4 ms·

Artificial Intelligence for Quantum Computing

66 points by jimminyx 2y ago

bastloing 2y ago
Throw in some crypto and you've got a recipe for some great word salad!
- kaycebasques 2y ago
  Blockchain and AI algorithms yield novel insights in superconductor quantum computing
  - dartos 2y ago
    I really believe that the confluence of these paradigm shifting technologies will enable even greater gains in productivity. With our new AI enabled smart algorithms, we can meta-analyze transactions in systems such as blockchain networks to identify areas where resources can be more effectively aggregated. We also gave tight integration with salesforce and Jira, enabling next-gen teams to conduct research and ship products with much flatter management structure. I wish word salad artist was a profession
itchyjunk 2y ago
Petition to add AI to HN so it lists out the gist of papers and articles posted xD . I also always thought AI would overlap with Q Annealing in some way vaguely because both are optimization process. But maybe this is where QC helps AI and not the other way around.
- l33tbro 2y ago
  People can deploy that personally if they wish. The abstract captures the gist in most cases.
mg 2y ago
Is there a metric which lets us track how far/close we are to do something useful with quantum computers? And when we look at that metric and extrapolate its progression over the last years, when do we expect QCs to hit datacenters?
- foresttony 2y ago
  QCs are in all major data centers already. Although there is not much you can do with them, but you can use them. IONQ is considered the leader right now in QC. Look them up, very interesting stuff they are doing. They just partnered with astrazeneca to start developing useful applications. They will also demonstrate hybrid algorithms next week where they offload some stuff to QPUs to speed up models. I would say within two years QCs will start being useful.
  - almostgotcaught 2y ago
    > QCs are in all major data centers already Citation needed
- bawolff 2y ago
  I think https://xkcd.com/678/ https://xkcd.com/678/ is relavent. Basically we are far enough out from "useful" QC that its anyone's guess (except for the people trying to convince you to invest in their startup). That said relavent metrics include number of qubits and their error rate (once you get past a certain number with a low enough error rate you can start to use error correction which is when things really start to become interesting) It does depend a bit on what you mean by "useful" though see also https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_era https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quant...
  - foresttony 2y ago
    Good job commenting on something you know nothing about...
    - 2y ago
dr_dshiv 2y ago
The most remarkable thing is using frontier models to write and then run code on quantum computers (eg IBM’s). It’s amazing — you can even teach with a “creative coding” approach (without the multiple courses in quantum physics). It’s not even the code that is the hardest part. In general, it is very difficult to frame a given problem domain (ie, any other field of science or optimization problem) as a problem addressable with a quantum computer. Quantum computer scientists have not made this easy—with LLMs, it still isn’t trivial, but it is a huge leap in accessibility. Warning: LLMs hallucinate a ton within this area. Many things can go wrong. But the fact that sometimes they are correct is amazing to me. We’ve run some studies showing the importance of expertise in this area: participants with quantum background and coding skills were much more effective at solving quantum problems with LLMs than novices, for instance.
Escapado 2y ago
My master thesis was on using machine learning techniques to synthesise quantum circuits. Since any operation on a QC can be represented as a unitary matrix my research topic was that, using ML, given a set of gates, how many and in what arrangement of them you could generate or at least approximate this matrix. Another aspect was, given a unitary matrix, could a neural network predict a number of gates needed to simulate that matrix as a QC and thereby give us a measure of complexity. It was a lot of fun to test different algorithms from genetic algorithms to neural network architectures. Back then NNs were a lot smaller and I trained them mostly on one GPU and since the matrices get exponentially bigger with the amount of qbits in the circuit it was only possible for me to investigate small circuits with less than a dozen qubits but it was still nice to see that in principle this worked quite well.
- sigmoid10 2y ago
  At which university? I literally know a guy who did exactly the same thing for his master thesis. I'm wondering if the world is so small or this specific topic is so common.
  - Escapado 2y ago
