap, free agency rules, etc., the contract he just signed is one of the largest for a defensive player in the league. QB's tend to make even more, but I can't recall a really high profile QB who has signed a big deal recently.

[1]: http://www.spotrac.com/nfl/new-york-giants/olivier-vernon/

Osweiler QB from the Broncos just signed a huge deal with the Texans...$18mil/year but I haven't heard how much of that is guaranteed so I'm sure.

A really big issue with NFL contracts is this "guaranteed money" thing...I believe the NFL is the only major US sports league who give player contracts without it, so you have to take those salary numbers with a grain of salt.

34 guaranteed over first two years

Football is kind of an oddcase since it the most popular sport in the richest country, and it runs very few games per year.

Best is around 10x that, but at the cost of their body and long term health. Nobody is playing professional football|basketball|baseball in there 50's, and even just 40 is pushing it. Where pro go players can 60+.

Gordie Howe played in the NHL until he was 53.[1]

Not really refuting your statement, which is essentially true, but it's worth your time to read the wikipedia page.

He played on a professional hockey team with his two adult sons at one point(!). He played in the NHL in five different decades.

[1] https://en.wikipedia.org/wiki/Gordie_Howe

Yep, it's interesting to see a few edge cases out there. There are a tiny number of people that came close to 50 in baseball:basketball:football.

  Julio Franco played baseball till 49.
  George Blanda played football till 48
  Nat Hickey played baseball till 45.

Interestingly, the world champions seem rather young.

If as many people who pay to watch (NFL|NBA|MLB) paid to watch Go, you'd likely see similar payouts.

I would like to see AlphaGo play 21 against Steph Curry.

I.e. Something like [1] for every move. I was a bit disappointed to learn that such table is only available for that particluar move at the first reading.

[1] http://www.nature.com/nature/journal/v529/n7587/fig_tab/natu...

Off-topic: we (the human species) have built an AI that can master the game of Go, but we don't yet have the intelligence to publish charts correctly on the web. That blur of a JPG is half a megabyte!

Yeah honestly that would be much better presented as an SVG since its mostly solid colors and geometric shapes. Every browsers supports them, and all the big image editors as well; the trouble is that the rest of our software and culture hasn't caught on. Why am I taking bitmap screenshots of websites when they're almost completely text? We need to start building a tools ecosystem around vector graphics. An extra bonus would be a machine-readable representation of the board as well. We live in a digital age, but its almost like we're cavemen still dealing with the modern equivalent of analog formats. (And at least analog has fidelity)

Screenshots might not be the best example, since there may be some "shiny cute effects" going around. However, reading your idea sprang another one in my head: screenshots shouldn't be restrained to the same rendering resolution as the rest of the system/the screenshot resolution should be configurable.

I don't require the screenshot to be instantaneous, I require it to appear instantaneous. In that sense, if the whole rendering pipeline is working to give me a framerate of 60 fps, then I could spend ten times as much rendering a screenshot without that delay being noticeable. Also, why on earth does Windows (don't know the behaviour on Linux/Mac) apply ClearType to a screenshot? That has always bugged me, there are some situations where you tolerate it and others where it hurts.

It didn't master anything. What the DeepMind team did was make an "AI" which means it can _imitate_ (to a certain degree) of "playing go".

What's the difference between "imitating" playing go and playing go, when it can beat any one us at go?

That would be awesome.

"Do not anthropomorphise computers. They really hate that" (NN)

By NN you mean a neural network, of course? That makes even more sense...

NN = nomen nescio ("I don't know the name") You use it when you cannot name the source of a quote, or when you would like to protect the source.

https://en.wikipedia.org/wiki/Nomen_nescio

Wouldn't "-Unknown" convey the same sense without the possible confusion?

I think this conveys a slightly different meaning.

When I see "-Unknown", I interpret it as "somebody said it, but no one is quite sure who".

"(NN)" in the current thread was used to indicate "I personally don't know", which does not imply the quote is unattributable.

