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8 years later: A world Go champion's reflections on AlphaGo

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Re: 8 years later: A world Go champion's reflections on AlphaGo

#21

Post by HackerThemAll »

tromp wrote: post #5

> Go is a deeply complex strategic game — famously far more complicated than chess, with 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible board configurations. The correct number of legal Go positions is over twice as much, or to…

All these digits are only making it more obfuscated. Using the order of magnitude it's 10^44 for chess versus 10^170 for Go. Thus, Go is 10^126 times more complex than chess.

For reference, the estimated number of individual atoms in the universe is thought to be between mere 10^80 and 10^83.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#22

Post by pvg »

ArtTimeInvestor wrote: post #16
bongodongobob wrote: post #11

Earlier quoted context omitted.

You do realize this was 8 years ago, and no Go engine came even close to what Alpha Go was able to do right? Afaik, there weren't even any competitive engines period. It basically came out of nowhere.

That's what I meant. That's how it usually goes with technological progress. In any field. Progress is minimal for a few years and then suddenly jumps up very suddenly. So to predict what's coming, you can't just extrapolate the progress of recent years. You have to account for it being exponential with a very uneven distribution of sudden jumps.

In any field.

That would be pretty strange. For a trivial counterexample, you can look up the history of integrated circuits from invention to today.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#23

Post by jsheard »

bevekspldnw wrote: post #17
svachalek wrote: post #7

Earlier quoted context omitted.

> In ten years, probably no human can compete with AI drivers anymore. That's what they said 10 years ago. Sooner or later people will say it and be right, but the last few percent of any problem is a lot harder than people give it credit for. It may not be that hard to stay in a lane or write a little code, and that may look like it's doing most of the job, but those common tasks are just the easy part.

“Driving” is solved. Driving with humans on the road - doing unpredictable human things - is far off still. My guess is industrial and home robotics will solve a lot of the “doing things around humans” problems in the next ten years. Why the hell people decided to automate giant death machines before perfecting small things never made sense to me.

> “Driving” is solved. Driving with humans on the road - doing unpredictable human things - is far off still.

Plus there's serious questions about liability with self driving cars which are still unresolved in most of the world - if the goal is to have vehicles operate themselves with no human supervision, who goes to jail when they kill someone? Despite all of the progress that's been made with AI it's mostly been in low-stakes problems where failure isn't a big deal, so we don't have a consensus on what we're supposed to do when a neural network negligently obliterates a person because some logistics company wanted to save a few bucks on driver salaries.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#24

Post by zehaeva »

ArtTimeInvestor wrote: post #16
bongodongobob wrote: post #11

Earlier quoted context omitted.

You do realize this was 8 years ago, and no Go engine came even close to what Alpha Go was able to do right? Afaik, there weren't even any competitive engines period. It basically came out of nowhere.

That's what I meant. That's how it usually goes with technological progress. In any field. Progress is minimal for a few years and then suddenly jumps up very suddenly. So to predict what's coming, you can't just extrapolate the progress of recent years. You have to account for it being exponential with a very uneven distribution of sudden jumps.

I'm not sure one can, from today that is, really understand how huge of a leap was made by AI at this time.

Even going back to the closest analogue, chess, there were good chess engines for a long time prior to Kasparov loosing in 97 to deep blue. Even before Kasparov lost Chess engines were pretty good, just look at the game in 96 when Kasparov won. A grand master would still need to put some thought into how he played.

In Go however even the best engines couldn't hold a candle to a professional player, let alone someone who was the equivalent of a chess grand master. Hell, even as a lowly amateur player I was able to trounce some of the most powerful AIs at the time. Looking at some of the Pro vs AI games back in the early 2010s it's almost painful how bad they were.

It's hard to communicate just how huge of a leap this was, and just how shocking to the whole Go community. It would be like a child one day being unable to speak and the literal next day reciting Shakespeare.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#25

Post by pinkmuffinere »

bevekspldnw wrote: post #17
svachalek wrote: post #7

Earlier quoted context omitted.

> In ten years, probably no human can compete with AI drivers anymore. That's what they said 10 years ago. Sooner or later people will say it and be right, but the last few percent of any problem is a lot harder than people give it credit for. It may not be that hard to stay in a lane or write a little code, and that may look like it's doing most of the job, but those common tasks are just the easy part.

“Driving” is solved. Driving with humans on the road - doing unpredictable human things - is far off still. My guess is industrial and home robotics will solve a lot of the “doing things around humans” problems in the next ten years. Why the hell people decided to automate giant death machines before perfecting small things never made sense to me.

Fwiw, I work in home robotics, but have no experience in self driving. My halfway-naive belief is that self-driving is easier than getting useful home robots —in fact I feel it’s not even a close comparison. Some reasons:

- The home is a very unstructured environment, whereas roads have at least _some structure_, and perhaps ~70% of the most useful roads even have clear lane markings and other signs.

