This AI Boom Will Also Bust • Hacker News Board

Re: This AI Boom Will Also Bust

#271

Post by jfv » Sun, Dec 04, 2016, 6:55 AM UTC

dwaltrip wrote: post #185

jfv wrote: post #182

Earlier quoted context omitted.

So is image recognition, but I think the main contention is that solving Go required little additional cleverness to what has already existed. The ideas of self-play, Monte Carto methods, and neural networks are not new and not novel for the problem. Not that it's so trivial -- I'm sure it took a while to work out the exact architecture and details, but what of that work actually teaches you something?

The combination of the methods was certainly novel as far as I am aware. Also, it was not clear ahead of time that it would actually succeed in defeating the best humans. Demonstrating that it could be done is a grear achievement. There is also the symbolic value. It was a "coming of age" event to a certain degree. I believe go was the last classic board game that researchers had been longing to conquer. I haven't lo…

My problem is that what people seem to be saying now is that "computers are smart enough to solve Go now, thanks to Google".

1) Too much credit is given to Google for this result. What I see as already a huge brain drain on society is only going to get bigger.

2) People are going to expect that if "computers are smart enough to play Go", they're smart enough to do ____. What goes in the blank? Very little right now, but I guarantee you investors and the public have a lot of ideas and think it's around the corner.

Hopefully a lot of good things will come out of this wave of AI, but who knows what or when. I think the point is that there may be a panic and contraction before anything really awesome happens, and a lot of that is going to be because of "stunts" (for lack of a better word) like this being overhyped.

Re: This AI Boom Will Also Bust

#272

Post by inimino » Sun, Dec 04, 2016, 7:18 AM UTC

logicallee wrote: post #214

xamuel wrote: post #209

Earlier quoted context omitted.

If P=NP then we already have the hardware to crack RSA encryption. The above sentence is true, but it has no bearing on anything.

don't you think it would have a lot more bearing if you had 7 billion devices nonchallantly walking around cracking RSA every day using the same or less hardware? (but we couldn't reverse-engineer them, because they were obfuscated in biology)? The fact that they weren't reverse-engineered (yet) would still have huge bearing on everything. By 7 billion samples I mean the humans walking around. Your analogy with an RS…

How much computing hardware does it take to beat a human at chess or at go? (Less than you think, Deep Blue was hopelessly inefficient.) And how long did it take for those much simpler things to happen?

Re: This AI Boom Will Also Bust

#273

Post by ianai » Sun, Dec 04, 2016, 7:37 AM UTC

dTal wrote: post #90

dheera wrote: post #39

Earlier quoted context omitted.

And before you do mundane data science on your structured data, you should figure out if there is a better way to get cleaner raw data, more data, as well as more accurate data. For example, I predict stereo vision algorithms will die out soon, including deep-learning-assisted stereo vision. It's useful for now but not something to build a business around. Better time-of-flight depth cameras will be here soon enough.…

Stereo vision is obviously highly effective in biology as it has independently evolved a great many times. Time-of-flight may be poised for a renaissance, but it scales badly and is active, not passive. Stereo vision, and its big brother light fields, are far more general and are certainly not going to "die out".

Actually brains eventually learn how to discern distance with one eye too, iirc.

Re: This AI Boom Will Also Bust

#274

Post by inimino » Sun, Dec 04, 2016, 7:39 AM UTC

mmkx wrote: post #219

zamalek wrote: post #200

One of two eventualities exist: * The article is correct and the current singularity (as described by Kurzweil) will hit a plateau. No further progress will be made and we'll have machines that are forever dumber than humans. * The singularity will continue up until SAI. So help them human race if we shackle it with human ideologies and ignorance. There is no way to tell. AlphaGo immensely surprised me - from my pers…

It's already happening. The world became hyper efficient. The hackers behind "Trumpbots" made money on the prediction markets. Understanding that mechanic makes me almost certain the singularity arrived after his election.

...what?

Re: This AI Boom Will Also Bust

#275

Post by bayonetz » Sun, Dec 04, 2016, 7:47 AM UTC

orthoganol wrote: post #198

vonnik wrote: post #123

[Disclosure: I work for a deep-learning company.] Robin's post reveals a couple fundamental misunderstandings. While he may be correct that, for now, many small firms should apply linear regression rather than deep learning to their limited datasets, he is wrong in his prediction of an AI bust. If it happens, it will not be for the reasons he cites. He is skeptical that deep learning and other forms of advanced AI 1)…

> that will prove him wrong I'm skeptical of claims about a one-shot learning silver bullet, unless people are talking about something different from how it has been classically presented, .e.g. Patrick Winton's MIT lectures. Yes, you can learn from a few examples, but only because you've imparted your expert knowledge, maintain a large number of heuristics, control the search space effectively, etc. There's a lot of…

Succinctly, there is no free lunch...

Re: This AI Boom Will Also Bust

#276

Post by tekni5 » Sun, Dec 04, 2016, 8:29 AM UTC

dkarapetyan wrote: post #253

dquail wrote: post #245

Earlier quoted context omitted.

Agree generally. Except being unimpressed unless performance is achieved on sub Google scale hardware. Today's Google supermachine is tomorrow's raspberry pie. No need to artificially constrain our bounds. There is, after all, the inevitability of Moores law.

Moore's law has been dead for a while now. Most of the chip in your phone is powered off because otherwise it would burn up. Highly recommend watching this video: https://www.youtube.com/watch?v=_9mzmvhwMqw

Very fascinating talk, and easy to understand.

Have there been any solutions proposed, in particular to the limitations of adding extra cores.

