V_V

Karma: 2,133

V_V Mar 9, 2016, 10:22 PM
6 points
in reply to: turchin’s comment on: AlphaGo versus Lee Sedol

EY could have such price if he invested more time in studying neural networks, but not in writing science fiction.

Has he ever demonstrated any ability to produce anything technically valuable?

V_V Mar 9, 2016, 4:29 PM
12 points
in reply to: Vaniver’s comment on: AlphaGo versus Lee Sedol

What I’m curious about is how much this reflects an attempt by AlphaGo to conserve computational resources.

If I understand correctly, at least according to the Nature paper, it doesn’t explicitly optimize for this. Game-playing software is often perceived as playing “conservatively”, this is a general property of minimax search, and in the limit the Nash equilibrium consists of maximally conservative strategies.

but I was still surprised by the amount of thought that went into some of the moves.

Maybe these obvious moves weren’t so obvious at that level.

V_V Mar 8, 2016, 9:32 PM
2 points
in reply to: Douglas_Knight’s comment on: Would you notice if science died?
Thanks for the information.

V_V Mar 8, 2016, 5:35 PM
0 points
in reply to: ChristianKl’s comment on: Would you notice if science died?
Would you label the LHC “science” or “engineering”?

V_V Mar 8, 2016, 5:32 PM
2 points
on: Would you notice if science died?
Was Roman engineering really based on Greek science? And by the way, what is Greek science? If I understand correctly, the most remarkable scientific contributions of the Greeks were formal geometry and astronomy, but empirical geometry, which was good enough for the practical engineering applications of the time, was already well developed since at least the Egyptians, and astronomy didn’t really have practical applications.

V_V Mar 8, 2016, 9:11 AM
5 points
in reply to: James_Miller’s comment on: AIFoom Debate—conclusion?

Eventual diminishing returns, perhaps but probably long after it was smart enough to do what it wanted with Earth.

Why?

A drug that raised the IQ of human programmers would make the programmers better programmers.

The proper analogy is with a drug that raised the IQ of researchers who invent the drugs that increase IQ. Does this lead to an intelligence explosion? Probably not. If the number of IQ points that you need to discover the next drug in a constant time increases faster than the number of IQ points that the next drug gives you, then you will run into diminishing returns.

It doesn’t seem to be much different with computers.

Algorithmic efficiency is bounded: for any given computational problem, once you have the best algorithm for it, for whatever performance measure you care for, you can’t improve on it anymore. And in fact long before you reached the perfect algorithm you’ll already have run into diminishing returns in terms of effort vs. improvement: past some point you are tweaking low-level details in order to get small performance improvements.

Once you have maxed out algorithmic efficiency, you can only improve by increasing hardware resources, but this 1) requires significant interaction with the physical world, and 2) runs into asymptotic complexity issues: for most AI problems worst-case complexity is at least exponential, average case complexity is more difficult to estimate but most likely super-linear. Take a look at the AlphaGo paper for instance, figure 4c shows how ELO rating increases with the number of CPUs/GPUs/machines. The trend is logarithmic at best, logistic at worst.

Now of course you could insist that it can’t be disproved that significant diminishing returns will kick in before AGI reaches strongly super-human level, but, as I said, this is an unfalsifiable argument from ignorance.

V_V Mar 8, 2016, 12:48 AM
1 point
in reply to: James_Miller’s comment on: AIFoom Debate—conclusion?

For almost any goal an AI had, the AI would make more progress towards this goal if it became smarter.

True, but there it is likely that there are diminishing returns in how much adding more intelligence can help with other goals, including the instrumental goal of becoming smarter.

As an AI became smarter it would become better at making itself smarter.

Nope, doesn’t follow.

V_V Mar 7, 2016, 3:50 PM
0 points
in reply to: Gunnar_Zarncke’s comment on: AIFoom Debate—conclusion?

But what if a general AI could generate specialized narrow AIs?

How is it different than a general AI solving the problems by itself?

V_V Mar 7, 2016, 12:33 PM
0 points
in reply to: James_Miller’s comment on: AIFoom Debate—conclusion?
That’s a 741 pages book, can you summarize a specific argument?

V_V Mar 6, 2016, 3:18 PM
0 points
in reply to: TheAncientGeek’s comment on: AIFoom Debate—conclusion?

I’m asking for references because I don’t have them. it’s a shame that the people who are able, ability-wise, to explain the flaws in the MIRI/FHI approach

MIRI/FHI arguments essentially boil down to “you can’t prove that AI FOOM is impossible”.

Arguments of this form, e.g. “You can’t prove that [snake oil/cryonics/cold fusion] doesn’t work” , “You can’t prove there is no God”, etc. can’t be conclusively refuted.

