Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

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

twitter.com

Post reply on HN
Print view View original

261–270 of 596 posts

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

#261

Post by JabavuAdams »

simonh wrote: post #61
21 wrote: post #12

The thing that was supposed to take at least 10 years happened. Only last month people were still saying that no way AlphaGo will beat the champion and that it will be crushed. Today everybody will have seen it coming and say that it was normal. Yet people will still tell that worrying about AI taking over is like worrying about overpopulation on Mars, and that this is a problem at least 50 years out.

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…

> This gets us no closer to strong AI than a tic tac toe program.

We don't know that, actually. Maybe GAI isn't one shining simple algo, but cobbling together a bunch of algorithms like this one.

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

#262

Post by fma »

GolDDranks wrote: post #203
knaik94 wrote: post #53

Earlier quoted context omitted.

The real achievement is in the algorithm. To make an analogy, the accomplishment of putting a man on the moon required that we understand enough to make a rocket. We could have put hundreds of car engines together but that wouldn't ever have gotten us to the moon.

This. AlphaGo utilizes the "Monte Carlo tree search" as its base algorithm[1]. The algorithm has been used for ten years in Go AIs, and when it was introduced, it made a huge impact. The Go bots got stronger overnight, basically. What novel thing AlphaGo did, was a similar jump in algorithmic goodness. It introduced two neural networks for 1) predicting good moves at the present situation 2) evaluating the "value" of…

Neural networks have been around for a long time. They basically took two existing concepts of AI and threw some money.

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

#263

Post by GolDDranks »

mafribe wrote: post #242
mjn wrote: post #63

Earlier quoted context omitted.

> 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 . I don't think that's quite true as a description of what we knew about computer Go previously, though it depends on what precisely you mean. Recent systems (meaning the past 10 years…

Play strength scales roughly with the log of computing power The rumor I have heard is that the new Deep Mind learning algorithm really improves on this and scales linearly with computing power.

The game itself, however, scales exponentially, and there's nothing to do about that, so if you enlargen the board, no computer... And no human may be able to play it well.

The achivement was a leap towards the human level of play (and quite possibly over it). There might be additional leaps, which will take AIs WAY beyond humans, but none of those will scale linearily in the end. (And yeah, I guess you didn't want to say that either)

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

#264

Post by fma »

Houshalter wrote: post #99
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…

Welcome to the AI effect! Every time AI makes an accomplishment, it is disregarded. The goalposts are perpetually moved. "AI is whatever computers can't do yet." People said for years that Go would never be beaten in our lifetime. They said this because Go has a massive search space. It can't be beaten by brute force search. It requires intelligence, the ability to learn and recognize patterns. And it requires doing…

As far as I know the goal post of Turing test has never moved.

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

#266

Post by JabavuAdams »

panic wrote: post #81
brian_cloutier wrote: post #71

Earlier quoted context omitted.

Forest for the trees. Monte Carlo Tree Search was necessary and itself a massive improvement over minimax but not sufficient for creating a Go program to challenge professional players. The true innovation here is the neural networks. Without those networks to guide it AlphaGo plays far worse than existing programs. The fact that those networks are sufficient is pretty incredible. We already knew that by inventing th…

It's totally impressive! I'm excited for the future of DeepMind and to see what other kinds of things we can build from neural networks. I'm just saying that we have to be careful with what kind of intelligence we ascribe to an algorithm like this. An AI is not going to take over the world by impressing us with its game-playing skills.

> An AI is not going to take over the world by impressing us with its game-playing skills.

What if you train an AI to play an RTS where matter, energy, and time are the resources and the goal is to take over the world?

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

#267

Post by sergiosgc »

exDM69 wrote: post #186
taneq wrote: 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…

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: "but this time it is a fundamental physics limit". Whatever. I'm jaded by previous doomsday predictions. We'll go clockless, or 3D, or tri-state or quantum. It'll be something that is fringe, treated as idiotic by current standards and an obvious choice in hindsight.

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

#268

Post by alienbaby »

taneq wrote: post #35
esturk wrote: post #24

Earlier quoted context omitted.

I've never felt playing against what is suppose to be an entire room of machines (wether Deep Blue or Watson) to be fair. What would be fair is to limit the total mass of the computer to say 200kg and leave it at that. What is effectively happening is AlphaGo is running on a distributed system of many, many machines. Even Watson took an entire room. Google is paying a premium to push AlphaGo to win.

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.

No, they haven't shown that the same kind of intelligence required to play go can be implemented in computer software. The methods AlphaGo uses are not the same as the intelligence a human uses at all. What they have done is prove an implementation of computer go in software is capable of beating a human player, not that they have implemented the same kind of intelligence as the human player.

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

#269

Post by kqr »

aurelianito wrote: post #221
kqr wrote: post #192

Earlier quoted context omitted.

The drawback with Capture Go is that it emphasises the capturing part perhaps a bit too much. I prefer introducing players to a variant with the same rules as capture go, except the winning condition is "having the most pieces on the board". This is essentially the same thing as regular go, but without all the fuffing about with learning scoring and such. When played on a small enough board, the games take about as l…

What do you do if they enter in ko?

Depending on which level you want to put the game at, you can either say that ko = draw or quickly explain how something like PSK works.

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

#270

Post by fma »

nl wrote: post #195
ubernostrum wrote: post #109

Earlier quoted context omitted.

Sort-of repeating a comment I made last time AlphaGo came up: As far as I know there is nothing particularly novel about AlphaGo, in the sense that if we stuck an AI researcher from ten years ago in a time machine to today, the researcher would not be astonished by the brilliant new techniques and ideas behind AlphaGo; rather, the time-traveling researcher would probably categorize AlphaGo as the result of ten years'…

It's easy to say that, in the same way that people now wouldn't be surprised if we could factor large numbers in linear time if we had a functional quantum computer !! 10 years ago no one believed it was possible to train deep nets[1]. It wasn't until the current "revolution" that people learned how important parameter initialization was. Sure, it's not a new algorithm, but it made the problem tractable. So far as al…

It's only difficult because no one threw money at it. It's like saying going to Mars is difficult. It is - but most of the technology is there already, just need money to improve what was used to go to the moon.

If you asked people 10 years ago before the moon landing if it was possible, I too would agree it's impossible. But after that breakthrough it opened up the realm is possibilities.

I see AlphaGo more of an incremental improvement than a breakthrough.

Post reply on HN