NN is (was) also used in neapolitan comedy, derived from earlier use throughout the Roman Empire and Middle Age. The "figlio di NN", or "son of NN" means someone who was found and adopted (typically by nuns) and whose parents were unknown.

NN can be used in general for people whose origin is uncertain. I think in this specific case it's a bit misleading - although the wikipedia article seems to suggest that NN can also be used as a synonym for "unknown", although from a historical perspective it is a bit incorrect.

The literal translation from Latin creates some confusion if you didn't know the context.

I hope this helps.

So NN can be used as an school version of anonymous?

... wrote the bot trying to hide its identity

Using the acronym of the phrase defeats the purpose, though, since it looks like someone's initials.

Or Netochka Nezvanova? https://en.wikipedia.org/wiki/Netochka_Nezvanova

Not so coincidentally, "This was when things got weird. From 87 to 101 AlphaGo made a series of very bad moves." [1]

The bad moves in the eyes of humans could be risky bets or the horizon effect. [1] [2] AlphaGo's use of deep neural nets (value networks) to evaluate board positions should significantly help counter the horizon effect, but since move 78 by Lee Sedol which turned the situation around was unexpected by some top pros (Gu Li referred to it as the 'hand of god' [1]), the patterns which follow are likely rare in possible game states and therefore not strongly embedded into the value networks, leading to AlphaGo's loss.

I hope the DeepMind team will help enlighten us on this in the near future.

[1] https://gogameguru.com/lee-sedol-defeats-alphago-masterful-c...

[2] https://en.m.wikipedia.org/wiki/Horizon_effect

78 was hard, but not impossible: If you watch the AGA commentary of the game, they had two pros at the time 78 happened, and they found 78 as the best answer a few minutes before Lee did, expecting AlphaGo to go with a stronger, yet still good not good enough 79, that left the game even, instead of basically lost. Then they were elated about how AlphaGo seemed to have failed to read the whole thing, and instead of doing preparatory moves for a nasty ko fight, the best option at the time, AlphaGo just took a route that provided almost no compensation.

If anything, it seems to me that AlphaGo's problem here might be the time management: Seeing a really scary situation, Lee Seido just sank many minutes into reading the problem, going pretty much all the way to byoyomi time. A human, after seeing something like that, would figure out that their assessment of the situation and their opponent's is very different, and spend a lot of budget trying to figure out what was wrong. AlphaGo just didn't see the problem, and didn't just budgets its time to analyze the position to death. It moved slower than before, but not really that much, and ended up making moves a kyu player could see as terrible.

Either way, I'd love to see Deepmind giving us all a good postmortem of the 70-100 range of moves.

I concur that better time management may have made a difference.

Beyond that, I think that AlphaGo may still be missing a type of component. From the descriptions of it, the policy network generates possible moves from board positions, and the value network evaluates the probability of desirable outcomes. How this is different than human play is that strategic assessment and planning are implicit in the middle layers rather than a 'conscious' element to searching and decision making. I'm not saying that this is a necessary component as AlphaGo has already done exceptionally well. I do believe this kind of 'middle-out' processing producing and evaluating strategic concepts could make it better handle unusual circumstances. Being trained on high amateur and pro games, it will best respond to the most conventional of those types of games, more unconventional the game becomes, the worse it would fare in terms of efficiency of move generation and choices of which to evaluate.

I got something different from the AGA commentary. The pros did consider 78, but came to the conclusion that it didn't work! I'm just a 1kyu player but I too can't see any way to make 78 work after Black plays 79 as an atari at L10, as suggested by the pros. So I'd be very interested to see some analysis that shows how White could get a fair result after Black 79 at L10.

It would be interesting to see a neural net evolve to take into account player state, not just game state. I play chess, and no where near professional levels, so I don't know if this anecdote is valuable, but if I see my opponent looking at a particular area of the board, I tend to take a second look.

