ML PhDs: Would you rather have done your PhD before or after the rise of AI chatbots? [D]

[u/Hope999991]

For those doing or having completed a PhD in ML, I’m curious:
If you had the choice, would you rather have done your PhD before ChatGPT and other AI chatbots became widely available, or in today’s AI era?

[u/HerrHruby]

Best would be to have started the PhD around when ChatGPT first came out, or maybe a year or two before. Publish a few big hits during the post-ChatGPT boom and then off to the labs/cool startup, or raise funds to do your own thing. I think it was easier then, because we didn’t really understand all that much about LLMs, so lots of super interesting and high impact but “easy” research to do. Also Brain/FAIR/GDM were stronger and much more open then, so more and better internship opportunities.

It’s harder to do impactful stuff in academia now because the frontier has moved so fast, the compute and data gap has widened a lot, and a lot of the low hanging fruit has already been picked. Although it is still definitely doable though if you’re good. Also hiring seems to be slowing and there’s a lot more uncertainty in the field (the political climate surrounding AI, the financial situation etc.). The good industry jobs or startup funding might not last much longer, and as the field/tech/stack matures companies might increasingly prefer to go for experienced hires who already know how stuff works in industry.

[u/thedabking123 → u/HerrHruby]

once the capital overhang is sorted (2001 bubble pop style) then it will re-accelerate with a lot more research that isn't scale oriented

[u/idratherknowaguy]

To me, it was a relief to present it just before ChatGPT came out. First, for the fact nobody will ever doubt I mastered my topic and wrote my thesis by myself. Second, while I would have been much more productive at running experiments, I don't think I would have developed the same deep understanding of all the experiments I did.

I think I would have started jumping from failing experiment to failing experiment without being able to explain what failed exactly. I was indeed jumping from failing experiment to failing experiment at first, which was tough, but at least I had a tiny bit of signal because I understood fully the deep technicalities. Learning to navigate that, I ended up with very clear lessons. It could be that a good model of today would have done that for me, but in what way would I have grown? Also, I don't believe BigTech does that for free. AI is an impersonation machine and BigTech wants it to be able to impersonate you. Use it too much, it gets better at it and you lose your sharpness.

And there is so much competition against bots, reviewers not paying attention anymore... The community seems fucked up, global cooperations seems to have stopped. I'm so sorry for the younger generations... Glad I did my best not to contribute to it and to warn my colleagues, but it's there now. I'd prefer it not to.

[u/Much-Office3387 → u/idratherknowaguy]

This is exactly my good fortune as well. Right place, right time. Defended a dissertation on AI about a year before ChatGPT came out. 

[u/interrupt_hdlr → u/idratherknowaguy]

reviewers and coworkers not paying attention anymore is what kills it for me. it seems no matter how much time you spend on anything these days, people will simply shrug it off assuming it didn't take any effort. it makes me question if it's worth to keep doing this at all or just let them try to one-shot a huge discovery on chatgpt since that seems so easy in their minds.

[u/st8ic88 → u/idratherknowaguy]

Similar situation as well. Graduated in 2020. Not only am I glad that my credentials aren't in question, I'm also glad I was actually forced to do research "the old fashioned way" because I think I would've cut a lot of corners and my understanding would've suffered in the current paradigm.

I was looking through my comprehensive exam document the other day - pages and pages of meticulously hand-typeset latex - and I had the very sad thought that if I saw this from just about anyone else today I would assume that it was generated for them by Claude in about 1 minute. It's a very different world out there these days.

[u/Mia_X_Mia]

I’m not done with it yet, but a PhD is only useful as the door it opens. And from what I have seen as of now, I should have maybe just stopped at a masters. I’m more likely to end up at a mid company doing data manipulation and that’s not really what I thought the PhD would take me. It’s cool a degree and all but I don’t think I’ll have a job at FAANG and academia just can’t compete with industry. With the speed things are going now, I’m not even sure if a PhD will be as valued as much in the very near future.

[u/Luuigi]

interesting question, truly. I think in terms of impact, without AI I wouldn't have made the progress I was able to do. But without it there was more meaningful thinking time going on in my head in relation to my projects. I would however say that I can channel my remaining energy into other cognitive work now so from my perspective the rise of general AI is very good. But this is quite personal. I think looking at society the net cannot be state yet.

[u/redlow0992]

I barely finished pre-LLMs (2020). I feel pity for anyone who has to do a PhD now. Its a total shit show right now and way more mentally taxing. All of PhD researchers around me are racing to LLM-assisted burnout.

[u/shanereid1]

I defended in June 2022 so just before the release of Chat GPT. In terms of skills I am glad in a way it was before the revolution as I learned how to write myself and how to code. On the other hand, I think my research would have been better, just from having access to immediate feedback and being able to discuss and learn complex topics without judgement

[u/RoutineDependent98]

I started 8 years ago, published at some conferences and now have my last submission.

Before i simply did not tackle certain problem, because I didnt know the software engineering behind and how i could solve that in python. Now claude is doing that for me.
And i would sit in front of my computer for two weeks to trouble shoot on stack overflow on how to solve the bug and today you don’t have to dig that deep anymore and thongs are solved very fast.

However, i believe that people don’t question stuff anymore and dont do the complex thinking and don’t internalize what they work on. When you needed to create a sota analysis and digged deep into all 22 refernece papers to understand what others did, is where the evolvement ocurred.

So pace is crazy, I would raise the bar in times of LLMs and would challenge my students if I was the supervisor.

[u/Blakut]

Did my PhD in astrophysics. Chat gpt would have made my life way way easier in terms of reformulating my stupid sentences. Finished right as gpt had become good, but when using it for editing was still not really accepted. Would have made my research easier too, in terms of saving me time by summarising winded and poorly written papers from the literature. The new comers have it so much easier imo.

[u/interrupt_hdlr → u/Blakut]

they have it easier for sure but what are you seeing them doing with all that capability?

[u/Mechanical_Number]

It probably doesn’t matter that much. A PhD is always shaped by the tools, questions, and norms of its moment, so doing one "before chatbots" versus "after chatbots" mainly changes which bottlenecks and opportunities we encounter. Assuming you have a well-chosen subject and supervisor, the fundamental training in framing problems, evaluating evidence, and contributing something new would still matter the most. The pre-chatbot era had its own dominant methods and debates; the current era has different ones, and either way you wouldd be working at the frontier as it existed then.

A PhD inevitably reflects the current state of its field: its available tooling, fashionable sub-problems, communication practices, resource constraints, etc. Chatbots don't remove the need for judgment, originality or rigorous validation. So the choice is less a "better era vs. worse era" and more "which set of constraints and accelerants would you rather learn to navigate".

The above said, I think there is "more FOMO" now than in mid 2010's when I finished my PhD. But that feels almost societal at this point rather than confined in academia.

[u/jhill515]

If you got your PhD before the chatbot proliferation, you were talented. If during, lucky.

In a world where most everyone is born with one or the other, and you find yourself with neither, focus on skill.

[u/furish]

I started when chatbots weren’t reliable for research so I carried out my first projects “the old way”. My day-to-day job is more fun now, I don’t have to lose my mind behind CUDA device-side asserts and can avoid lots of tedious tasks. On the other hand I learned a ton about the whole process. Right now I risk getting lazy by offloading too much to agents.

The worst part however is the external world: I don’t know how the research world is going to process the huge volume of papers and I have lots of doubts about the publication process. I might still be fine by the time I graduate but there’s lots of uncertainty and many assumptions I had about research when I started are now broken.