AI winter is well on its way • Hacker News Board

Re: AI winter is well on its way

#241

Post by crummy » Wed, May 30, 2018, 9:51 AM UTC

Grue3 wrote: post #153

ehsankia wrote: post #88

Earlier quoted context omitted.

How can something be biased when it's listing facts? Those are actual features that are available today to anyone, that were made possible by AI. Do you think it would be possible to type "pictures of me at the beach with my dog" without AI in such as short time frame? Or to have cars that drive themselves without a driver? These are concrete benefits of machine learning, I don't understand how that's biased.

Can't speak for the other items, but these >translate over 100 languages in Google Translate; >caption over a billion videos in 10 languages on YouTube; barely even work. Yeah, it's a difficult problem but it's not even close to being solved.

Google Translate is way, way better than it used to be (at least German > English which I suppose is probably an easier task than many languages).

Re: AI winter is well on its way

#242

Post by some_account » Wed, May 30, 2018, 9:53 AM UTC

felippee wrote: post #137

tim333 wrote: post #109

Earlier quoted context omitted.

>Deepmind hasn't shown anything breathtaking since their Alpha Go zero They went on to make AlphaZero, a generalised version that could learn chess, shogi or any similar game. The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. That seemed impressive to me. Also they used loads of compute during the training but not so much during play.(5000 TPUs, 4TPUs). Also it got better th…

It's not like humanity really needs another chess playing program 20 years after IBM solved that problem (but now utilizing 1000x more compute power). I just find all these game playing contraptions really uninteresting. There are plenty real world problems to be solved of much higher practicality. Moravec's paradox in full glow.

Tell me about it. The brightest minds are working on ads, and we have AI playing social games.

Can AI make the world better? It can, but it won't since we are humans, and humans will weaponize technology every chance it gets. Of course some positive uses will come, but the negative ones will be incredibly destructive.

Re: AI winter is well on its way

#243

Post by YeGoblynQueenne » Wed, May 30, 2018, 9:54 AM UTC

tmalsburg2 wrote: post #193

Stopped reading after the first half. The evidence for the idea that deep learning is failing is that Deep Mind haven't produced anything revolutionary since Alpha Go Zero which was published not even a year ago? And that preformance doesn't scale linearly with the number of parameters? And speculation about why Lecun made a certain career decision? Not very convincing.

You're forgetting that Andrew Ng is tweeting 30% less this year! Isn't that enough to convince even the staunchest critic?

Re: AI winter is well on its way

#244

Post by danielbarla » Wed, May 30, 2018, 9:58 AM UTC

kelnage wrote: post #228

danielbarla wrote: post #182

Earlier quoted context omitted.

You're right, though the distinction with the parent poster is that AlphaGo Zero had no input knowledge to learn from, unlike humans (who read books, listen to other players' wisdom, etc). It's a fairly well known phenomenon that e.g. current era chess players are far stronger than previous eras' players, and this probably has to do with the accumulation of knowledge over decades, or even hundreds of years. It's incr…

But software is starting from the same base. To claim it isn't would be to claim that the computers programmed themselves completely (which is simply not true).

Sure, there is some base there, and a fair bit of programming existed in the structure of the implementation. However, the heuristics themselves were not, and this is very significant. The software managed to reproduce and beat the previous best (both human and the previous iteration of itself), completely by playing against itself.

So, in this sense, it's kind of like taking a human, teaching them the exact rules of the game and showing them how to run calculations, and then telling them to sit in a room playing games against themselves. In my experience from chess, you'd be at a huge disadvantage if you started with this zero-knowledge handicap.

Re: AI winter is well on its way

#245

Post by MichaelMoser123 » Wed, May 30, 2018, 9:59 AM UTC

Forget about self driving cars - the real killer application of deep learning is mass surveillance - there are big customer for that (advertising, policing, political technology - we better get used to the term) and its the only technique that can get the job done.

I sometimes think that there really was no AI winter as we got other technologies that implemented the ideas: SQL Databases can be seen as an application of many ideas in classical AI - for example its a declarative language for defining relations among tables; you can have rules in the form of SQL stored procedures; actually it was a big break (paradigm shift is the term) in how you deal with data - the database engine has to do some real behind the scenes optimization work in order to get a workable representation of the data definition (that is certainly bordering on classical AI in complexity).

these boring CRUD applications are light years ahead in how data was handled back in the beginning.

