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adi_kurian | on: Failing grades soar with AI usage, dwindling math skills in Berkeley CS classes
Do any of said PhDs gain anything positive from LLM usage? Or does it only lead to declining thinking skills in your view?
camelmel | parent | next
Yes, I can churn out a lot more stuff as can most of my peers. Experiments etc are all way faster to run with coding agents. But I think the overall creativity and originality is a lot lower. I think this is what many people are facing, if you don't use LLMs your short term productivity is worse.
layer8 | root | parent | next
There’s the saying that we overestimate what we can achieve in the short term, but underestimate what we can achieve in the long term. Optimizing for the short term is therefore counterproductive if it impairs us for the long term.
eueje | root | parent
“ But I think the overall creativity and originality is a lot lower.

Therein lies the trade off. Your implicit gamble is that you expect machines to continue to get better in the future. What if they don’t?

thedevilslawyer | parent | next
They're incredibly more productive. LLMs are amplifiers, so where they'd have branched and tried out N things, they can easily try 5N pathways of RnD. LLMs are extending the frontiers of science fast -- math -> phy -> chem -> bio in that order.
steve_adams_86 | root | parent | next
In my own experience, the only path I truly gain intellectual benefits is the one where I work closely with the LLM, test very narrow hypotheses, and leverage it for learning over producing.

Trying 5N paths is useful and sometimes yields interesting insights I’ll retain, but it’s not the rich, challenging, deeply engaging kind of process I find I need in order to develop useful knowledge and skills.

So yes it’s an accelerant for people who want stuff from me, but that doesn’t map directly to learning and building skills. I think that mismatching is really important.

chorsestudios | root | parent | next
To help learn I use LLMs to generate practice exams for whatever I'm trying to learn, then on the questions I struggle with have the LLMs explain the logic and point out my mistakes. I haven't been in college for over a decade, this is just for topics I'm curious about and want to learn. For any serious topic I recommend auditing the practice exams with a different LLM than the one used to generate to help reduce hallucinations. Seems to work well for me. I quite like reading the "thought" processes shown by DeepSeek.
tstrimple | root | parent
I don’t see these at odds. Sometimes through working closely with an LLM, N paths emerge. Having it go off and test each with defined metrics to determine which is better is the natural follow up. Even better if you dive into the why it ended up being better which the LLM seems to be able to expose well in a lot of cases.

The part I find weird is all the claims that LLM usage leads to less thinking and exploring and just grabbing the first result. I constantly find myself going off on tangents and pulling on threads when I’m working with these tools. Is it really that different than before when my “peers” weren’t able or willing to be curious about their craft? They didn’t explore other programming languages out of curiosity or for fun? That covers literally 95% of all software developers I’ve worked with in the last 24 years across many domains. To them it’s just a job. Their only goal is to deliver tickets assigned to them and go home. They rarely go out of their way to learn something new unless the company assigns them some mandatory courses. Largely the LLM is capable of producing better and more consistent results than they ever could in the first place.

I don’t know how to cultivate curiosity in the work force. Maybe it’s not possible and you have to filter aggressively at the hiring step. But then your pool of hireable candidates shrinks to a few thousand developers most who are probably not actively looking for work.

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cootsnuck | root | parent | next
I'm hearing different from PhDs. The bottleneck with much research isn't "trying out ideas" so much as it's all the bureaucratic minutiae, grants, mentoring PhD candidates, collaboration with other researchers, etc.

I've heard LLMs can be helpful in limited targeted ways. But not as some kind of "game changing" accelerant.

sandeepkd | root | parent
Understanding in what ways it can be useful and in what ways it can be counterproductive in long run requires a certain degree of experience itself.
intended | root | parent | next
It’s creating a daemon and machine spirit filled world of Warhammer 40k. We already scarcely understand how the world works, but LLM use actively degrades cognitive ability that way it is used by a majority of people (The bringing a forklift to gym analogy).
ElProlactin | root | parent | next
The AI is among us.
xadhominemx | root | parent
To me it is crazy that you are being downvoted. My experience in academia was that an incredible amount of time was devoted to data cleansing analysis, coding, etc., which were completely non-core to the actual underlying academic pursuit.
grey-area | root | parent | next
Data cleansing is a terrible use for LLMs if you want reliable data.
thedevilslawyer | root | parent
There's an unnecessary feeling of fear that permeates any factual conversation on LLM's impact on science and engineering. You can just view the practitioner over the shoulder and see all the things they're able to do in a minute that would have taken days.

The downvotes are just a sign of the times. It's also something to observe and think about..

dosisking | parent
It depends on the field, but an Economist with a PhD is a huge red flag and anything they say should be ignored.

Other fields may be different. YMMV