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Uninformed speculation from the rationalist cult forum that wants to will science fiction into reality.

If you actually look at the trajectory of post-LLM AI developments, the successes have all been in areas where the major labs have some way to get their hands on s**tons of correlated data. That's why they're pushing into maths now. I see no reason to assume that will be replicated with biological science data, which is extremely proprietary and not required to be exposed as part of the end product. It doesn't even have an equivalent to a black market in piracy like books or movies did. This data was not valuable to the public before now.



The successes are in areas where you can get AI to execute an iterative loop autonomously. Try, fail, refine, retry - succeed eventually.

Coding is, inherently, quite amenable to that. Is bioscience?

They're certainly working on making it so:

https://www.anthropic.com/news/model-hardware-standard-resea...


We're saying the same thing. The ability of the system to iterate is dependent on the digitizability of its artifacts, and its familiarity with such artifacts through its training data.




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