281–290 of 298 posts
Interesting that this wasn't tested on ARC-AGI. Francois has always said he believed program search of this type was the key to solving it. It seems like potentially this approach could do very well.
My thought as well. How well does it translate into arc agi? If it does well then we have a general purpose super intelligence… so maybe agi?
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What it essentially does is a debugging/optimization loop where you change one thing, eval, repeat it again and compare results. Previously we needed to have a human in the loop to do the change. Of course we have automated hyperparameter tuning (and similar things), but that only works only in a rigidly defined search space. Will we see LLMs generating new improved LLM architectures, now fully incomprehensible to hu…
If I understood, isn't this software only as useful as the llm powering it is? It sounds like something very useful, but either I'm missing something or it put into a loop and a validator a "please optimize this code". Useful, but maybe not as revolutionary as the underlying llm tech itself Edit the white paper says this: AlphaEvolve employs an ensemble of large language models. Specifically, we utilize a combination…
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No, I'm saying they have a massive database of solutions (the training set) and don't even bother proving that their solution isn't in there. I'm not claiming something, they are failing to provide some necessary information here
Many of the problems (such as the matmul and packing problems) have existing "scoreboards". It would be quite surprising if so many records had already been broken without it coming to the attention of the people who care about the problem.
The paper does not give that many details about the evolution part. Normally, evolutionary algorithms contain some cross-over component where solutions can breed with each other. Otherwise it's better classified as hill climbing / beam search.
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> And it will start with people are not respected or valued for their work, so they can leave, once left, they will not be replaced or replaced lower skilled folks and at some point that position stop existing altogether. Automation changed farming for the worse? Farmers today are not respected / valued for their work? Farmers were replaced with low skilled labor? Do you think the job of a farmer (aka "food grower")…
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…
I get the opposite impression. If anything software developers get more respect than they deserve.
The following algebraic point of view could be utter hogwash, so I might embarrass myself... but if you think about it, the "merge" operation is isomorphic to the product in a free commutative monoid (over a large number of generators, otherwise you can use Counting Sort). So sorting is all about computing a bunch of products (merges) in the optimal order. Now consider mergesort, insertion sort, Timsort.
This is great. But how incremental are these advancements? I picked one at random (B.2 -- the second autocorrelation inequality). Then, I looked up the paper that produced the previous state of the art ( https://arxiv.org/pdf/0907.1379 ). It turns out that the authors had themselves found the upper bound by performing a numerical search using "Mathematica 6" (p.4). Not only did the authors consider this as a secondar…
Merely from your telling, it seems it is no longer "not worth the effort", as "the effort" has been reduced drastically. This is itself significant.
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Merely from your telling, it seems it is no longer "not worth the effort", as "the effort" has been reduced drastically. This is itself significant.
This advance likely uses more compute than the authors in 2009 could have imagined. It most certainly is not drastically reduced effort.
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This advance likely uses more compute than the authors in 2009 could have imagined. It most certainly is not drastically reduced effort.
That assumes that compute = effort, which is not how most people would interpret it I think.
If you prefer to think of human effort, there was also immense human effort building the models, the needed infra, assembling the data to train on, etc. There's usually 1000+ specialists on projects like this (see the last chat gpt paper author list, which took pages and pages as an appendix).
There is no way I can think any of this result was anything more than a massive effort, costing 10s to 100+ millions of dollars.
Go ahead and explain how this was low effort.