Re: AI winter is well on its way

#246

Post by red75prime » Wed, May 30, 2018, 9:59 AM UTC

kelnage wrote: post #228

danielbarla wrote: post #182

Earlier quoted context omitted.

You're right, though the distinction with the parent poster is that AlphaGo Zero had no input knowledge to learn from, unlike humans (who read books, listen to other players' wisdom, etc). It's a fairly well known phenomenon that e.g. current era chess players are far stronger than previous eras' players, and this probably has to do with the accumulation of knowledge over decades, or even hundreds of years. It's incr…

But software is starting from the same base. To claim it isn't would be to claim that the computers programmed themselves completely (which is simply not true).

All software starts with a base of 4 billion years of evolution and thousands years of social progress and so on. But Alpha Zero doesn't require a knowledge of Go on top of that.

Re: AI winter is well on its way

#247

Post by salvar » Wed, May 30, 2018, 10:01 AM UTC

pleasecalllater wrote: post #130

tim333 wrote: post #109

Earlier quoted context omitted.

>Deepmind hasn't shown anything breathtaking since their Alpha Go zero They went on to make AlphaZero, a generalised version that could learn chess, shogi or any similar game. The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. That seemed impressive to me. Also they used loads of compute during the training but not so much during play.(5000 TPUs, 4TPUs). Also it got better th…

> The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. In a not equal fight, and the results are still not published. I'm not claiming that AlphaZero wouldn't win, but that test was pure garbage.

How was it not equal?

Re: AI winter is well on its way

#248

Post by Retric » Wed, May 30, 2018, 10:04 AM UTC

danielbarla wrote: post #182

carlmr wrote: post #168

Earlier quoted context omitted.

>Also it got better than humans in those games from scratch in about 4 hours whereas humans have had 2000 years to study them so you can forgive it some resource usage. Most humans don't live 2000 years. And realistically don't spend that much of their time or computing power on studying chess. Surely a computer can be more focused at this and the 4h are impressive. But this comparison seems flawed to me.

You're right, though the distinction with the parent poster is that AlphaGo Zero had no input knowledge to learn from, unlike humans (who read books, listen to other players' wisdom, etc). It's a fairly well known phenomenon that e.g. current era chess players are far stronger than previous eras' players, and this probably has to do with the accumulation of knowledge over decades, or even hundreds of years. It's incr…

Not so much from the accumulation of knowledge because players can only study so many games. The difference is largely because their are more people today, they have more free time, and they could play vs high level opponents sooner.

Remember people reach peak play in ~15 years, but they don't nessisarily keep up with advances.

PS: You see this across a huge range of fields from running, figure skating, to music people simply spend more time and resources getting better.

Re: AI winter is well on its way

#249

Post by [deleted] » Wed, May 30, 2018, 10:05 AM UTC

EliRivers wrote: post #198

batmansmk wrote: post #164

Earlier quoted context omitted.

I guess there are reasons why researchers build chess programs: it is easy to compare performance between algorithms. When you can solve chess, you can solve a whole class of decision-making problems. Consider it as the perfect lab.

What is that class of decision-making problems? It's nice to have a machine really good at playing chess, but it's not something I'd pay for. What decision-making problems are there, in the same class, that I'd pay for? Consider it as the perfect lab. Seems like a lab so simplified that I'm unconvinced of its general applicability. Perfect knowledge of the situation and a very limited set of valid moves at any one ti…

[deleted]

Re: AI winter is well on its way

#250

Post by salty_biscuits » Wed, May 30, 2018, 10:09 AM UTC

felippee wrote: post #137

tim333 wrote: post #109

Earlier quoted context omitted.

>Deepmind hasn't shown anything breathtaking since their Alpha Go zero They went on to make AlphaZero, a generalised version that could learn chess, shogi or any similar game. The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. That seemed impressive to me. Also they used loads of compute during the training but not so much during play.(5000 TPUs, 4TPUs). Also it got better th…

It's not like humanity really needs another chess playing program 20 years after IBM solved that problem (but now utilizing 1000x more compute power). I just find all these game playing contraptions really uninteresting. There are plenty real world problems to be solved of much higher practicality. Moravec's paradox in full glow.

It's not like the research on games is at the expense of other more worthy goals. It is a well constrained problem that lets you understand the limitations of your method. Great for making progress. Alpha zero didn't just play chess well, it learned how to play chess well (and could generalize to other games). I'd forgive it 10000 times the resources for that.