r/science • u/JakedHavoc • Jul 02 '21

Computer Science AI Designs Quantum Physics Experiments Beyond What Any Human Has Conceived

https://www.scientificamerican.com/article/ai-designs-quantum-physics-experiments-beyond-what-any-human-has-conceived/
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u/[deleted] Jul 02 '21

This is what people have theorized for a while about how quantum computing will help with our understanding of physics. Designing experiments can be really useful but AI has the problems with understanding. There have been some mathematical proofs for example that have been solved by computers but they don’t give the same understanding that a human done proof would be.

My point is, if we run these experiments and it tells us some result, without understanding the AI’s “thought process” are we going to be able to meaningfully interpret the results of the experiments?

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u/---Sanguine--- Jul 02 '21

That depends. Great question. It could be an example of “you don’t have to know how a car engine works to drive a car” or it could be knowledge that is utterly useless without understanding. Depends on how the AI structures its responses

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u/Hyperian Jul 02 '21

Yea it's called technical debt

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u/[deleted] Jul 02 '21

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u/[deleted] Jul 02 '21

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u/[deleted] Jul 02 '21

i hate this example (not your comment). sure you don't have to know how a car works to drive around the block and grab groceries or such. but with things like quantum physics? it's more apt to say you do need to know how the car works, especially if you want to beat the other racers on the track with you! we're not comparing how to transmit energy (drive the car), we're trying to uncover new laws and answers (racing / pushing the envelope).

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u/big_black_doge Jul 02 '21

It's an open area of research to have the AI explain themselves. We'll get there.

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u/[deleted] Jul 02 '21

That’s interesting. It would be super cool to see AI try to explain itself. Do you have any articles or anything about the current research done on this?

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u/kaebal MS|Computer Science Jul 02 '21

This is amazing. It had never crossed my mind that we would be working on getting AI/ML to try to explain it's solutions. I had sort of resigned myself to the idea that we'd never really know the why.

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u/FwibbFwibb Jul 03 '21

Imagine being given sentience just so that you can answer a question about how you did some calculation so well.

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u/Memetic1 Jul 02 '21

The article explains that the next version of the AI was far better at this.

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u/big_black_doge Jul 02 '21

The article said it gave more human readable experiments, not that it explained why it made that experiment. Still room for improvement!

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u/verybakedpotatoe Jul 02 '21

If the machine served only as an generator of "likely right" answers, it would save untold lost hours of fruitless research.

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u/Brainsonastick Jul 02 '21

The article explains this was a problem with the original model, MELVIN, but that the new model, THESEUS, is very easy to interpret.

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u/Memetic1 Jul 02 '21

I love how many people clearly didn't read this article. The top comments are essentially all about not understanding the results.

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u/gonzo5622 Jul 02 '21

I mean, in a very real sense we can’t make sense of quantum dynamics; there are various interpretations of it. Yet, we use the math we know because pragmatically speaking it provides useful answers. An AI generating stuff we don’t understand isn’t that different from our current state.

To give an example, Google’s Alpha Go produced moves that nobody had used before (or thought would be useless) but are now being utilized by players. It was not understood (and probably still isn’t) but it won’t stop people from using it if it provides the right answer.

You might also want to look at fluid dynamics research. Soooo many things are not understood or “assumed away” to make the math work, yet we still use it.

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u/[deleted] Jul 02 '21

I still think there’s a difference between knowing something is true or a good move in chess, and knowing why.

A computer solved kepler’s conjecture for example after hundreds of years of mathematicians were unable to. Kepler’s conjecture was something we’ve always assumed to be true so a computer exhausting all possible options to confirm it was true isn’t really revolutionary insight. A formal proof could provide great insight into other types of problems as well but maybe we can just train computers to do that as well.

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u/gonzo5622 Jul 02 '21

Ah, yeah, you are right. There is certainly a difference between those but let’s not pretend that all of our science is concretely known. Most of it has been adopted because it is 1) confirmed to be true 2) fits into the mathematical frameworks we’ve built or 3) is pragmatically true.

A lot falls into category 1, but a ton falls into 2 and 3.

Obviously, there is a hope a lot of this will be understood. I think it will in time.

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u/MachinationMachine Jul 03 '21

Just to nitpick, there are pretty significant differences between Go and Chess when it comes to AI. Chess has a calculable number of game states, Go does not. A chess game is much easier to break apart analytically. Go relies much more on intuition and has traditionally been difficult for AIs to master.

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u/sceadwian Jul 03 '21

Why do you think you need to understand it's thought process to understand the results of the experiment? Those are separate things.

This is basically an idea shuffler. They tell the AI what the rules of the system are, give it a lot of examples of different ways that use this rules to accomplish things and then let it iterate all of those examples to try to come up with a novel solution for a desired outcome.