    University of Hamburg in Germany.
- IIAOPSW 2y ago
  How did it do compared to the baseline of the solvoy kitaev algorithm (and the more advanced algorithms that experts have come up with since)? How (if at all) can the ML approach come up with a circuit when the unitary is too big to explicitly represent it as all the terms in the matrix but the general form of it is known? Eg it is known what the quantum fourier transform on N qubits is defined to be, and consequently any particular element within its matrix is easy to calculate, but you don't need (and shouldn't try) to write it out as a 2^n x 2^n matrix to figure out its implementation.
  - westurner 2y ago
    Solvay-Kiteav theorem: https://en.wikipedia.org/wiki/Solovay%E2%80%93Kitaev_theorem https://en.wikipedia.org/wiki/Solovay%E2%80%93Kitaev_theorem /? Solvay-Kiteav theorem Cirq QISkit: https://www.google.com/search?q=Solvay-Kiteav+theorem+cirq+qiskit https://www.google.com/search?q=Solvay-Kiteav+theorem+cirq+q... qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py: https://github.com/Qiskit/qiskit/blob/main/qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py https://github.com/Qiskit/qiskit/blob/main/qiskit/transpiler... qiskit/synthesis/discrete_basis/solovay_kitaev.py: https://github.com/Qiskit/qiskit/blob/stable/1.2/qiskit/synthesis/discrete_basis/solovay_kitaev.py#L24-L185 https://github.com/Qiskit/qiskit/blob/stable/1.2/qiskit/synt... SolovayKitaevDecomposition: https://docs.quantum.ibm.com/api/qiskit/qiskit.synthesis.SolovayKitaevDecomposition https://docs.quantum.ibm.com/api/qiskit/qiskit.synthesis.Sol... What are more current alternatives to the Solvay-Kiteav theorem for gate-based quantum computing?
medo-bear 2y ago
My next paper will be titled Artificial Intelligence for Quantum Computing with Applications to Blockchain ... in Rust
- dghughes 2y ago
  Used to find a cure cancer but only on a Friday.
JanisErdmanis 2y ago
One thing that comes to my mind and reminds me by looking into the examples is the fragility of existing implementation processes for quantum computers. Pulse optimisation, frequency allocation to minimise cross-talk between qubits, and the development of custom error correction codes tailored for specific quantum computers, circuits, or computations are unpredictable in their successes and, hence, inherently unscalable. It looks like the primary use for AI here is to optimise benchmark results for publishing rather than enable practical quantum computations.
aithrowawaycomm 2y ago
Outside of a few odd citations in the intro (which is innocuous) I don't see anything shady or dishonest in this paper after a cursory skimming. But I do worry about 60% of the authors being NVIDIA employees, where the corresponding author is not a staff scientist, but rather a "technical marketing engineer" whose job "focuses on inspiring developers by sharing examples of how NVIDIA quantum technologies can accelerate research."[1] So I am wondering about what articles didn't make it to this review, where ANN/GPU-accelerated QC research didn't work very well or was too expensive to justify. It makes me suspect I am being advertised to, and that this paper must be read with an unusually high degree of scrutiny. Like I said: there's nothing obviously shady or dishonest here. But this is also an arXiv paper, so no need for authors to disclose conflicts of interest. (OpenAI has pioneered the technique of using the arXiv to distribute academic infomercials with zero scientific value.) And I worry about the distortion this stuff has on honest scientific work. Bell Labs was always an independent subsidiary: Bell's marketing staff did not take ownership of Bell Labs' research. The fact that NVIDIA's marketer has a PhD and an "engineer" title doesn't actually mitigate any of this. [1] https://developer.nvidia.com/blog/author/mawolf/ https://developer.nvidia.com/blog/author/mawolf/
- alw4s 2y ago
  meanwhile the 5M prize for the first real application of quantum remains open.. quantum computing like string theory remains a scratch waiting for an itch - ie, a boondoggle. to be fair though, it is worth looking at something that has the potential to break all of the encryption on the internet.
Jabbs 2y ago
Aliens for Time Travel (is how I read this)
- bee_rider 2y ago
  Well, of course Aliens are for time travel. The universe is far too long, we don’t get to see anything interesting if we show up after everybody is dead.
vivzkestrel 2y ago
me and my friend used to joke about how to get VC funding a few years ago and it's about to be true soon at this rate VC: what are you building? me: Decentralized deep learning powered vertical farming using quantum computing on the blockchainfor onions
- dartos 2y ago
  That’s always how it works with tech investors
hulitu 2y ago
> Artificial Intelligence for Quantum Computing They forgot the blockchain. /s