Various AI experts have expressed skepticism in an imminent super-human AI FOOM, pointing out that the capability required for such scenario, if it is even possible, are far beyond what they see in their daily cutting-edge research on AI, and there are still lots of problems that need to be solved before even approaching human-level AGI. I doubt that these expert would have much to gain from keeping to argue over all the countless variations of the same argument that MIRI/FHI can generate.

V_V Feb 21, 2016, 9:11 PM
0 points
in reply to: Kaj_Sotala’s comment on: LINK: Videogame with a very detailed simulated universe
This is a press release though, lots of games were advertised with similar claims that don’t live up to expectation when you actually play them.

The reason is that designing an universe with simple and elegant physical laws sounds cool on paper but it is very hard to do if you want to set an actually playable game in it, since most combinations of laws, parameters and initial conditions yield uninteresting “pathological” states. In fact this also applies to the laws of physics of our universe, and it is the reason why some people use the “fine tuning” argument to argue for creationism or multiple universes.

I’m not an expert game programmer, but if I understand correctly, in practice these things use lots of heuristics and hacks to make them work.

V_V Feb 19, 2016, 11:30 AM
10 points
on: LINK: Videogame with a very detailed simulated universe
Video games with procedural generation of the game universe have existed since forever, what’s new here?

V_V Feb 12, 2016, 11:37 PM
23 points
on: Where does our community disagree about meaningful issues?
- “Bayes vs Science”: Can you consistently beat the experts in (allegedly) evidence-based fields by applying “rationality”? AI risk and cryonics are specific instances of this issue.
- Can rationality be learned, or is it an essentially innate trait? If it can be learned, can it be taught? If it can be taught, do the “Sequences” and/or CFAR teach it effectively?

V_V Feb 12, 2016, 10:33 PM
−2 points
in reply to: gwern’s comment on: The Brain Preservation Foundation’s Small Mammalian Brain Prize won

If the new evidence which is in favor of cryonics benefits causes no increase in adoption, then either there is also new countervailing evidence or changes in cost or non-adopters are the more irrational side.

No. If evidence is against cryonics, and it has always been this way, then the number of rational adopters should be approximately zero, thus approximately all the adopters should be the irrational ones.

As you say, the historical adoption rate seems to be independent of cryonics-related evidence, which supports the hypothesis that the adopters don’t sign up because of an evidence-based rational decision process.

V_V Feb 12, 2016, 10:26 PM
0 points
in reply to: gwern’s comment on: The Brain Preservation Foundation’s Small Mammalian Brain Prize won
4.You have a neurodegenerative disease, you can survive for years but if you wait there will be little left to preserve by the time your heart stops.

V_V Feb 12, 2016, 5:54 PM
0 points
in reply to: qmotus’s comment on: The Brain Preservation Foundation’s Small Mammalian Brain Prize won
If revival had been already demonstrated then you would pretty much already know what form you will be going to wake up in

V_V Feb 12, 2016, 10:29 AM
0 points
in reply to: gwern’s comment on: The Brain Preservation Foundation’s Small Mammalian Brain Prize won

Adoption is not about evidence.

Right. But the point is, who is in the wrong between the adopters and the non-adopters?

It can be argued that there was never good evidence to sign up for cryonics, therefore the adopters did it for irrational reasons.

V_V Feb 12, 2016, 10:08 AM
2 points
in reply to: Brillyant’s comment on: The Brain Preservation Foundation’s Small Mammalian Brain Prize won

I’m not sure this distinction, while significant, would ensure “millions” of people wouldn’t sign up.

Millions of people do sign up for various expensive and invasive medical procedures that offer them a chance to extend their lives a few years or even a few months. If cryonics demonstrated a successful revival, then it would be considered a life-saving medical procedure and I’m pretty confident that millions of people would be willing to sign up for it.

People haven’t signed up for cryonics in droves because right now it looks less like a medical procedure and more like a weird burial ritual with a vague promise of future resurrection, a sort of reinterpretration of ancient Egyptian mummification with an added sci-fi vibe.

V_V 7 Feb 2016 10:03 UTC
0 points
in reply to: Richard_Kennaway’s comment on: Upcoming LW Changes
Here.

V_V 31 Jan 2016 20:23 UTC
0 points
in reply to: Houshalter’s comment on: [Link] AlphaGo: Mastering the ancient game of Go with Machine Learning

The best setting for that is probably only 3-5 characters, not 20.

In NLP applications where Markov language models are used, such as speech recognition and machine translation, the typical setting is 3 to 5 words. 20 characters correspond to about 4 English words, which is in this range.

Anyway, I agree that in this case the order-20 Markov model seems to overfit (Googling some lines from the snippets in the post often locates them in an original source file, which doesn’t happen as often with the RNN snippets). This may be due to the lack of regularization (“smoothing”) in the probability estimation and the relatively small size of the training corpus: 474 MB versus the >10 GB corpora which are typically used in NLP applications. Neural networks need lots of data, but still less than plain look-up tables.