AlphaGo beats the world champion Lee Sedol in first of five matches • Hacker News Board

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#401

Post by geebee » Wed, Mar 09, 2016, 6:14 PM UTC

cjbprime wrote: post #399

geebee wrote: post #387

Terrific accomplishment. Just a question to throw out there - does anyone feel like statements like this one "But the game [go] is far more complex than chess, and playing it requires a high level of feeling and intuition about an opponent’s next moves." … seem to show a lack of understanding of both go and chess? I understand there may be some cross-sports trash talking, but chess, played at a high level by humans ,…

No, I think the statement's approximately correct. Chess has an average branching factor of 35, Go has an average branching factor of 250, intuition is required to prune candidate moves in Go in a way that it is only extremely minimally required in Chess.

But is this true as humans play it? I'm not good enough at either to really know for sure, but my impression is that while the branching factor makes a big difference for computers, it is essentially impossible for a human to manage the branching in either game (massive numbers of branches vs exceptionally massive numbers of branches). As a result, humans play both games at a high level by relying on intuition.

For instance, I read a while back (approximating and paraphrasing to follow...) that top chess players can think up to 10 moves ahead along a very few branches. So let's say that in chess, there are 30 million possible positions to evaluate, and in go, there are 300 trillion. They're both such an order of magnitude different for humans that it makes really no difference in terms of how we play the game, so intuition takes over. For computers, it's a different story.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#402

Post by gjm11 » Wed, Mar 09, 2016, 6:14 PM UTC

stromgo wrote: post #348

gjm11 wrote: post #183

Earlier quoted context omitted.

Here's a way to measure the sophistication of a game of skill. Consider two players A and Z. A is a ten-year-old who has just been told the rules; Z is God. Now, in between them, put a series of other players B, ..., Y, where B beats A 2/3 of the time, C beats B 2/3 of the time, ..., Z beats Y 2/3 of the time. (We assume God doesn't use his magical divine powers to cheat by, e.g., making Y play bad moves.) Unfortunat…

> In go, beating someone 2/3 of the time corresponds to being about one kyu/dan rank stronger This isn't true. One kyu/dan rank stronger means being 1 stone stronger (so winning 50% of the time when playing White with reverse komi). In practice this may correspond to winning 2/3 of the time with normal komi for high dan players, but that doesn't hold for low kyu players. A 29k has maybe a 51% chance of winning agains…

Fair comment about very weak players. My impression is that the element of chance goes way down well before you get to high dan level, though. How sure are you that I'm wrong?

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#403

Post by hosh » Wed, Mar 09, 2016, 6:16 PM UTC

d0m wrote: post #398

hosh wrote: post #392

Earlier quoted context omitted.

And just to emphasize the big point here: The AlphaGo that beat the 2p European champion five months ago was not as strong as the AlphaGo that beat Lee Sedol (9p). I don't think this was just the AlphaGo team throwing more hardware. I think they had been constantly running the self-training during the intervening months so that AlphaGo was improving itself. If that is so, then the big thing here isn't that AlphaGo is…

I think it's fair to say that in the future, people will look back and wonder how it was possible to live without having a good AI.. similar to how we look past at caveman and wonder how they could live without electricity. AI is really just a tool that we leverage, the same was as we leveraged the wheel or electricity.

Yep. I was just talking with the founder of a startup I work with. His son was born in the past 5 months or so. The son is never going to live in a world that doesn't have deep learning. Like the kids who never knew what the world was like before the smartphone. Like the kids who never knew what the world was like before the web browser.

And AI is just one strand. There are several strands that are as deeply changing, that is happening simultaneously.

I remember someone speaking about the shift between classical hard sci fi and more current sci-fi authors like Neal Stephenson or Peter Hamilton. The classical authors like Heinlein or Asimov might do world building where they just change one thing. What would the world be like if that one thing changed? After a certain point though, things were changing so fast that later authors didn't do that. There were too many things that changed at the same time.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#404

Post by d0m » Wed, Mar 09, 2016, 6:16 PM UTC

geebee wrote: post #387

Terrific accomplishment. Just a question to throw out there - does anyone feel like statements like this one "But the game [go] is far more complex than chess, and playing it requires a high level of feeling and intuition about an opponent’s next moves." … seem to show a lack of understanding of both go and chess? I understand there may be some cross-sports trash talking, but chess, played at a high level by humans ,…

I know I will offend chess players by saying this but.. I feel like chess is more of a IQ contest, while Go is more Art-ish in how you move and slowly cripple and surround your opponent.

Realistically speaking, there aren't that many moves you can do in chess. Most of them are just blunder that would get you insta-killed by a good player. Contrast that to Go where there are so many good moves. This is why I think the Go AI is more impressive.

Part of me thinks that at some point in the future, we'll have Chess "solved". Not in a "That computer is too good for humans", but more in a mathematical sense where all avenues will have been explored and at any point you mathematically know from a position whether you 100% win. So, the computer will make a move, a second computer will make a move, and then they will agree on a draw. To be able to achieve this, I think it will be some kind of rainbow table for chess (on a much bigger scale obviously), where you can represent one position by a hash and just brute-force all possible solution from the "end-game" to the initial board. So, it's not even about AI, more about bruteforce and hardware. I know it's not possible to do this at the moment but quantum computing would be.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#405

Post by YeGoblynQueenne » Wed, Mar 09, 2016, 6:16 PM UTC

Eliezer wrote: post #75

simonh wrote: post #61

Earlier quoted context omitted.