I suppose beating humans isn't AlphaGo's primary motive though - learning to play a perfect game of Go in general is probably more difficult than playing the perfect game against a particular person.

Having the AI use eye-tracking to predict an opponent's moves is a truly terrifying thought. Just by tracking the eye with millisecond precision you could probably work out the strategy they were reading. It's so game-breaking that it shouldn't be allowed as an input, and indeed, is easily defeated with reflective sunglasses anyway (like a lot of pro Poker players wear).

The AI player can't give up information in this manner because it lacks eyes, so I'd say that it should not be able to use this information from the human player.

Seems like just another avenue to trick the computer

This actually came up in the commentary. Michael Redmond actually mentioned that some amateurs watch to see where their opponent is looking, but he called it merely a "trick", and he said it is not useful in professional play.

That type of metagame seems useful though, in the sense that you can start to sense the state of mind of your opponent. If they are working harder than you think they need to, you might get away with a riskier move for instance.

Just in case someone wants the commentary around this move 78

https://www.youtube.com/watch?v=yCALyQRN3hw&t=11413

Here's the Myungwan Kim commentary around that same move: https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h33m. He had been looking with Hajin Lee at variations involving the move beforehand (https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h28m1s), so he immediately noticed that AlphaGo made a possible error in its response.

But Kim also jumped a bit backwards and forward for a few moves, until he finally decided it was a mistake. It didn't seem 100% clear.

Professionals are understandably hesitant to call AlphaGo's plays mistakes after the first few games, because AlphaGo had played a few moves that seemed like obvious mistakes (the eyestealing tesuji under the avalanche and the fifth line shoulder hit) but later proved to be very strong moves. Remember that when go is your career, your reputation is based partly on your ability to analyze games accurately, so calling a move a mistake and finding out later that it was strong would be a big embarrassment.

Any chance of explaining the mistake on move 79 to someone who's only played a few casual games of Go?

AlphaGo enlarged a group that was at risk of atari (loss to opponent) instead of correctly trying to divert attention to elsewhere on the board or starting a new fight or simply writing it off. If basically added stones to a group that was almost certainly dead and allowed the opponent to punish it heavily, thus giving away more stones than it had to.

OT: What's with using monotype for quotes? That's breaks line wrapping and makes it hard to read on mobile or small screens. I don't get why people do it.

"People" don't do it; HN does it. Indented lines in a post are always monospaced, on the assumption, I suppose, that they're likely to be code examples. There's no way to turn this off AFAIK.

And no, HN does not use Markdown.

I know the formatting system. My question is why the users are formatting their text (e.g. with 4 places leading each line) *suc that HN renders it as monospace, which then forces a sideways scroll on mobile and small screens. That seems to make it harder to read for some with no corresponding upside.

Oh. Well, I think they just don't realize that HN will monospace it.

I agree with you, it's annoying.

They don't realize it even after seeing their post go live? And seeing what other people's monotype quotes look like?

I never like to assume malice, but ...

The people indent the text (or fail to remove the leading white space when copying).

It isn't a huge time sink to wrap a paragraph in stars.

I think mostly people forget that > works and that therefore you can do

> quotes like this

since it's markdown - often you get commentish things that allow limited HTML plus indented code blocks, and people get used to using the latter as the only thing that works everywhere

'>' doesn't "work"; it doesn't do anything on HN. It's just a convention that readers recognize as indicating quotation.

HN does not use Markdown.

At least ">" doesn't break anything.

    Pre is broken on mobile, forcing users to scroll a horizontal line which is incredibly annoying if it's a long line.

Here's a screen shot: http://imgur.com/Ru56wMK

And pre with very long unbroken lines is even worse.

I wasn't expressing a value judgment, just trying to explain how HN works.

I agree with you that it's annoying when people post long indented lines.

it can be touch-scrolled here, there just aren't scroll bars. Took me a while to find, but maybe your browser is buggy, eve.

