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AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

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251–260 of 298 posts

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#251

Earlier quoted context omitted.

What about brownfield development though? What about vague requirements or cases with multiple potential paths or cases where some technical choices might have important business consequences that shareholders might need to know about? Can we please stop pretending that software engineering happens in a vacuum?

The thing with vague requirements is that the real problem is that making decisions is hard. There are always tradeoffs and consequences. Rarely is there a truly clear and objective decision. In the end either you or the LLM are guessing what the best option is.

Yes, decisions are but they need to be made. Ideally shareholders will be given as much context so they can decide. This communication is as vital as having good programming skills imo. Your beautiful code means nothing if it does not adequately solve the business problem

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#252
post #95
post #90

Earlier quoted context omitted.

I have not read this linked article, but your comment made me recall a discussion about a speed up of CUDA kernels presented by Sakana AI Labs. The researcher Ravid Shwartz Ziv at NYU posted about it on LinkedIn [1], and here is the Twitter post of interest [2] """ Yesterday's news about Sakana AI Labs provided an important lesson for all of us working with AI agents. Their announcement of an AI system that could sup…

lmao this is exactly the kind of stuff I always see from Claude. It’s like adding a Skip() to a test and declaring it works now. “Well it’s a lot faster, I met the criteria of my TODOs cya” I’ve seen it so much I kinda doubt it was “inadvertent” because they’re like seemingly intentional about their laziness, and will gaslight you about it too.

Well you forgot to fully qualify your linguistic basis and semantic interpretation of the text of your wish to the great genie bottle.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#253
post #208

Earlier quoted context omitted.

Is it new? I'm getting mixed messages from the posts here. On one side there is evidence that 48 and 46 multiplication solutions have been known (and could have found themselves in the model training data). On the other side I see excitement that the singularity is here. If the latter were the case surely we wouldn't be reading about it in a published paper, we would already know.

Let's assume that the 46 multiplication algorithm was known, prior to AlphaEvolve re-discovering it. AlphaEvolve still has made an improvement to a performance critical area that has had likely had thousands of engineer-hours put into it. None of those engineers apparently knew about the improved algorithm, or were able to implement the algorithm. This is empirical evidence of an LLM outperforming its (domain expert)…

Isn't this like comparing a human historian to Wikipedia though? Of course the knowledge in Wikipedia will in most cases beat the human. However, that's not the kind of thing we're looking for here.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#254
post #99

Interesting to see Terence Tao in the authors list. I guess he's fully ai pilled now. Did he check the math results?

He is not in the author list, just acknowledged by the authors.

Maybe this is interesting: the whitepaper says:

> Most of these discoveries are on open problems suggested to us by external mathematicians Javier Gomez Serrano and Terence Tao, who also advised on how to best formulate them as inputs to AlphaEvolve. This highlights the potential for synergistic partnerships between AI-driven discovery engines like AlphaEvolve and human mathematical expertise.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#255

> AlphaEvolve achieved up to a 32.5% speedup for the FlashAttention kernel implementation in Transformer-based AI models > In roughly 75% of cases, it rediscovered state-of-the-art solutions, to the best of our knowledge. > And in 20% of cases, AlphaEvolve improved the previously best known solutions These sound like incredible results. I'd be curious what kind of improvements were made / what the improvements were.…

Remember that GPUs have cache hierarchies and matching block sizes to optimally hit those caches is a big win that you often don't get by default, just because the number of important kernels times important GPUs times effort to properly tune one is greater than what people are willing to do for others for free in open source. Not to mention kernel fusion and API boundaries that socially force suboptimal choices for…

Hey, do you have any suggestions for resources to learn more about this kind of custom optimisation? Sounds interesting, but not sure where to start?

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#256

Why do I get the feeling they are doing the "IBM Watson" thing where different efforts are being put underneath the same brand name? Not saying it is that egregious, but it's a slippery slope from "well, it didn't do all these different things out of the box, unsupervised".

One thing I've really internalized since IBM Watson is that the first reports of any breakthrough will always be the most skeevy. This is because to be amplified it can be either true or exaggerated, and exaggeration is easier. That is to say, if you model the process as a slowly increasing "merit term" plus a random "error term", the first samples that cross a threshold will always have unusually high errors.

For this reason, hype-driven/novelty-driven sites like HN usually overestimate initial developments, because they overestimate the merit term, and then underestimate later developments - because they now overestimate the error term from their earlier experience.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#257
post #210
post #204

Earlier quoted context omitted.

And the invention of AGI will have the same impact as the electricity, i mean, they're both inventions, right ? I can't wait for all these billions of new full time jobs coming to replace the current ones. Farmers couldn't be replaced by low skill labor because they are low skill. Farmer didn't stop existing, but we went from 80% of the population farming is to 1-10%. If farming automation had happened in 1800 when 8…

Great points. Besides if one look around even today beyond people who somehow still succeeding at software hustle, there are already tons of people fallen off IT gravy train. A lot of manual testers who would make decent living are now eliminated by automation. Software document writers jobs are kind of gone. Developers are supposed to create document themselves on Confluent wiki etc. A lot of prized SAP consultants…

There are two ways to think about your work in IT, one is as a person who really understands how to use a particular technology, and the other is as someone who can figure out how to use technology in general to achieve some particular end. Anybody who picks the first path might have a very well paid career for the few years that that technology is relevant, but will eventually crash out. You need to always be looking at the next thing and keeping your skills and knowledge up to date. Nobody ever guaranteed that Microsoft Outlook admins would have a career for life.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#259
post #179
post #172

Earlier quoted context omitted.

My understanding of the situation is that: 1. Waksman's algorithm works in any commutative ring admitting division by 2. 2. In particular, it won't work when the matrix entries are themselves matrices, which means you can't use it recursively to get an algorithm for n-by-n matrices with large n with a better exponent than you get from Strassen's algorithm. 3. The Deep Mind paper is annoyingly unexplicit about whether…

1. Correct 2. Correct, however you can use Waksman as a basecase and always beat Strassen (though it is not asymptotically better of course). 5. Possible, but even so, there is already an algorithm that will work with 46 real multiplications (and some divisions by 2). The real numbers are commutative and admit division by 2.

My point about #5 was just that their emphasis on "complex numbers" isn't necessarily (and I think probably isn't) an admission that their algorithm can't be applied recursively.

If it can be, then it is a genuine advance in the sense that it yields faster large-n matmuls than were previously available just by recursive application of a 4x4 matmul algorithm.

None of which, to be clear, makes it OK that they don't make any mention of earlier work that does 4x4 matmuls over commutative rings faster than their algorithm does. I suspect they didn't check the literature carefully enough before publication. In any case, good scholarship means being clear about what in your work is a genuine advance on what's already known and what isn't, and they failed to do that here.

Re: AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms

#260

Earlier quoted context omitted.

Remember that GPUs have cache hierarchies and matching block sizes to optimally hit those caches is a big win that you often don't get by default, just because the number of important kernels times important GPUs times effort to properly tune one is greater than what people are willing to do for others for free in open source. Not to mention kernel fusion and API boundaries that socially force suboptimal choices for…

100%. LLMs are extremely useful for doing obvious but repetitive optimizations that a human might miss.

One can have obvious but repetitive optimizations with symbolic programming [1].

[1] https://arxiv.org/abs/1012.1802

Strange that AlphaEvolve authors do not compare their work to what is achievable by equality saturation. An implementation of equality saturation can take interesting integrals with very simple rules [2].

[2] https://github.com/alt-romes/hegg/blob/master/test/Sym.hs#L3...

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