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Google and a nuclear fusion company have developed a new algorithm

theguardian.com

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Re: Google and a nuclear fusion company have developed a new algorithm

#81

Post by erikpukinskis »

noobermin wrote: post #67
abefetterman wrote: post #37

Earlier quoted context omitted.

Basically nobody was using automated gradient descent / etc because of the proclivity of these algorithms to get stuck on a boundary. The problem is the boundaries are not well defined. One example might be a catastrophic instability. If it gets triggered it has the potential to damage the machine. But the exact parameters in which the instability occurs are not well known. So with this algorithm you mix the best of…

I am still very skeptical that a human is really that good at avoiding the problem areas, although they might be marginally better. Plus, they don't seem to claim that anywhere in the paper, instead, they just rated shots as either "better" or"just as good", ie., a local evaluation which won't let you avoid such areas, which of course is a judgement that requires more knowledge than just the conditions in the neighbo…

> I am still very skeptical that a human is really that good at avoiding the problem areas

Why? Humans have a much richer modeling apparatus than any computer does right now. We can draw on a very large and yet almost fully tuned to reality set of possible models simultaneously. You can estimate the number of available models as whatever number of neurons you have, in combinatorial. We also have machinery for searching that entire model space simultaneously and testing against a continuous stream of megabytes of data in realtime, in order to find good fits.

Existing AIs wouldn't even know where to start. They can apply infinite models, but have no grounding in reality, and no way to choose amongst them. The AI doesn't even have an intrinsic sense of space, seeing has how it lacks a body. It's a very fast worker that can get things done when you give it very specific instructions, but it has no real ability to understand what it is doing or why it would want to do something different.

Re: Google and a nuclear fusion company have developed a new algorithm

#82

Post by ChuckMcM »

efm wrote: post #68
lamp_book wrote: post #20

From the actual journal article: > Two additional complications arise because plasma fusion apparatuses are experimental and one-of-a-kind. First, the goodness metric for plasma is not fully established and objective: some amount of human judgement is required to assess an experiment. Second, the boundaries of safe operation are not fully understood: it would be easy for a fully-automated optimisation algorithm to pr…

Hot or not, but for dynamical systems optimization.

Each plasma out come is shown to a researcher as a Tinder profile, if they select the ones they want by swiping right :-)

Re: Google and a nuclear fusion company have developed a new algorithm

#83

Post by kleer001 »

amelius wrote: post #60
abefetterman wrote: post #16

This is actually a really exciting development to me. (Note, what is exciting is the "optometrist algorithm" from the paper [1] not necessarily googles involvement as pitched in the guardian). Typically a day of shots would need to be programmed out in advance, typically scanning over one dimension (out of hundreds) at a time. It would then take at least a week to analyze the results and create an updated research pl…

Perhaps a stupid question, but why can't the whole experiment be run as a simulation?

The numbers are too big, and nature is hiding stuff from us.

So we can't simulate it because we don't know enough to simulate it. And even if we did know there's not enough computing power to do so.

Re: Google and a nuclear fusion company have developed a new algorithm

#84

Post by paulsutter »

amelius wrote: post #60
abefetterman wrote: post #16

This is actually a really exciting development to me. (Note, what is exciting is the "optometrist algorithm" from the paper [1] not necessarily googles involvement as pitched in the guardian). Typically a day of shots would need to be programmed out in advance, typically scanning over one dimension (out of hundreds) at a time. It would then take at least a week to analyze the results and create an updated research pl…

Perhaps a stupid question, but why can't the whole experiment be run as a simulation?

Because fusion simulations are really hard. This simulation[1] took 15 million hours of CPU time to model a cubic cm of plasma. The results were used to update 5 scalar parameters in a model.

[1] http://news.mit.edu/2016/heat-loss-fusion-reactors-0121

Re: Google and a nuclear fusion company have developed a new algorithm

#85

Post by eternauta3k »

zitterbewegung wrote: post #15
EternalData wrote: post #4

Google might try to become the conglomerate of all forward-facing things but it is somewhat funny to see how through it all, it's their advertising revenues that form the core of the business.