I noticed people were doing this and wrote a userscript a while ago to make it work. I kind of wish HN supported it.

https://gist.github.com/kennethrapp/7a21c0187fedd6f47e7c

I wrote in a while ago to ask that it be officially supported, but apparently that would break something that HN's spam filter relies on.

Looks good in desktop browsers.

not really: http://i.imgur.com/uxqERat.png (you have to be very careful about what indentation level you're at, how long your lines are, etc, etc, things that people just don't do most of the time)

It's also customary when quoting large sections of text. I'm not sure if this carried over from email, or from academic texts (where if your quote is more than a line or two, it needs to be formatted differently).

I think mostly people forget that > works and that therefore you can do

> q

How frigging smart Sedol is?

Kind of cool to know you're as smart as algorithms that require 1920 CPUs and 280 GPUs

They've said it doesn't require that, AlphaGo running on a single machine beats the cluster they're using 25% of the time.

So based on current data, Lee Sedol is exactly as good AlphaGo running on a single machine.

Doubtful; I don't think comparing such small W/L distributions will be illustrative.

On the other hand, the Nature paper shows the single 8 GPU machine performs similar to the 64 GPU cluster, but the larger clusters perform a comfortable margin better. [0]

By a single machine winning many games relative to the distributed version, really it's just saying that the value/policy network is more important than the monte carlo tree search. The main difference is the number of tree search evaluations you can do; it doesn't seem like they have a more sophisticated model in the parallel version. The figure suggests that there are systematic mistakes that the single 8 GPU machine makes compared to the distributed 280 GPU machine, but MCTS can smooth some of the individual mistakes over a bit.

[0] http://www.milesbrundage.com/uploads/2/1/6/8/21681226/877172...

Probably better. If we assume a uniform distribution across possible win rates of Sedol vs AlphaGo, then update it with bayes rule, we get 33% chance that Sedol will win the next match.

That's not factoring in other information, like Sedol now being familiar with alphaGo's strategies and improving his own strategies against it.

So there is a good chance he is now evenly matched with AlphaGo, and likely much better than the single machine version.

There's a bit of a slight of hand in this statistic -- yes, they can do runtime on a single machine, but it took the compute power of a small country to train the neural nets that are loaded onto that one machine.

That's not really sleight of hand. Lots of things take more energy to produce than to run. It's like saying a 400W electric motor can put out as much power as a fairly fit human, but it's 'sleight of hand' because it took a whole factory to make the motor.

And it took decades of play for Sedol to become a top player. I find the similarities a mix of satisfying and amusing.

You're conveniently forgetting that this "AI" is a representation of tens of millions of amateur plays which is far more than a few decades in total time. Not that Lee Sedol needs someone like me to defend him, but remarks like yours are very misleading.

A human is far, far, leagues, more efficient at learning than today's AIs. These AI requires millions of hours of man time of data to even come close to competing at the level of an expert person which did the same, and even arguably far better, in a "few decades".

Even on a single machine it has the "memory" of virtually any Go game AlphaGo could be fed.

If you look at DeepMind's numbers, AlphaGo is meant to win more than 50% of the time against human players (expert). Right now, my opinion is that its actual capability in wins is less than 50%.

We're in the very infancy of the field though. Give it a year and it's likely you'll have a neural-net-based Go program that runs on a single machine that can defeat every single human professional. Human Go players have been getting better for millennia; don't assume that a program that's only two years old has no room for improvement left.

It took some serious hardware for Deep Blue to defeat Garry Kasparov. Now there are smartphone apps with that same level of Chess-playing skill. And if anything the AlphaGo approach is more amenable to running on lower-specced hardware without requiring help from Moore's Law (because you simply train it better).

It is believed now that Lee Sedol has a really good ability in reading AlphaGo's moves now (see: Micheal Redmond and AGA Game 4 commentary). Game 5 is going to be very interesting. I'm pretty sure the DeepMind team is just as excited. After game 4, they were noticeably far more ecstatic in the after-game press review.

