> Many graduate students (I know) are having a crisis if any of their research worth it? If AI can (or will) do everything, what's the point of doing experiments and all? This will eventually deter a whole generation of curious minded students from research.
we stumbled into a way of brute forcing intelligence with gradient descent.
I genuinely enjoy doing this, it's really fun to think critically about what an author wrote or how a particular approach works.
But it does make you wonder, why bother? Probably a frontier model could one shot my algorithm in a day or less. It's incredibly depressing. At least I'm not forced to use it now, but I fear I will have no choice after I join academia or industry in the future.
Those who think it's me or the machine will fail.
Those who realize how much you can accelerate your research with the help of AI will succeed.
> Those who realize how much you can accelerate your research with the help of AI will succeed.
This is only true up until a point. If I treat a mid-sized model (say, Qwen3.8 Flash Next) like a pair programmer, then yes, it accelerates my work.
But I can already see the next stage with Fable: If I give it a couple of paragraphs of spec and $50, then I can just leave the room and go wash the dishes. I learn nothing, I participate in nothing, and I bring nothing to the process. I am no longer succeeding at all. Fable's succeeding without me.
Now, in this model generation, Fable starts getting sloppy after a few thousand lines. I can still build better at scale.
But I don't expect AI to accelerate humans or improve our productivity for long. I can already see the first signs of a future where the AI doesn't need us for anything at all.
Software has always progressed this way, lots of devs back then would work on business websites that have been 99% replaced by wordpress, squarespace and instagram.
I'm sure it's the same with research, you're going to tackle problems that would have not been worth the effort or outright impossible without AI. The old stuff that you'd work for months, yeah that's going to be a prompt away.
Yes, but, in the last week we saw an AI lab front-run[1] the research of mathematicians doing what you suggest. The lab threw something like $15M of compute at a problem and the researchers were able to spend nowhere near that. I think the authors are more concerned about that kind of asymmetry and race to publish the results.
[1] - I am not going to debate whether that was deliberate on the part of the lab or if it crept into training data, etc. I don't know and don't think it matters towards the point of the authors here.
It didn’t lead to a lot of people having a wildly successful career, it lead to a lot of people getting burnt out, exploited, underpaid and generally disillusioned.
There will be a lucky few, who have the benefit of being given the space to work alongside. The vast majority of people will (unless we change things) simply be made to take whatever the machine outputs and call it a day.
So many people who are excited about AI making them more productive are, I think, drastically overestimating how much value they are adding to that process.
It biases maths and theoretical physics towards the rich.
That one thing that was free.
If you set a wrong foot and start trusting the model outputs, you can waste years searching for nothing.
How can someone realize this? By getting proper research training, failing, and learning from mistakes. For people beginning their research, it would be really hard to make decisions to move forward.
If only though, because:
> There will be no curiosity, no enjoyment of the process of life
You must be new here.
So I started saying that it only made sense to focus on problems whose solutions would be useful immediately. I even emailed my supervisor about it, arguing that our efforts were “pointless” in the sense that AI-related problems were much more pertinent and had to be prioritised.
My supervisor thought I was bonkers. I still have the email, though. Quoting myself from April 2015:
> By 2030-2040 we will have enough computing power to simulate a human brain neuron by neuron. Once we manage to create a human intelligence we will be one little step away from super intelligence: just set the intelligence to modify itself and see the exponential growth in action. Our human intelligence is bounded by a number of biological factors (e.g. size of a skull) and even the smart human who has ever lived will appear to be a primitive ant to a supper intelligence (machine intelligence will also have perfect motivation). There is plenty of literature on this if you are interested in discussing this further. > > What does it have to do with research in pure maths? I can say that research in pure maths which won't come handy in the next 60 years is just wasted effort. The super intelligence will be able to do maths way better than humans. I believe a lot of current efforts should go into researching of artificial intelligence (or areas to do with AI) instead rather than the pure maths. I want to be proven wrong but most mathematicians I interact with are too narrow-minded to counter me and they just laugh about even contemplating the above. Frankly I am myself so perplexed that I take the above seriously, but I do and it's hurting my motivation.
I'm quite curious what my supervisor thinks of that email now.
And then to get retorts of "it's just just rich techies that want to find 'meaning' in their jobs while millions starve in the third world". Why would we expect the most wealth concentrating technology in history to lead to mass benefits for those in the 3rd world?
This is a very disrespectful way to make a point about acting with integrity.
You should consider that maybe your views on what makes something ethical or moral are not universal -- and that coming to a discussion with the assumption that your position is the only valid one is not conducive to convincing others who disagree with you.
I now realize many people have different tolerance level for this.
Just compare with the comments on https://news.ycombinator.com/item?id=49639408
To use a metaanalogy from chess (once again), mathematicians play the opening game, and builders play the end game. AI is sort of a middleman connecting human understanding to applications.
I think there's a Technical argument to be made that openAI is a threat to the game itself. For example, could it have produced the navier-stokes counterexample without human inputs? since it seemed to have used the much gossiped research strategy "C" and "D", you can't absolutely be certain that Son of Astra (son of altman?) was magicking an unknown unknown from nothing (sorry to cue Rumsfeld). You have got to wait for the other five problems to be solved after general boycott
Subpar PR engine of the OpenAI leadership might kill the pipeline of inputs that they won't admit they still need in this dreamtime before "recursive self-improvement". You can call that emotional. Personally I would rather accuse mathematicians of "preferring local models that believe in the usefulness of unidentifiable individual contributors, and the uselessness of named generalist managers (ie the prompt writers at oAI)"
Big man tlb likes to say that science might be dead but engineering is just getting started. Navier-Stokes is the hammer of the nail in the science coffin. It kills science by killing the prestige of science. The engineers have to imagine that it's likely they will now get all their design ideas from the hypothetical future datacenters.
At the current rate of advancement that phase will last, what, all of 6 months if we're lucky?