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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

#331

Post by PascalsMugger »

onion2k wrote: post #193
Houshalter wrote: post #116

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…

Do you think it's better to propose we won't, and not start preparing for a smarter-than-human intelligence. Or to propose we might, and that we should prepare for it to happen?

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

#332

Post by hacker_9 »

afc wrote: post #284
sergiosgc wrote: post #267

Earlier quoted context omitted.

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:…

This looks like a good example of the Normalcy bias logical fallacy: https://en.wikipedia.org/wiki/Normalcy_bias That previous constraints have been beaten in no way supports the argument that we will beat the laws of physics this time.

Our brains use roughly ~20 watts though, so we know that the power constraints can be overcome, if not in silicon then it may be biological machines we use in the future.

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

#333

Post by hyperpape »

spot wrote: post #317
j2kun wrote: post #306

Earlier quoted context omitted.

> without having all of the training data in advance What? They certainly trained the algorithm on a huge database of professional go games. It's even in the abstract. [1] [1]: http://www.nature.com/nature/journal/v529/n7587/full/nature1...

they were amateur expert games from the KGS server.

I believe the October match used amateur games, but for this match, they added a professional database.

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

#334

Post by PascalsMugger »

s_kilk wrote: post #176
vkou wrote: post #94

Earlier quoted context omitted.

That, and towel-folding [1]. Humans have a pretty clear edge on that. [1] https://www.youtube.com/watch?v=gy5g33S0Gzo&ab_channel=RLLbe...

That's pretty cool. I wonder how it would deal with a teddy bear or stray piece of underwear in the pile of towels?

I look forward to a future when the only remaining occupation is hotel maid.

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

#335

Post by PascalsMugger »

moistgorilla wrote: post #117
atemerev wrote: post #77

Earlier quoted context omitted.

The only remaining are language-related. Natural languages are the next focal point of AI research.

How about walking and image recognition.

The recent video of Boston Dynamics Atlas robot looked like it could walk about as well as a human, maybe even better at recovering its balance (see it heroically walking through snow).

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

#336

Post by goblinking »

eru wrote: post #208
spacehome wrote: post #146

Earlier quoted context omitted.

Yea, let me just go home and grab my hundreds of GPUs and CPUs.

Renting them in the cloud for a single game should actually not be all that expensive. Around 100 USD per game perhaps? And the price is only going to fall. An Amateur can learn plenty from slightly weaker version on less hardware already.

Lee Se-dol as a Service!

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

#337

Post by jonknee »

ciot1CDM wrote: post #322
exDM69 wrote: post #172

Earlier quoted context omitted.

1202 CPUs and 176 GPUs is the figure mentioned in the Nature paper. But it's important to understand that this is the computer used to train the networks used by the algorithm. It took about 30+ days worth of wallclock to train it. That's about 110 megawatt-hours (MWh) worth of energy required! During the play, the computational requirements are vastly less (but I don't know the figures). It's still probably more tha…

If your 110MWh to train is accurate, and the 25W used by the human brain reported in this thread is as well. This is equivalent to one person expending 500 years solely to learn Go.

And thus why we're not destined to compete with AI, that 110MWh worth of training time can be instantly available to all other Go bots. If only I could have access to a Grandmaster's brain when I needed it!

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

#338

Post by Ketsuban »

chakkop wrote: post #106
zamalek wrote: post #74

Earlier quoted context omitted.

Indeed. The first time a computer defeated a human in Chess it was this[1] size (1997). In 2009 it became possible to fit a grandmaster into this[2]. > Pocket Fritz 4 won the Copa Mercosur tournament in Buenos Aires, Argentina with 9 wins and 1 draw on August 4–14, 2009. Pocket Fritz 4 searches fewer than 20,000 positions per second. This is in contrast to supercomputers such as Deep Blue that searched 200 million po…

GM Michael Stean lost to Cyber 176 (a mainframe 'supercomputer') in 1977 (at blitz). AFAIK this was the first time a computer defeated a GM; they began defeating IMs and experts some ten years before that. Kasparov himself lost to Fritz 2 at blitz as early as 1992.

"Under tournament conditions" is the condition everyone forgets. Go AIs were competing with ranked players given handicaps of varying degrees of absurdity.

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

#339

Post by nwah1 »

exDM69 wrote: post #219
Cyph0n wrote: post #190

Earlier quoted context omitted.

Your making the same assumption people made about computing in the 50s, then 70s, then 90s, etc.

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)

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

#340

Post by lern_too_spel »

argonaut wrote: post #130
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'…

Agreed. People don't realize that all of the huge algorithmic innovations (LSTMs, Convolutional neural networks, backpropagation) were invented in past neural net booms. I can't think of any novel algorithms of the same impact and ubiquity (e.g. universally considered to be huge algorithmic leaps) that have been invented in this current boom. The current boom started due to GPUs.

Dropout and deep belief networks are significant recent algorithmic advances that are already widely used.
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