66 points by jimminyx 2y ago

bastloing 2y ago

Throw in some crypto and you've got a recipe for some great word salad!

kaycebasques 2y ago
Blockchain and AI algorithms yield novel insights in superconductor quantum computing
- dartos 2y ago
  I really believe that the confluence of these paradigm shifting technologies will enable even greater gains in productivity. With our new AI enabled smart algorithms, we can meta-analyze transactions in systems such as blockchain networks to identify areas where resources can be more effectively aggregated. We also gave tight integration with salesforce and Jira, enabling next-gen teams to conduct research and ship products with much flatter management structure. I wish word salad artist was a profession

itchyjunk 2y ago

Petition to add AI to HN so it lists out the gist of papers and articles posted xD . I also always thought AI would overlap with Q Annealing in some way vaguely because both are optimization process. But maybe this is where QC helps AI and not the other way around.

l33tbro 2y ago
People can deploy that personally if they wish. The abstract captures the gist in most cases.

mg 2y ago

Is there a metric which lets us track how far/close we are to do something useful with quantum computers? And when we look at that metric and extrapolate its progression over the last years, when do we expect QCs to hit datacenters?

foresttony 2y ago
QCs are in all major data centers already. Although there is not much you can do with them, but you can use them. IONQ is considered the leader right now in QC. Look them up, very interesting stuff they are doing. They just partnered with astrazeneca to start developing useful applications. They will also demonstrate hybrid algorithms next week where they offload some stuff to QPUs to speed up models. I would say within two years QCs will start being useful.
- almostgotcaught 2y ago
  > QCs are in all major data centers already Citation needed
bawolff 2y ago
I think https://xkcd.com/678/ https://xkcd.com/678/ is relavent. Basically we are far enough out from "useful" QC that its anyone's guess (except for the people trying to convince you to invest in their startup). That said relavent metrics include number of qubits and their error rate (once you get past a certain number with a low enough error rate you can start to use error correction which is when things really start to become interesting) It does depend a bit on what you mean by "useful" though see also https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quantum_era https://en.wikipedia.org/wiki/Noisy_intermediate-scale_quant...
- foresttony 2y ago
  Good job commenting on something you know nothing about...
  - 2y ago

dr_dshiv 2y ago

The most remarkable thing is using frontier models to write and then run code on quantum computers (eg IBM’s). It’s amazing — you can even teach with a “creative coding” approach (without the multiple courses in quantum physics). It’s not even the code that is the hardest part. In general, it is very difficult to frame a given problem domain (ie, any other field of science or optimization problem) as a problem addressable with a quantum computer. Quantum computer scientists have not made this easy—with LLMs, it still isn’t trivial, but it is a huge leap in accessibility. Warning: LLMs hallucinate a ton within this area. Many things can go wrong. But the fact that sometimes they are correct is amazing to me. We’ve run some studies showing the importance of expertise in this area: participants with quantum background and coding skills were much more effective at solving quantum problems with LLMs than novices, for instance.

Escapado 2y ago

My master thesis was on using machine learning techniques to synthesise quantum circuits. Since any operation on a QC can be represented as a unitary matrix my research topic was that, using ML, given a set of gates, how many and in what arrangement of them you could generate or at least approximate this matrix. Another aspect was, given a unitary matrix, could a neural network predict a number of gates needed to simulate that matrix as a QC and thereby give us a measure of complexity. It was a lot of fun to test different algorithms from genetic algorithms to neural network architectures. Back then NNs were a lot smaller and I trained them mostly on one GPU and since the matrices get exponentially bigger with the amount of qbits in the circuit it was only possible for me to investigate small circuits with less than a dozen qubits but it was still nice to see that in principle this worked quite well.

