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simianwords • today at 3:30 PM • 1 reply • view on HN

> Private control of frontier LLMs is potentially dangerous.

The author spends a lot of time trying to suggest that LLMs are not the end all be all and humans are still needed for understanding etc. Fine. I understand.

If it is so the case that LLMs don't help that much, surely it doesn't matter if LLMs are privately controlled?

How come LLMs are important enough that private control matters but also not enough for actually advancing mathematics significantly on its own?

In other words, you are almost always better off with LLMs even if it is privately controlled. The mathematics community can just ignore LLMs for the base case or use ChatGPT if they want. In either case, it is strange to suggest that things will get worse for them. Its as if they don't have the coordination or agency to adapt.


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lukehandcool • today at 3:57 PM

This is my understanding of that part you quoted. It's not really a statment about open vs closed models (which is another very important topic, personally I think open is the only way forward). What he is suggesting is mathematicians will use llms for their research because llms are transformative for math and research. As they work on a problem, OpenAI will put their strongest model on their biggest cluster and synthesize all the work by the individual mathematicians to arrive at the answer.

One big problem here is that OpenAI would be hoarding this ability by 1) not releasing their top models for public use,as we have already seen them do, and 2) limiting the capability of the public API, which we have also seem them do.

This not only kills incentive for math, it means that OpenAI becomes the arbiter of math and research for the world. The research that will be done is the research OpenAI decides to do.

This seems very dangerous to me.

Another path forward is distributed local models. Professors can do research on their HPC machines, individuals can have full access to their models. It's a much more democratic approach.

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