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SoylentRox t1_j9bqmp7 wrote

As I understand it:

(1) current quantum computers are useless for AI so far (not enough qbits)

(2) they are useful for limited types of problems.

AI is useful for everything. So there's a lot more interest in it.

Like a lot of things, the actual tech order is probably:

high perf computers -> narrow AI -> AGI -> self replicating robots -> nanotechnology -> quantum computers

That is, we will not have large and useful quantum computers until we have nanotechnology, and we can't afford that without self replicating robots, and we can't make that without AGI, and so on.

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turnip_burrito t1_j9bx76r wrote

Wait, why are quantum computers only possible after AGI? Researchers are doing fine without it so far, from my bystander view.

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SoylentRox t1_j9bz1xs wrote

Because the current ones cost a fortune and have almost no qbits, making them useless for most problems. There are nasty scaling laws that make adding more qbits nonlinearly harder.

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turnip_burrito t1_j9bz6pt wrote

But the number of qubits is increasing rapidly, I thought?

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SoylentRox t1_j9bzbhm wrote

It is not, and the number needed to do useful things like crack encryption is very far away.

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turnip_burrito t1_j9bzfd6 wrote

I see. How many orders of magnitude more will be needed?

Edit: A quick Google search returns 10^8 over 1 hour for breaking AES 256. Right now we're at 10^2 and I don't know how long it stays coherent (looks like around 10^-4 seconds). I see what you mean now for encryption.

How much do you need for quantum chemistry simulations? Quick Googlr search says the numbers are far lower to be useful there. Maybe 10^2 or 10^3 order of magnitude?

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SoylentRox t1_j9c5lgd wrote

Also how useful is quantum chemistry.

You can probably just "memorize the rules" with a neural network, the way protein folding was solved, and not actually simulate the quantum chemistry. This is drastically faster and almost as accurate.

This means you just do a bunch of chemistry experiments, or load in the data from already performed experiments, and figure out the rules so you can predict the experiments you didn't perform. Neural networks can already learn most possible functions so they can approximate what a quantum chemistry sim would theoretically be exact for.

And the approximations can be potentially just as accurate : remember your input data has finite resolution. (significant figures)

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Sigma_Atheist t1_j9c1voq wrote

As far as I'm aware, there is no known quantum algorithm that could break AES-256.

Your quantum chemistry simulation qubit estimate seems about right. But that's also a boring use case. You'll only make money off of chemistry researchers.

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mr_ludd t1_j9cf4s6 wrote

> there is no known quantum algorithm that could break AES-256.

So far...

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MultiverseOfSanity OP t1_j9dwwt7 wrote

Hmm, growing up, I always thought AGI would require quantum computing. Guess I was wrong.

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SoylentRox t1_j9dx7nz wrote

I thought it would require a lot of things. But here we are.

Open source devs have re-created the core of an LLM like GPT-3 (it's what powers chatGPT and BingChat) in a few thousand lines of code.

It's really not that complicated. https://github.com/EleutherAI/gpt-neox

And yet this one repeated algorithm and a few tricks in training and we can get like 50% of human intelligence right there.

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