This pattern happens more often than you think. Microsoft: They make an Operating System and Office Suite. From Microsoft Research they have labs on Quantum Computing, they have five Turing Award winners (One is Leslie Lamport) and he developed TLA+ while employed there. Facebook: A social network Funds a bunch of Deep Learning Research and NLP. Elon Musk: Helped create PayPal, now does electric cars and rockets, (Te…

Bell Labs, over 1k PhDs at some point.

Re: Google and a nuclear fusion company have developed a new algorithm

#86

Post by semi-extrinsic »

noobermin wrote: post #63
amelius wrote: post #60

Earlier quoted context omitted.

Perhaps a stupid question, but why can't the whole experiment be run as a simulation?

The system is fundamentally 6^N dimensional with N~10^23.

I suppose you meant 6*N? Which is a lot better, but still intractable. And anyway, we don't exactly resolve molecules in e.g. turbulent flow simulations, yet they still take tens, even hundreds of millions of CPU-hours.

Re: Google and a nuclear fusion company have developed a new algorithm

#87

Post by ouid »

dmurray wrote: post #78
ouid wrote: post #72

Earlier quoted context omitted.

is it picking a new configuration at random, or does it still have to be "close" to the last configuration?

It still has to be close by some metric to be considered hill climbing. The article doesn't make it clear, but I suspect a lot of the insight in the algorithm is how the computer chooses two similar sets of inputs that differ in an "interesting" way.

last clarifications, sorry.

Some manifold has a goodness function defined on it, described by a (totally ordered?) relation provided by the observing scientist.

The goodness function is assumed to be (continuous/differentiable/continuously differentiable?) with respect to some metric, and the computer picks a random coordinate within some small distance of the last coordinate in the metric, and then asks the human to order them?

I don't think this is hill climbing, and my simple reasoning for that is that I don't believe the first assertion. The expert is almost certainly behaving non-deterministically. In fact, I believe that each time the expert is presented with the "same" pair of coordinates, he is more likely to yield a different ordering.

That said, I could be reading this wrong.

Re: Google and a nuclear fusion company have developed a new algorithm

#88

Post by DennisP »

dwaltrip wrote: post #31

There was a talk about the state of nuclear fusion by some MIT folks linked here on HN a few days ago. One of the biggest takeaways was that many fusion efforts are very far away (3 to 6+ orders of magnitude) on the most important metric, Q, which is energy_out / energy_in. Additionally, much press and public discussion completely fail to discuss this and other core factors that actually matter for making fusion viab…

Tri Alpha has been running at relatively low temperature, about 10 million degrees, while they figured out how to make their plasma stable. They achieved that in 2015 with their older reactor.

According to their model, the plasma should get more stable at higher temperature. They just finished a new reactor they'll use to test that. It'll hit temperatures closer to 100 million degrees.

If they're right about plasma stability, they'll be ready to attempt net power with a full-scale demo reactor. Since they're using boron fuel they'll need to get the temperature to about three billion degrees, but they say pumping in more heating is relatively easy.

(Source for all that: I saw one of the Tri Alpha people speak at an MIT Solve conference the other year.)

So the 50% improvement isn't a make-or-break thing, but I'm sure it'll help. In general, being able to run simulations in hours instead of months will probably help a lot.

Re: Google and a nuclear fusion company have developed a new algorithm

#89

Post by noobermin »

semi-extrinsic wrote: post #86
noobermin wrote: post #63

Earlier quoted context omitted.

The system is fundamentally 6^N dimensional with N~10^23.

I suppose you meant 6*N? Which is a lot better, but still intractable. And anyway, we don't exactly resolve molecules in e.g. turbulent flow simulations, yet they still take tens, even hundreds of millions of CPU-hours.

6*N, yes. Pretty bad mistake there. But yes, even if you don't model every particle and restrict yourself to "parcels" of fluid like in most simulations, you still have a very difficult problem.
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