Re: This AI Boom Will Also Bust

#277

Post by tekni5 » Sun, Dec 04, 2016, 8:31 AM UTC

dquail wrote: post #264

dkarapetyan wrote: post #253

Earlier quoted context omitted.

Moore's law has been dead for a while now. Most of the chip in your phone is powered off because otherwise it would burn up. Highly recommend watching this video: https://www.youtube.com/watch?v=_9mzmvhwMqw

Interesting. I've yet to hear a Moores law is dead argument, so perhaps I should watch the video before commenting further. But the fact that most of the chip is turned off, doesn't falsify the fact that most of it still exists. Cooling it properly is a separate problem independent of computation no?

The talk mentions that there is a physical law to how many cores you can add to a CPU before it becomes useless, even with parallel computing.

Re: This AI Boom Will Also Bust

#278

Post by Noseshine » Sun, Dec 04, 2016, 8:47 AM UTC

logicallee wrote: post #196

Noseshine wrote: post #183

Earlier quoted context omitted.

> Obviously it is hard to know when that magic moment will happen that some kind of general AI > is created that can learn in some sense similarly to how humans do. My every indication and > astonishment at the results that are being produced strongly suggests "at any moment". As an IT guy with a basic but solid neuroscience education (which isn't even needed for what I'm about to say): Yep, you are on the hype train…

My hype is different, because in my estimation we already have the hardware. You write: >As an IT guy with a basic but solid neuroscience education -- could you go ahead and take a few minutes (maybe will take you 5-10) to read through my above-referenced links referencing my previous discussion and tell me whether I'm correct in your estimation on the bottom-up aspect - i.e. the amount of computation that human neur…

  > i.e. the amount of computation that human neural nets can likely be doing

We don't know nearly enough what they are really doing! We only know a few selected bits and pieces! You are basing your assumptions on nothing, so according to logic any conclusion is possible from a faulty premise. On which you promptly deliver spectacularly.

Also, the "computation" a brain does at one moment leaves out the time aspect: Lots of things lead to constant changes. The wiring changes all the time. The "computation" metaphor has little use for describing or understanding this major aspect of "brain". The more I learned about neuroscience the more unhappy I got with the computing metaphor that I had had going in (as a CS graduate, naturally, I think). The brain is so very, very different from my pre-neuroscience-courses notions.

How much neuroscience do you know? If the answer isn't at least an undergrad introductory course (the accompanying book is over a thousand pages), why do you get the idea you can make any predictions?

Read this to read about complexity in biology vs. engineering and what scientists in the field think how well we are dealing with it:

- http://biorxiv.org/content/early/2016/05/26/055624

- http://www.cell.com/cancer-cell/fulltext/S1535-6108(02)00133...

Test yourself: Do you understand what he's talking about? http://inference-review.com/article/the-excitable-mitochondr...

Fortunately you don't have to sign up at university these days just for such knowledge:

Free courses (if you ignore the certificate nonsense):

- https://www.mcb80x.org/ (This is linked to from edX as "The Fundamentals of Neuroscience" Parts 1, 2, 3)

- https://www.coursera.org/courses?languages=en&query=neurosci... (Especially "Medical Neuroscience": https://www.coursera.org/learn/medical-neuroscience)

- https://www.edx.org/course?search_query=neuroscience

Re: This AI Boom Will Also Bust

#279

Post by Noseshine » Sun, Dec 04, 2016, 9:30 AM UTC

xamuel wrote: post #241

logicallee wrote: post #214

Earlier quoted context omitted.

don't you think it would have a lot more bearing if you had 7 billion devices nonchallantly walking around cracking RSA every day using the same or less hardware? (but we couldn't reverse-engineer them, because they were obfuscated in biology)? The fact that they weren't reverse-engineered (yet) would still have huge bearing on everything. By 7 billion samples I mean the humans walking around. Your analogy with an RS…

Interesting observation. If brains routinely cracked RSA, that could be evidence that P=NP. Still it wouldn't help us find the P-time algorithm in question. We could say "it seems to exist", but that would not imply "we'll discover it any day now".

  > If brains routinely cracked RSA

For brains numbers have a completely different meaning and internal representation than for computers. Brains don't "think in numbers". Doing the kind of math we invented is a major effort for the brain, it's not what it developed for, and it is very poorly equipped to do explicit numerical calculations (emphasis on "explicit"). So looking at brains to "crack RSA" seems like waiting for a hammer to be useful in driving screws.

Re: This AI Boom Will Also Bust

#280

Post by tim333 » Sun, Dec 04, 2016, 10:50 AM UTC

_fh5n wrote: post #141

I understand that most people working with deep learning wouldn't want this type of thinking to spread amongst the public, and I surely don't want it either. But you have to be totally unaware of reality to think that DL is the definitive tool for AI. Most impressive results in DL in the past 2 years happended like this: >deepmind steals people from the top ML research teams in univerisites around the world >these pe…

I'm not sure solving Pacman on a Raspberry Pi would be terribly worthwhile. Deepmind's research into getting their software to play Atari games was interesting because they used a general algorithm that just received the values of the screen pixels and game score and learned from there. They used the same software for each game - it wasn't tuned or set up differently and so was a form of general AI if a very sub human one. It was interesting research that it worked as well as it did and played some games very well but wasn't good as Pacman because it lacked the ability to plan ahead.

They are primarily a research company, not a marketing setup. The latest stuff the released on letting the networks do something like dreaming which reduced the time to learn by up to 10x seemed interesting and I look forward to seeing how they do with Starcraft and the hippocampus. A lot of this stuff is cool because it gives insights into the human mind and how the brain works rather than practical gadgets. https://www.extremetech.com/extreme/240163-googles-deepmind-...