[junon]

Disclaimer, not a biologist. Ex did a lot of work in this area though.

If I understand your query (it's hard to parse), then no, AI is nothing that would help. This is an insanely hard problem to understand let alone solve. You're asking for a cartesian of every possible interaction of every possible enzyme, protein, molecule, etc. which, if it were possible to do with existing tech, it would have been done already.

ML (AI) is, at least right now, fancy pattern matching. Nothing more.

Further, Quantum computers can only run certain classes of programs, at least for now. Also not an expert there but if these two fields have been married in any way it's certainly not been done with any amount of clarity.

Hopefully that's a somewhat sufficient, serious answer. The question itself is very.... uh, r/futurism, if we're being honest. You can't just throw AI and Quantum at hard problems expecting them to just somehow solve them.

[jjcon]

> ML (AI) is, at least right now, fancy pattern matching. Nothing more.

I mean, every problem can be boiled down to some sort of 'fancy pattern matching', the question is really how fancy/sophisticated the solver and how large the problem space the problem. I'm not sure why AI couldn't be helpful here even if the convergence of the solver/problem space are still many years off.

[bawolff]

That's basically equivalent to saying, by the church-turring thesis computers can solve any solvable problem, therefore it can probably solve the problem at hand.

Which is technically true, but as a pragmatic matter doesn't really tell us much about if, when, or how the problem will be solved.

[jjcon]

Exactly - I’m not claiming a specific timeframe for AI to be helpful in this area - just pointing out that the claim that it is, ‘just fancy pattern matching’ isn’t limiting to its utility and that in theory it should be able to contribute here.

[taneq]

s/computers/engineers/g and your post still holds true. Predicting when we’ll solve unsolved problems is just hard.

[Andy_G11]

Thanks for your response. I did chemistry and physics and uni (almost 30 years ago now) and I remember how complex some of the computer modelling that was done at the time was (even for very simple things - I think we looked at a model of what happened when a proton and a hydrogen atom came into close proximity).

Since then things have advanced hugely - both in biochem and in computing - and I was curious to see what might have been done. Also, hard science is fundamentally pattern recognition, isn't it: it requires that given the same inputs, the same output is consistently delivered.