Highly optimised single-function algorithms like this are impressive stuff and can lead to useful tools, but that's it. This gets us no closer to strong AI than a tic tac toe program. Until we have systems that can tackle a wide range of fundamentally different problems and independently adapt strategies for dealing with one class of problems to deal with other classes of problems, systems like Alphago will remain on…

In case you're not aware, AlphaGo's key component is based on the same type of Deepmind system that learned to play dozens of Atari games, to superhuman levels, by watching the pixels, without any programmatic adaptation to the particular Atari game. At least the version of AlphaGo that played in October was far less specialized for Go than Deep Blue was for chess. Demis Hassabis says that next up after this is getti…

>> In case you're not aware, AlphaGo's key component is based on the same type of Deepmind system that learned to play dozens of Atari games, to superhuman levels, by watching the pixels, without any programmatic adaptation to the particular Atari game.

The Atari-playing AI watched the pixels indeed, but it was also given a set of actions to choose from and more importantly, a reward representing the change in the game score.

That means it wasn't able to learn the significance of the score on its own, or to generalise from the significance of the changing score in one game, to another.

It also played Atari games, that _have_ scores, so it would have been completely useless in situations where there is no score, or a clear win/loss situation.

AlphaGo is also similarly specialised to play Go. As is machine learning in general: someone has to tell the algorithm what it needs to learn, either through data engineering, or reward functions etc. A general AI would learn what is important on its own, like humans do, so machine learning has not yet shown that it can develop into AGI.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#406

Post by d0m » Wed, Mar 09, 2016, 6:17 PM UTC

sago wrote: post #91

atemerev wrote: post #77

Earlier quoted context omitted.

The only remaining are language-related. Natural languages are the next focal point of AI research.

Skill related. I'd be interesting to see how quickly driving AIs take to beat the best human drivers, in a weight-equal vehicle. An algorithmic competitor in formula one, would be interesting.

I feel AI could take so much more risk if there's no lives in danger so that would give them an edge.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#407

Post by YeGoblynQueenne » Wed, Mar 09, 2016, 6:18 PM UTC

schoen wrote: post #386

YeGoblynQueenne wrote: post #377

Earlier quoted context omitted.

People have probably spent billions of dollars to find a cure for cancer, but there isn't one that works for all cancers and most are still very bad news. Say you spent a hundred billion dollars to extinguish the sun- that wouldn't work. How much money you spend is irrelevant when you're up against what people call "hard physical limits".

Isn't our inability to cure all cancers a limitation of our knowledge more than a hard physical limit? I've read several articles saying that different cancers are not exactly the same disease, but more like different diseases with the same symptom (uncontrolled tumor growth) and different etiology, even sometimes different from person to person, not just from tissue to tissue. This was said to be a reason that a gen…

>> there would need to be qualitative breakthroughs which aren't guaranteed to happen at any particular level of expenditure

Yep, that's my point, thanks. Sorry, I'm not in my most eloquent today :)

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#408

Post by aidenn0 » Wed, Mar 09, 2016, 6:23 PM UTC

geebee wrote: post #401

cjbprime wrote: post #399

Earlier quoted context omitted.

No, I think the statement's approximately correct. Chess has an average branching factor of 35, Go has an average branching factor of 250, intuition is required to prune candidate moves in Go in a way that it is only extremely minimally required in Chess.

But is this true as humans play it? I'm not good enough at either to really know for sure, but my impression is that while the branching factor makes a big difference for computers, it is essentially impossible for a human to manage the branching in either game (massive numbers of branches vs exceptionally massive numbers of branches). As a result, humans play both games at a high level by relying on intuition. For i…

The true branching number of chess is much smaller, as most moves are obviously bad.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#409

Post by gcr » Wed, Mar 09, 2016, 6:23 PM UTC

hosh wrote: post #370

sethbannon wrote: post #7

I was at the 2003 match of Garry Kasparov vs Deep Junior -- the strongest chess player of all time vs what was at that point the strongest chess playing computer in history. Kasparov drew that match, but it was clear it was the last stand of homo sapiens in the man vs machine chess battle. Back then, people took solace in the game of Go. Many boldly and confidently predicted we wouldn't see a computer beat the Go wor…

The 2003 match was a brute force approach. AlphaGo's architecture resembles much closer to how humans think and learn. I initially learned Go to be able to have some chance of an AI. I then had some transformative experiences that coincided with my early kyu learning of basic Go lessons. On of the big lessons in Go is to learn how to let go of something. Taking solace in anything on the Go board is one of the blocks…

This isn't about Moore's Law though. From the AlphaGo paper:

    > During the match against Fan Hui, AlphaGo evaluated thousands of times
    > fewer positions than Deep Blue did in its chess match against
    > Kasparov; compensating by selecting those positions more intelli-
    > gently, using the policy network, and evaluating them more precisely,
    > using the value network—an approach that is perhaps closer to how
    > humans play. Furthermore, while Deep Blue relied on a handcrafted
    > evaluation function, the neural networks of AlphaGo are trained
    > directly from gameplay purely through general-purpose supervised and
    > reinforcement learning methods

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#410

Post by SilasX » Wed, Mar 09, 2016, 6:24 PM UTC

afc wrote: post #284

sergiosgc wrote: post #267

Earlier quoted context omitted.

As solid as your argument may be, everyone saw arguments like this over and over. Every single time they were solid. For a time, it was the high frequency noise that would not be manageable (80s), then heat dissipation (90s), then limits on pipeline optimization (00s) and now size constraints on transistors. They were all hard barriers, deemed impossible and all were overcome. I already know that your answer will be:…

This looks like a good example of the Normalcy bias logical fallacy: https://en.wikipedia.org/wiki/Normalcy_bias That previous constraints have been beaten in no way supports the argument that we will beat the laws of physics this time.

It also looks like a fully general argument against anything new ever being accomplished.