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This mirrors my understanding when I use Claude code for mathematics. I can have deep discussions with it and it can solve my hairy problems. But whenever we go

This mirrors my understanding when I use Claude code for mathematics. I can have deep discussions with it and it can solve my hairy problems. But whenever we go off the beaten track into design new mathematics, it struggles to make conceptual leaps and find the right definitions. Once I give it my ideas, it is back to its super-human pace and top notch intelligence. This situation suits me fine, since I am anyways more of an ideas person, than a crunching open problems person. But I understand the desperation of my colleagues who mad solving hard problems their identity.

int_19h 5d ago
> Once I give it my ideas, it is back to its super-human pace and top notch intelligence. That's the real benefit of AI today: you can test your ideas almost as fast as you can generate them, in parallel even. If you have a crazy idea that is unlikely to work but has massive advantages if it does, you just set an agent to explore and prototype it while you focus your main attention elsewhere. And so on. It's still GIGO, though! An AI can make a bad idea work (and will do so if you don't carefully prompt it to not be so sycophantic!) but it won't work well. Knowing when the idea is bad and should be abandoned is also the part that currently requires human judgment. That said, given the pace at which models have been improving so far, I can't help but think that this is a transient state of affairs.
socketcluster 4d ago
Yes very much the same situation in software development. The people who prided themselves on raw puzzle-solving ability got hit hard. Those who are idea-driven and architecture-oriented feel like they got handed a superpower. It's quite a big shock at the industry level because the entire software engineering job interview process at essentially all large companies was heavily biased towards well-defined, raw problem-solving under time constraints which is precisely the skill which AI has replaced.
- bharatsuthar 4d ago
  Yeah and companies continue to use leetcode style interviews even today and software engineers keep grinding for them. It's nauseating to contemplate on.

int_19h 5d ago

> Once I give it my ideas, it is back to its super-human pace and top notch intelligence. That's the real benefit of AI today: you can test your ideas almost as fast as you can generate them, in parallel even. If you have a crazy idea that is unlikely to work but has massive advantages if it does, you just set an agent to explore and prototype it while you focus your main attention elsewhere. And so on. It's still GIGO, though! An AI can make a bad idea work (and will do so if you don't carefully prompt it to not be so sycophantic!) but it won't work well. Knowing when the idea is bad and should be abandoned is also the part that currently requires human judgment. That said, given the pace at which models have been improving so far, I can't help but think that this is a transient state of affairs.

socketcluster 4d ago

Yes very much the same situation in software development. The people who prided themselves on raw puzzle-solving ability got hit hard. Those who are idea-driven and architecture-oriented feel like they got handed a superpower. It's quite a big shock at the industry level because the entire software engineering job interview process at essentially all large companies was heavily biased towards well-defined, raw problem-solving under time constraints which is precisely the skill which AI has replaced.

bharatsuthar 4d ago
Yeah and companies continue to use leetcode style interviews even today and software engineers keep grinding for them. It's nauseating to contemplate on.