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Comment by reasonableklout | Hacker News Reader

But what does the human researcher do in this future?

If they are not needed to understand the result, then what's their role? Asking the right questions? But how will they know what questions to ask if they don't have a deep understanding of the domain earned by sweating the details themselves?

And how long will they be needed to ask the right questions, how long until AI can do that too?

> Software has always progressed this way

These platforms took on the order of a decade to mature, during which people had plenty of time to learn what's next. With LLMs we went from one-shotting functions in 2025 to entire projects just over a year later.

What do you think you will be working on in a decade?

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> Asking the right questions? But how will they know what questions to ask if they don't have a deep understanding of the domain earned by sweating the details themselves?

The right questions are very simple to ask.

How do I get food. How to cure aging. How to turn lead into gold. How to fly high. What is the ultimate theory of physics. Are there any odd perfect numbers. Is there a soul.

We have reached complicated questions requiring deep knowledge because we tried to solve the simpler ones and reached obstacles. For example to solve alchemy we had to develop nuclear physics (and in the process we got chemistry). If one has a genie able to solve questions, you won't have to think about the complicated ones because the genie will.

I think it will be like how a lot of people know how to code in python but have zero understanding of assembly or how a cpu works. As a researcher you'll accept there's this low level stuff that if you want you can dig into but isn't worth your time, like looking at the generated ASM isn't.

You're exaggerating the LLM progress a bit but yeah progress has been crazy. Yet not much has changed right? We mostly have the same jobs, just code wayyyy more than before because things that wouldn't be worth it now are worth it.

10 years from now I have no fucking idea. But I'm sure in the meantime those who leverage AI will do better than those who yell at a cloud.

True, surprisingly not much has changed in software despite the incredible progress. I think it's partly because much software is an "open loop" system where what you build depends on running the software on client computers, devs talking to users, etc. There are still things that only human engineers can do. I worry it is less so for poor mathematicians, where math is "closed loop", and the exchange of capital into research progress is more liquid.

I can't help but be pessimistic about AI moreso than any other technology. Why? I used to be excited to learn the next big thing because I knew it would unlock much more things to do and get paid for, and there would always be more for me. With AI, the new things come nearly too fast, are not very deep or satisfying, and it's hard to see that there will always be a place for me. And so while I leverage AI in my day-to-day, I will yell at the cloud, too.

I think in a few decades when there are more humanoid robots than humans we'll likely have skynet, so I'm pessimistic in a way lol.

But in the near future and on a personal level I think we'll need to adapt and pivot but we'll manage.

They are needed to guide the research in fruitful directions and understand the result.

LlMs don’t understand, they generate, though they have fooled a lot of people who should know better.

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