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

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

#431
post #356
post #54

Earlier quoted context omitted.

As a person who knew only the basic rules beforehand, I wouldn't imagine it any better. Any more complicated and I'd get lost. I'd love to see one day a live commentary, with an extra window showing what computer is thinking at the moment.

Having worked on some code very similar to this, showing the computer's best moves would be quite artificial. Here's some thoughts as to why that is: 1. The computer can discard all its current best ideas and flip through new ones so fast, it would be a flickering blur to humans. 2. Even if we put a speed limit on it, the move being considered is itself the result of considering a lot of slight variations. 3. The abi…

I can back this up a bit. I created a strong Chess engine variant and had it visually show what the computer was considering as moves with strengths as color strength. It would even show what it considered your best counter-moves.

Even with all that thinking output on the screen, the computer would still soundly beat myself and another (intermediate) player.

Here are some screenshots to illustrate what I'm talking about:

http://fifthsigma.com/CoolStuff/DecachessThinking/

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

#432

The funny thing about AI at this scale is we don't really know why the computer does what it does. It's more of a inductive extrapolation that we can verify that a technique works for a small problem, so we'll throw a whole bunch of GPU power and data at it and it SHOULD work for a big problem. How it actually works is fuzzy though as there's just a couple of gigabytes of floats representing weights in neural network…

> No human can look at that and say: "Oh! I see why it made that move".

Well, it depends. During the game last night there were quite a few forced moves that require an immediate and unique reply. The motivation for the reply is quite clear. But that's the simple stuff.

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

#434
post #370

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…

Is the Monte Carlo approach specific to Go in terms of A.I. challenges? Or is the Monte Carlo approach gaining traction in other A.I. problems as well?

I am tremendously unfamiliar with recent A.I developments.

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

#435
post #186
post #35

Earlier quoted context omitted.

It's a proof-of-concept. What they've proved is that the same kind of intelligence required to play Go can be implemented with computer hardware. Before now, software couldn't beat a ranked human player at Go no matter how much computing power we threw at it . Now we can. Give it ten years and, between algorithmic optimizations and advances in processing, you'll have an unbeatable Go app on your phone.

> Give it ten years and, between algorithmic optimizations and advances in processing, you'll have an unbeatable Go app on your phone. I find this overly optimistic because of the huge amount of power required to run the Go application. Remember, we're getting closer and closer to the theoretical lower limit in the size of silicon chips, which is around 4nm (that's about a dozen silicon atoms). That's a 3-4x improvem…

I don't think you appreciate how much of this is good algorithms, and how little you need sheer computing power to get good results.

If you look at http://googleresearch.blogspot.com/2016/01/alphago-mastering... you'll find that Google's estimate of the strength difference between the full distributed system and their trained system on a single PC is around 4 professional dan. Let's suppose that squeezing it from a PC to a phone takes about the same off. Now a pocket phone is about 8 professional dan weaker than the full distributed system.

If their full trained system is now 9 dan, that means that they can likely squeeze it into a phone and get a 1 dan professional. So the computing power on a phone already allows us to play at the professional level!

You can get to an unbeatable device on a phone in 10 years, if self-training over a decade can create about as much improvement they have done in the last 6 months, AND phones in 10 years are about as capable as a PC is today. Those two trade off, so a bigger algorithmic improvement gets you there with a weaker device.

You consider this result "overly optimistic". I consider this estimate very conservative. If Google continues to train it, I wouldn't be surprised if there is a PC program in a year that can beat any Go player in the world.

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

#437

Earlier quoted context omitted.

The interesting thing is that this algorithm taught itself to master the game. If you're writing a chess engine, you just "write the AI for the problem space" in a few dozen lines of code, as you put it, and let brute force do the rest. In the case of DeepMind, faced with a game where a traversal approach is numerically impossible, its programmers gave it the ability to improve by playing against itself. That's the d…

it is a big deal, but it is still very different from general AI, and we are very good at underestimating complexity. Remember that "solve computer vision" was considered a summer project.

Remember that "solve computer vision" was considered a summer project.

And they're pretty much there. Have you seen some of the latest results in that field?

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

#438
post #339
post #219

Earlier quoted context omitted.

Please do elaborate. I try to base my assumptions (which I accept may turn out to be completely wrong) on physics and experience in working in semiconductors. I just don't see a 1000x+ decrease in the power required happening in a decade or two without some revolutionary technology I can't even imagine. Is this what you meant? I'm sure most people couldn't imagine modern silicon chips in the 1950s vacuum tube era. Bu…

Here's some possibilities: Stacked 3D chips (HBM, etc), Heterogenous computing (OpenCL, Vulkan), Optical computing, Memristors, Graphene-based microchips, Superconductors, Spintronics, Quantum computers, Genetic computers (self-reconfigurable)

Heterogenous computing is already used in AlphaGo (and your smartphone). 3d chips will come to mainstream devices in a few years, but will give "only" a modest performance boost, say 2x or so.

The rest of the technologies you mention have great potential but will they be available in a smartphone in one decade? I don't think so.

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

#439

Earlier quoted context omitted.

There is a lot of progress being made in AI right now. Hard problems that were expected to take decades, are being beaten regularly. Who is to say how much AI could advance in the next 20-30 years? Do you really believe there's less than a 50% chance strong AI won't be invented in your lifetime?

There is a lot of progress being made in AI right now. Hard problems that were expected to take decades, are being beaten regularly. Who is to say how much AI could advance in the next 20-30 years? "We've beaten some hard problems more quickly than expected therefore we'll likely beat other hard problems more quickly than expected" is logical induction. It's equivalent to "I just flipped a coin and got heads. I'll pr…

>I just flipped a coin and got heads. I'll probably get heads again on the next flip

Which is corrrect, if you don't know the true probability of flipping heads. You might find, for example, that it's a trick coin with two heads and no tails.

You absolutely can predict future progress from past progress. E.g. Moore's law held true for decades after the observation was made. If you see a technology advancing rapidly, then there is no reason to say it will stop in the near future!

>I don't really see the value in speculating.

Because everything depends on this prediction. The invention of AI will be the most significant event in the history of humanity. It will totally change the world. Or likely, destroy it. Being prepared for it is absolutely necessary.

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

#440
post #151

Beating humans in Go is, in itself, not all that exciting. Go bots have been beating strong humans for quite some time now (just not the very top humans). There are other implications that make this AlphaGo progress super exciting though. Go captures strategic elements that go well beyond the microcosm of one nerdy board game. That's the real reason Go has been around for >2,000 years, and why this AI progress is rel…

I disagree with this due to the rate of AlphaGo's progress. Consider CrazyStone which was the previous state of the art in Go computers. That program reached 5dan after many years of development and has not shown any signs of being able to reach Lee Sedol level (9dan).

In October of this year AlphaGo beat a 5dan player, bringing it into the range of CrazyStone. Only ~6 months later it beats a 9dan player which means it is now ~400 Elo higher. This means the new version would be predicted to beat the old version ~99% of the time.

Such incredible consistent progress of a problem considered somewhat intractable is notable and exciting. Imagine where this machine will be in 6 more months.

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