Hassabis and Silver kind of reminded me of developers given the details of a bug that was notoriously difficult to find.

edit; I can't wait for the reviews of the entire 5 game series. If a book came out I'd very likely buy it. A book discussing both Go and AlphaGo AI at the same time consisting of people among the top of their respective fields would be amazing.

I wish some of these had been re-tweeted by the @DeepMindAI account. I'll definitely be keeping an eye on Demis' account during game 5.

It feels really weird to see someone being showered with congratulations for beating a computer program. What exactly is he being congratulated for? For probably triggering and then capitalizing on a bug in AlphaGo's AI? For showing that human resolve, perseverance and a "fighting spirit" can trump a flawed AI, at least until the AI gets fixed? For giving DeepMind extremely valuable test data that will only accelerate the refinement of AlphaGo's AI? For helping to advance an amoral field of study that can potentially delegitimize everything that currently makes humans unique and extraordinary?

As noted by the live commentator, this has the opportunity to be the third revolution of the game of Go, opening again new ways of playing for the whole of humanity.

Imagine what AI, in different fields, means for humanity if it has so much to teach us, just by being able to "think" differently. I sure hope that one day they start writing philosophy and, doing so, potentially legitimize everything that currently makes humans unique and extraordinary.

What are the other two revolutions of game of Go?

cf post game 3 conference commentary : https://youtu.be/qUAmTYHEyM8?t=20639

(also during the actual game with more details, but I can not find the exact time again). Edit : can not find game3 commentary but during game 4 he is coming back to it again with interesting details as for why this is a great opportunity to inspire human players : https://youtu.be/yCALyQRN3hw?t=7097

Basically, once in ancient Japan and more recently a Chinese origin player in Japan, both incredibly strong players, surprised everyone with never before seen moves that subsequently where integrated in modern game theory. The hope is that the same could happen here.

a computer that loves wisdom?

Perhaps you'd like a shot at explaining why AI is an "amoral field of study", and why it could "delegitimize everything that currently makes humans unique and extraordinary"?

Dolphins are about as intelligent as us, too. Are dolphins amoral? Do they delegitimize Beethoven, Tesla, Gödel, Einstein, and da Vinci?

> Dolphins are about as intelligent as us, too. Are dolphins amoral? Do they delegitimize Beethoven, Tesla, Gödel, Einstein, and da Vinci?

If we invented dolphins, and they began to replace and displace us, then maybe? I don't think it is about the intelligence, but in how we use it of course. Dolphins don't really have any control of my life or those around me.

That sounded a lot more paranoid than I meant, I actually agree with what I think you are saying

> Dolphins are about as intelligent as us, too

How are you making this comparison?

I think Bud wanted to make a different point. Ie that AI doesn't delegitimize us---whatever that even means. Dolphins were just an example. He could have used Neanderthals, or Aliens.

Dolphins definitely delegitimize Beethoven.

/s

Not really related, but dolphins are assholes!

http://www.deepseanews.com/2013/02/10-reasons-why-dolphins-a...

Frankly many pre-modern, pre-civilizarion humans were assholes. Read many studies or accounts of life in relatively isolated tribal societies and hair curlingy awful accounts of violent and sometimes institutionalised abuse are uncomfortably common. Leave the safety catches off basic human urges for long and it can get pretty ugly.

> Frankly many pre-modern, pre-civilizarion humans were assholes.

While it's somewhat news to me, I'm very glad to hear we've moved past that.

I hope that was irony.

Very much so. Many modern, "civilized" humans are assholes, and now we've got global audiences for it!

See https://en.wikipedia.org/wiki/The_Better_Angels_of_Our_Natur...

Yes, I know, it's just completely insane to declare that we've somehow qualitatively moved past our brutish origins as long as torture, rape, and murder remain de facto extensions to politics.

I have no reason to doubt that quantitatively we have made some progress - although Pinker's arguments are most definitely not universally accepted in the scientific community.

Lee Sedol will forever be known as the first human to defeat AlphaGo in Game 4, and potentially the last one too.