- People already know that roads are dangerous, and there’s an expectation that babies won’t suddenly crawl in front of cars. This doesn’t exist in the home

- People are more comfortable being recorded on roads and highways than in their own homes, so you can get training data more easily for self driving.

- to do something useful in the home, imo you need to solve navigation _and_ complicated manipulation problems. For self driving, you only need to solve the navigation problem.

- (this is speculation on my part) Customers will happily pay 10k-20k extra for a self-driving car, and there are industries in which even more cost makes sense. Customers are less likely to pay that for a robot that does your chores

Would be very interested to hear the perspective of someone that works on self-driving

Re: 8 years later: A world Go champion's reflections on AlphaGo

#26

Post by nemothekid »

lawn wrote: post #13
ArtTimeInvestor wrote: post #4

I thought it would be an easy victory I ... ended up only winning one out of our five games It's interesting, how an expert in a field can be unaware of how AI is taking over. And a few years later, no human can compete anymore. I think we are in a similar situation in multiple professions today. For example with self-driving. Musk recently said, that other car manufacturers are not much interested in talks about lic…

> It's interesting, how an expert in a field can be unaware of how AI is taking over. I think the interesting thing is how an expert in a field is wholly unprepared for predicting how the future will develop. You mention what Musk has said about FSD and how it will completely take over in just ten years, but I feel compelled to point out that Musk has said that it's just right around the corner with only small challe…

Musk wasn't wrong - he just wasn't the person to deliver it. Waymo, AFAICT works astonishingly in San Francisco. I think you can argue that it might not work in the snow, but that's pretty much it

Re: 8 years later: A world Go champion's reflections on AlphaGo

#27

Post by lp4vn »

tromp wrote: post #5

> Go is a deeply complex strategic game — famously far more complicated than chess, with 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible board configurations. The correct number of legal Go positions is over twice as much, or to…

Go is played in a a bigger board though and has this kind of recursive nature where a subset of a go game is also a go game while chess is more ad-hoc.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#28

Post by samatman »

bevekspldnw wrote: post #17
svachalek wrote: post #7

Earlier quoted context omitted.

> In ten years, probably no human can compete with AI drivers anymore. That's what they said 10 years ago. Sooner or later people will say it and be right, but the last few percent of any problem is a lot harder than people give it credit for. It may not be that hard to stay in a lane or write a little code, and that may look like it's doing most of the job, but those common tasks are just the easy part.

“Driving” is solved. Driving with humans on the road - doing unpredictable human things - is far off still. My guess is industrial and home robotics will solve a lot of the “doing things around humans” problems in the next ten years. Why the hell people decided to automate giant death machines before perfecting small things never made sense to me.

I think your guess that home robotics will be solving problems before self-driving cars git gud will be disproven (industrial robotics have been delivering value for five decades at least).

Home robotics has to solve two problems: the robot and operating the robot ~perfectly. Self-driving cars already have cars, which are waldos, if you squint. What sort of sensors should be added is up for debate but the actuation mechanism is a solved problem, and a very simple one, cars have three linear inputs and two binary ones for the turn signals. Technically a few more but none of them are any less trivial.

There's less risk of a fatality when Rosie Robot knocks over the vase you inherited from your grandmother, but people are no more tolerant of that kind of failure in home robots than they are in cars.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#29

Post by rhaps0dy »

Great PR for Google from Lee! It totally isn't mostly for advancing Google's commercial interests, the bottom line being:

"I believe that humans can partner with AI and make great progress. As long as we can set clear principles and standards for it, I am quite optimistic about the future of AI technology in our daily lives."

I hope he got paid well.

Re: 8 years later: A world Go champion's reflections on AlphaGo

#30

Post by Veserv »

bevekspldnw wrote: post #17
svachalek wrote: post #7

Earlier quoted context omitted.

> In ten years, probably no human can compete with AI drivers anymore. That's what they said 10 years ago. Sooner or later people will say it and be right, but the last few percent of any problem is a lot harder than people give it credit for. It may not be that hard to stay in a lane or write a little code, and that may look like it's doing most of the job, but those common tasks are just the easy part.

“Driving” is solved. Driving with humans on the road - doing unpredictable human things - is far off still. My guess is industrial and home robotics will solve a lot of the “doing things around humans” problems in the next ten years. Why the hell people decided to automate giant death machines before perfecting small things never made sense to me.

“Driving” is not solved unless you mean perfectly paved streets in perfect weather on empty streets with no pedestrians. A competent solution like Waymo can handle significantly more complex cases at real world levels of complexity, but it is still unclear how comprehensive and robust that really is across the massive complexity of reality even without other cars on the road. There is simply not enough data, and no independent audits yet.

It is prudent to remain cautiously optimistic that the evidence will bear out in time, but not assert unsupported claims.

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