TBH, I am waiting for Mathocalypse-level progress in biology and medicine, but I guess that's not happening as fast, because it's the real world, human lives, etc., mostly etc.

Math is completely abstract and the base rules and mechanics of it are some of the most clear cut and formalised because that’s the entire point of the subject.

Biology is the complete opposite of that.

Indeed, actually, one of the limitations preventing AI from making more contributions is humans. Human emotions, laws, morality, responsibility, and so on are all part of these limitations.

I've always thought openai could actually create an agent that can control various physical robotic arms and things like that, and then continuously iterate on solutions that can participate in the real physical environment. This could accelerate automatic iteration for many things that require human operations, such as complicated experiments, assembly adjustments, and testing.

Otherwise, AI is always trapped in virtual systems and still needs human intervention. But even though AI is already very powerful now, there is still a limit to how much humans can handle or assign tasks. Many times, AI has already finished processing something, but I don't even have time to assign the next deeper level of tasks.

People hope AI can improve productivity, but at the same time they're afraid of AI actually getting involved in reality, while the valuation of the entire AI industry is so high.

This kind of wanting to move forward but not moving forward makes humans especially uncomfortable.

I expect that AI use in the more axiomatic kinds of research will be well in advance of sciences that have a heavy, messy empirical foundation, like biology.

first math; now its first integral w.r.t. time: physics, then second integral: chemistry, then third: biology

finally, us

That plus organs on a chip could be scalable and generate interesting data

I might be wrong, but I expect robotics to come before Biology. At least robotics is much easier to verify, most humans can look at a robot and let you know if it is working correctly or not.

Oh I'd hope we can do better. Cures with only theoretical evidence and an inscrutable explanation for why they work sounds terrible.

Keep waiting

Specifically, it's because the verification loops are much longer in applied sciences. In biology you need to wait for wet lab experiments, clinical trials, regulatory steps, etc. before you can call something "solved".

Since sequential steps are slow, I think we're going to see massive increases in parallelization. I'm not sure how the regulatory frameworks will keep up honestly.