sigmoid10 2y ago
At which university? I literally know a guy who did exactly the same thing for his master thesis. I'm wondering if the world is so small or this specific topic is so common.
- Escapado 2y ago
  University of Hamburg in Germany.
IIAOPSW 2y ago
How did it do compared to the baseline of the solvoy kitaev algorithm (and the more advanced algorithms that experts have come up with since)? How (if at all) can the ML approach come up with a circuit when the unitary is too big to explicitly represent it as all the terms in the matrix but the general form of it is known? Eg it is known what the quantum fourier transform on N qubits is defined to be, and consequently any particular element within its matrix is easy to calculate, but you don't need (and shouldn't try) to write it out as a 2^n x 2^n matrix to figure out its implementation.
- westurner 2y ago
  Solvay-Kiteav theorem: https://en.wikipedia.org/wiki/Solovay%E2%80%93Kitaev_theorem https://en.wikipedia.org/wiki/Solovay%E2%80%93Kitaev_theorem /? Solvay-Kiteav theorem Cirq QISkit: https://www.google.com/search?q=Solvay-Kiteav+theorem+cirq+qiskit https://www.google.com/search?q=Solvay-Kiteav+theorem+cirq+q... qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py: https://github.com/Qiskit/qiskit/blob/main/qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py https://github.com/Qiskit/qiskit/blob/main/qiskit/transpiler... qiskit/synthesis/discrete_basis/solovay_kitaev.py: https://github.com/Qiskit/qiskit/blob/stable/1.2/qiskit/synthesis/discrete_basis/solovay_kitaev.py#L24-L185 https://github.com/Qiskit/qiskit/blob/stable/1.2/qiskit/synt... SolovayKitaevDecomposition: https://docs.quantum.ibm.com/api/qiskit/qiskit.synthesis.SolovayKitaevDecomposition https://docs.quantum.ibm.com/api/qiskit/qiskit.synthesis.Sol... What are more current alternatives to the Solvay-Kiteav theorem for gate-based quantum computing?

medo-bear 2y ago

My next paper will be titled Artificial Intelligence for Quantum Computing with Applications to Blockchain ... in Rust

dghughes 2y ago
Used to find a cure cancer but only on a Friday.

JanisErdmanis 2y ago

One thing that comes to my mind and reminds me by looking into the examples is the fragility of existing implementation processes for quantum computers. Pulse optimisation, frequency allocation to minimise cross-talk between qubits, and the development of custom error correction codes tailored for specific quantum computers, circuits, or computations are unpredictable in their successes and, hence, inherently unscalable. It looks like the primary use for AI here is to optimise benchmark results for publishing rather than enable practical quantum computations.

aithrowawaycomm 2y ago

Outside of a few odd citations in the intro (which is innocuous) I don't see anything shady or dishonest in this paper after a cursory skimming. But I do worry about 60% of the authors being NVIDIA employees, where the corresponding author is not a staff scientist, but rather a "technical marketing engineer" whose job "focuses on inspiring developers by sharing examples of how NVIDIA quantum technologies can accelerate research."[1] So I am wondering about what articles didn't make it to this review, where ANN/GPU-accelerated QC research didn't work very well or was too expensive to justify. It makes me suspect I am being advertised to, and that this paper must be read with an unusually high degree of scrutiny. Like I said: there's nothing obviously shady or dishonest here. But this is also an arXiv paper, so no need for authors to disclose conflicts of interest. (OpenAI has pioneered the technique of using the arXiv to distribute academic infomercials with zero scientific value.) And I worry about the distortion this stuff has on honest scientific work. Bell Labs was always an independent subsidiary: Bell's marketing staff did not take ownership of Bell Labs' research. The fact that NVIDIA's marketer has a PhD and an "engineer" title doesn't actually mitigate any of this. [1] https://developer.nvidia.com/blog/author/mawolf/ https://developer.nvidia.com/blog/author/mawolf/

alw4s 2y ago
meanwhile the 5M prize for the first real application of quantum remains open.. quantum computing like string theory remains a scratch waiting for an itch - ie, a boondoggle. to be fair though, it is worth looking at something that has the potential to break all of the encryption on the internet.

Jabbs 2y ago

Aliens for Time Travel (is how I read this)

bee_rider 2y ago
Well, of course Aliens are for time travel. The universe is far too long, we don’t get to see anything interesting if we show up after everybody is dead.

vivzkestrel 2y ago

me and my friend used to joke about how to get VC funding a few years ago and it's about to be true soon at this rate VC: what are you building? me: Decentralized deep learning powered vertical farming using quantum computing on the blockchainfor onions

dartos 2y ago
That’s always how it works with tech investors

hulitu 2y ago

> Artificial Intelligence for Quantum Computing They forgot the blockchain. /s