Even in good times, CS was poorly matched with the jobs people got the degree for. People put up with the BS because there was gold at the end of the rainbow.
I don't think that it's primarily about jobs. At this rate, CS is going to be the first field to be "solved." By 2030 we'll probably know whether P=NP (like many others, I'm starting to suspect that it does,) and just about every other open problem shall fall, so everything that seemed important to us from first principles will be known.
The same will happen in biotech, pharma and many fields where data is easier to process with ai. Its already in progress. The only fields immune are where the cost of robotics exceeds the cost of humans. Say aircraft maintenance, ,mechanics, etc.. fields where robotics are still way more expensive
The problem with biotech/pharma is that data processing doesn't work if you lack the data to begin with. There are too many holes in science's understanding of how the cell works, how the organism ages, etc., and LLMs can't easily fill these in. Hypotheses can and will be generated, but it will take great lengths of time and comparatively heroic efforts before the picture becomes much clearer.
The contrast with math and CS couldn't be starker, really. Everything that hinges on formal logic or logical relations is done for.
There is a lot more data than one individual can process. Is there something that humans can know and it wouldn't, I pretty much doubt it. But can it do experiments that are biological? Yes it can order it I think; it probably knows where its knowledge is ambiguous.
Hm. I think it depends on two things: (1) how sample-efficient AI can become if CS and mathematics becomes "solved", (2) if AI still sucks on this metric compared to biological brains despite that, can it at least self-play its way to solutions?
Given what AI could do with protein folding, I wouldn't bet on biology being a "no" for AI. It might be, but I wouldn't bet on it.
Likewise, if AI can do mathematics so well it solves "just" all of computer science, let alone other branches of mathematics, if this somehow doesn't lead to AI becoming similarly sample-efficient as biological brains, that's very interesting and will say something nice and surprising about the nature of minds and possibly the nature of being alive.
I think Ai understands biology better than humans because it can correlate everything where humans can never know enough to correlate all. But Ai will not just focus on a solution till it is given a runway to solve and deliver.
Even in good times, CS was poorly matched with the jobs people got the degree for. People put up with the BS because there was gold at the end of the rainbow.
I don't think that it's primarily about jobs. At this rate, CS is going to be the first field to be "solved." By 2030 we'll probably know whether P=NP (like many others, I'm starting to suspect that it does,) and just about every other open problem shall fall, so everything that seemed important to us from first principles will be known.
> https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_c...
Then advances in algorithmic efficacy will be the province of machines, who will act in ways and at speeds that are beyond human.
What room, then, for CS students?
I wonder if biology and theology are picking up students. Those fields, I'd bet, won't be solved within our lifetimes.
The same will happen in biotech, pharma and many fields where data is easier to process with ai. Its already in progress. The only fields immune are where the cost of robotics exceeds the cost of humans. Say aircraft maintenance, ,mechanics, etc.. fields where robotics are still way more expensive
The problem with biotech/pharma is that data processing doesn't work if you lack the data to begin with. There are too many holes in science's understanding of how the cell works, how the organism ages, etc., and LLMs can't easily fill these in. Hypotheses can and will be generated, but it will take great lengths of time and comparatively heroic efforts before the picture becomes much clearer.
The contrast with math and CS couldn't be starker, really. Everything that hinges on formal logic or logical relations is done for.
There is a lot more data than one individual can process. Is there something that humans can know and it wouldn't, I pretty much doubt it. But can it do experiments that are biological? Yes it can order it I think; it probably knows where its knowledge is ambiguous.
Hm. I think it depends on two things: (1) how sample-efficient AI can become if CS and mathematics becomes "solved", (2) if AI still sucks on this metric compared to biological brains despite that, can it at least self-play its way to solutions?
Given what AI could do with protein folding, I wouldn't bet on biology being a "no" for AI. It might be, but I wouldn't bet on it.
Likewise, if AI can do mathematics so well it solves "just" all of computer science, let alone other branches of mathematics, if this somehow doesn't lead to AI becoming similarly sample-efficient as biological brains, that's very interesting and will say something nice and surprising about the nature of minds and possibly the nature of being alive.
I think Ai understands biology better than humans because it can correlate everything where humans can never know enough to correlate all. But Ai will not just focus on a solution till it is given a runway to solve and deliver.
https://archive.ph/bhUVm