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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

#41

Post by [deleted] »

reaperman wrote: post #31
pinkmuffinere wrote: post #25

Earlier quoted context omitted.

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…

> Customers are less likely to pay that for a robot that does your chores They will if you can get them 2% financing like I can get on a new Honda HR-V.

[deleted]

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

#42

Post by hyperpape »

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…

At the time, the only public results were demonstration games against a much weaker professional. The actual strength of the machine was only known privately within DeepMind.

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

#43

Post by bevekspldnw »

Veserv wrote: post #30
bevekspldnw wrote: post #17

Earlier quoted context omitted.

“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 i…

Precisely my point, I’m talking about the DARPA grand challenge era of “look this car drives itself” being the “solved” part. I’d you cleared all the roads and left street signs and stoplights I’m sure most self-driving cars would be fine.

People got way overconfident once the grand challenges were accomplished.

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

#44

Post by bevekspldnw »

ArtTimeInvestor wrote: post #18
bevekspldnw wrote: post #17

Earlier quoted context omitted.

“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 the giant death machines costs us billions of manhours every day. Hundreds of billions of manhours per year. Which small thing puts a similar burden on mankind?

Phones.

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

#45

Post by bevekspldnw »

pinkmuffinere wrote: post #25
bevekspldnw wrote: post #17

Earlier quoted context omitted.

“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…

Yes this is my point - the home is a hard place to operate in but less potential for lethal outcomes. If we can solve home robotics I think cars would be easier.

Also, a robot that replaces a housekeeper would have a huge market. I’d pay a handsome sum to have perfectly cleaned kitchen and bathrooms every day when I wake up.

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

#46

Post by FooBarBizBazz »

radarsat1 wrote: post #40
vintermann wrote: post #19

Earlier quoted context omitted.

Not entirely right. Remi Coulom's Monte Carlo Tree Search, in 2006, was the first really big discovery. It didn't make engines good enough to beat the best humans, but it steadily made them good enough to beat 99% of go playing humans, playing at up to 6 - 7 dan level. It was still part of AlphaGo, too (though as I recall AlphaGo Zero did away with it).

I think AlphaZero does use MCTS?

The thing AlphaZero did away with, AFAIK, is supervision with expert games. Instead it just knows the rules and tries to win.

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

#48

Post by SkyMarshal »

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. And a few years later, no human can compete anymore.

Easy to see that in hindsight, but when the game was actually played it was earlier in the development of AI and less apparent how good it had become.

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

#49

Post by dvh »

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…

FSD will never work because it concentrates defendants into single juicy target.

When your neighbor Bob (who is still paying mortgage and his wife is battling cancer and who occasionally babysit your kids) ran over your cat, you don't sue him. But you would sue Tesla.

Mark my words, in 10 years ex-programmers will be throwing shelter cats under FSD cars just to earn a living.

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

#50

Post by xcv123 »

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.

AlphaGo took many AI researchers by surprise. An even bigger surprise came next year, with AlphaZero:

"AlphaZero was a reinforcement learning system that was able to master three different perfect information games - chess, shogi (Japanese chess), and Go - at superhuman levels by just learning from self-play, without using any human expert games or domain knowledge crafted by programmers.

Its predecessor AlphaGo, which defeated the world champion Go player in 2016, was revolutionary but relied on human expert games and domain-specific rules coded by the DeepMind researchers.

AlphaZero started from random play and used a general-purpose reinforcement learning algorithm to iteratively improve its gameplay through self-play, ending up with superior performance compared to the best human players and previous game-specific AI systems.

Many experts were stunned that a general algorithm could rediscover from scratch the millennia-old principles and strategies for these highly complex games, often discovering novel and counterintuitive moves along the way."

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