What is the breakthrough? There is no mention of the problem solved, nor the accuracy of the quantum solution, nor the amount of classical computing resources needed for a non-quantum solution.
The engineering probably has some cool novelty: 39 qubit and 10 million layers is a very large circuit. But simulating a large circuit is very different to achieving a quantum computing breakthrough in CFD.
I do get where you are coming from. Indeed, it makes little sense to use Julia for lots of machine learning when PyTorch and Jax are just so good. And it sounds like you don't want to use Julia, so who am I to try and convince you? Python/R are capable languages.
But, there are still reasons I reach for Julia.
Interesting packages where I prefer Julia over Python/R: Turing.jl for Bayesian statistics; Agents.jl for agent-based modelling; DifferentialEquations.jl for ODE solving.
I would much rather data-munge tabular data in Julia (DataFrames.jl) than Python, though R is admittedly quite nice on this front.
Personally I reach for Julia when I want to use one of the previous packages, or something which I want to code up from scratch, where base Julia is much preferable to me than numpy.
Janet seems really tempting for tiny footprint, distributability etc.
But I'm currently leaning towards to Racket just because it would be more or less compatible with a whole host of Scheme books that I'd like to read (The Little Schemer/Typer/Learner, SICP, Functional Differential Geometry).
Does anyone familiar with Janet know if those books can be easily worked through with Janet for a newbie Lisper?
Two big hurdles for ML: a) explainability b) accountability.
ML-enhanced development neatly circumvents this: explainability and accountability is passed on to the developer. This includes bugs and license infringements.
I have no qualms about ML tools in development. But so long as the buck stops with me, I prefer to write from scratch.
Traditional chess engines excel at tactics. But most chess tactics are brute forceable, and traditional chess engines are normally brute force behemoths.
Large language models have tradtionally been very weak at brute force computing (just look at how bad they are at multiplicaion of large numbers). If it can somehow excel at something which typically involves computing power like chess tactics deep into a game well after a novel position has been reached, then put me down as impressed.
There is much more to generative models than building out language models and image models.
Generative models are about characterising probability distributions. If you ever predict more than just the average of something using data, then you are doing generative modelling.
The difference between generative modelling and predictive modelling is similar to the difference between stochastic modelling and deterministic modelling in the traditional applied mathematical sciences. Both have their place. Neither is overrated.
If you answer all the questions after reading all of them, you could only get only question 100 wrong and get the other 99 correct, so reach a score of 99/100.
If you answer only questions 1 and 2, you get the answer to 100 right too, so you could score 3/100.
In the latter case, you could score 3/3 too, depending on how the examiner decides to mark it.
I used to use a Vimium-FF (a Firefox version). I love the better browsing ergonomics.
But, after some thought, I realise that allowing such extension simply requires trusting a third party app access to so much of my personal information. They (understandably) need the ability to read every page I browse. Vimium-FF even requires clipboard access.
I do believe the authors have the best intentions. But the amount of trust I need to have in order for a third party app to have so much access to some of my most confidential information (online banking, emails etc.) is very very high.
> Still find it nuts you need to operate the system at 0 kelvin. I assume if we had super efficient cooling equipment (not LN2) we could also do superconductors on a small scale?
Neutral atom quantum computers (the type outlined in the article) work at room temperature.
Superconducting qubit based quantum computers do indeed require cooling to these levels, though.
Apologies for making a more meta-comment. But I think the title of the post title should be the the paper title "Attention Is All You Need" as per the HN guidelines.
"...please use the original title, unless it is misleading or linkbait; don't editorialize." [0]
[0] https://en.wikipedia.org/wiki/Indiana_Pi_Bill