That's quite an accomplishment.

Maybe they should fork version 18 as the hard but human betable version of alphago

How about just for playing a good game of Go?

So I suppose the fact that the opponent is a computer program should not be factored into the reaction to Sedol's win at all.

I hope your reductionist explanation is not accurate because it would imply that we are already so highly conditioned to machines and to AI that this match is thought to be no different from a match between two humans.

The machine beat him 3 times and was more or less expected to win again. It didn't, which would imply that Sedol played an exceptionally good game. Seems pretty obvious to me.

You're acting like following arbitrary sets of rules to maximize a value function isn't something that computers excel at. The only thing that was holding up computers for Go was simply time; there were too many possibilities to consider. Humans are really, really good at heuristically trimming possibilities, but sometimes to the detriment of finding maxima.

You know that computers beating us at chess allowed us to get better at chess, right?

Fan Hui, the professional player they beat late last year, already improved his game by quite a bit from the occasional match with AlphaGo (deepmind hired him as a consultant to test). He's won every single game in the last European championship, and moved from around top 600th player in the world to around top 300.

Wow. I know nothing about go, but 600--->300 sounds like quite an improvement.

A quote by Lee Sedol from years ago (might be apocryphal, couldn't find the original source):

Q: We heard there's now an anti-Lee Sedol website in Korea?

A: I don't even have time for my fans. I don't care about haters. ("나를 좋아하는 팬들에게도 신경을 못 쓰는데 그들에겐 당연히 신경 끈다.")

>For helping to advance an amoral field of study that can potentially delegitimize everything that currently makes humans

Or, writing from the point of view of our mechanical successors to this world, for helping to advance a highly ethical field that could exterminate that genocidaly murderous evolutionary abomination that was the human race. Who incidentally thought they were extraordinary but couldn't even play Go.

I don't think this comment should be so shouted down. Besides the politeness that typically comes with these events, it does feel strange to congratulate, on top of normal politeness, Se-dol's victory.

And for a game that was thought to be many decades away in terms of computer capabilities, this probably should be a time to think of the possible consequences of AI improvement and take a close look at it.

I think (or at least hope) most of the downvotes have nothing to do with congratulations, and only refer to the part where AI is called "an amoral field of study that can potentially delegitimize everything that currently makes humans unique and extraordinary".

That line of reasoning would be worth a laugh, if it wasn't so widespread in the general population.

Perhaps still better than my friend, who thinks suffering is what makes humans special. Discussions with him are, well, interesting.

Maybe introduce your friend to buddhist ideas of ending suffering via meditation. Might be another interesting discussion.

I think Buddhism is where he got that idea from.

amoral

>Both have to do with right and wrong, but amoral means having no sense of either

Well that's true then! A nice quote is from Feynman in regards to scientific research.

"To every man is given the key to the gates of heaven; the same key opens the gates of hell. — Richard Feynman "

We really have no idea yet how this AI research will play out.

I don't quite like the line "Delegitimize all that makes people unique and special" But that's my only real disagreement.

If developments in AI can delegitimise human intelligence, then it was never "legitimate" in the first place (whatever that means).

>For giving DeepMind extremely valuable test data that will only accelerate the refinement of AlphaGo's AI?

You're treating Lee Seedol as if he is a fixed dataset to be trained on. Why can't he also be a "NN" who can also "refine" his AI[0] and thus be hearder for Alpha Go to compete with?

You're putting too much faith in the machine and dropping the person, that might not be completely fair.

[0] Albeit not artificial in this case.

> For helping to advance an amoral field of study that can potentially delegitimize everything that currently makes humans unique and extraordinary?

If you care about being unique and extraordinary more than about reason, knowledge, truth, the observable reality, and the search for what it really means to be sentient, then and only then you may call AI "amoral".

Also, you are being racist against artificial sentient beings, and being racist is hopefully not what makes humans extraordinary.

racist is, imo, a strange word to use there

Yes to all of the above, except the last.