Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

LLMs reward expertise

seangoedecke.com

Post reply on HN
Print view View original

51–60 of 606 posts

Re: LLMs reward expertise

#51

Post by bonoboTP »

neilv wrote: post #44

> In the 2010s, if you had technical gaps (say, you couldn’t write CSS), you had to either rely on a skilled colleague or just hope that the answer to your exact problem was out there on the internet. You could read some general reference/guide/tutorial documentation on CSS, and then probably solve your problem (without searching for "how to center a div", or whatever your exact problem was, and copy&pasting the answ…

I don't think AI use is supposed to replace foundational learning such as reading a C++ book or Python book or CSS tutorial when you're a beginner. You still have to do those things if you want to be a professional or a strong amateur. But many people just want to get the thing done. They don't want to become a mechanic, they just want to drive from A to B.

Re: LLMs reward expertise

#52

Post by bashtoni »

The short version I give to non-technical people who ask me about whether "AI will replace coding" is this: it accelerates you. You can get much further much more quickly.

If you don't know where you're going or how to get there, or even if you're just not paying enough attention, it will get you very far in the wrong direction before you've realised.

Re: LLMs reward expertise

#53

Post by porphyra »

fragmede wrote: post #18
natsucks wrote: post #12

Earlier quoted context omitted.

And what about problems that cannot be one-shotted but helped along?

There was one math proof that was AI generated going around Twitter and the chat transcript to generate it was basically the human prompting "keep going" until it solved it. Tao's chat was fascinating because the questions he was asking belied expert knowledge of the subject that only a handful of people could have asked.

Yup I linked that in my other comment but copy-pasted here for everyone's convenience:

The counterexample of the Dinitz-Garg-Goemans conjecture was basically just "keep going" and finally "enough of partial results. now finish with a complete unconditional counterexample"

https://x.com/DmitryRybin1/status/2079904005652893709

https://chatgpt.com/share/6a60b2eb-0b64-83ee-9c76-7931ca1de0...

Re: LLMs reward expertise

#54

Post by bonoboTP »

colechristensen wrote: post #30
fragmede wrote: post #18

Earlier quoted context omitted.

There was one math proof that was AI generated going around Twitter and the chat transcript to generate it was basically the human prompting "keep going" until it solved it. Tao's chat was fascinating because the questions he was asking belied expert knowledge of the subject that only a handful of people could have asked.

Yes, we're in the low hanging fruit stage where folks can just say "here's the problem" and "keep going" until a result is found and it will work sometimes. The low hanging fruit will run short. Ultimately mathematics is a field of subjective selections of problems and proofs as beautiful and interesting. Machines absolutely will struggle with what to study, what theorems are desirable, and when do be done with a pro…

> Machines absolutely will struggle with what to study, what theorems are desirable, and when do be done with a proof

And why do you think this would be the case? I'm not talking about today but in 1-2 years. For reference o1 was released less than 2 years ago, and we've had reasonable coding agents for 9 months or so.

Re: LLMs reward expertise

#55

Post by cyberax »

Yes. This is called the Matthew Principle:

> For to every one who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away.

Re: LLMs reward expertise

#56

Post by nullsanity »

neilv wrote: post #44

> In the 2010s, if you had technical gaps (say, you couldn’t write CSS), you had to either rely on a skilled colleague or just hope that the answer to your exact problem was out there on the internet. You could read some general reference/guide/tutorial documentation on CSS, and then probably solve your problem (without searching for "how to center a div", or whatever your exact problem was, and copy&pasting the answ…

[dead]

Re: LLMs reward expertise

#57

Post by nullsanity »

randysalami wrote: post #15
postalcoder wrote: post #4

Not sure I agree with this. The math guy at anthropic's prompts are essentially: "suppose you’ve gotta resolve the $CONJECTURE, like absolutely have to, everything depends on it. think really hard, and try to come up with a bunch of ideas to try. but remember to trust yourself and not necessarily in conventional wisdom!!" https://claude.ai/share/25740bd5-aa97-4bd7-bf58-c4df3793fda7 https://xcancel.com/__alpoge__/stat…

LLMs are a collection of biases. Humans are also a collection of biases. So we project our biases as input through the biases of an LLM and get an output. Hence why I think getting optimal output requires being an optimal person. And in that sentence there are many points of expression. Finally, we train our LLMs on who we are. Another reinforcement of biases.

[dead]

Re: LLMs reward expertise

#58

Post by pianopatrick »

This feels like a moment in time, not the end state of AI.

Like I read there was a time when teams of people + AI could beat pure AI at chess. But that these days, pure AI wins.

For all the things people say about "how AI works" you have to add the missing piece "how current AI works".

Re: LLMs reward expertise

#59

Post by bonoboTP »

walrus01 wrote: post #29
bonoboTP wrote: post #10

Earlier quoted context omitted.

Many, including myself, report having a lot of success with braindumping and not structuring anything. Just talking into speech recognition for 2-10 minutes as a stream of consciousness about what my context is, what I want, what I know already, what I have a vague hunch about, how it fits into a bigger picture, what aspects are most important to me, any footguns I already know about, really like having a chat with a…

I don't completely disagree with the concept of giving a free association thought process ramble into context. But I also bet that when you start getting it to actually generate code and link modules of things together, subroutines, functions, code structure and filenames, you still pay attention to what it does and you guide it into the architecture that makes logical sense to you.

For real work yes. For personal projects, less and less since Fable came out (probably the same if true of the other frontier models). You can get a lot done if it's just some one off, or a personal tool, even without looking at the code, just trying the application. Frontier models now automatically test it before handing the thing to you, they take screenshots, they fix the superficial issues themselves. To get something up and running, it's enough to send chat messages.

Re: LLMs reward expertise

#60

Post by foolswisdom »

bonoboTP wrote: post #28
postalcoder wrote: post #4

Not sure I agree with this. The math guy at anthropic's prompts are essentially: "suppose you’ve gotta resolve the $CONJECTURE, like absolutely have to, everything depends on it. think really hard, and try to come up with a bunch of ideas to try. but remember to trust yourself and not necessarily in conventional wisdom!!" https://claude.ai/share/25740bd5-aa97-4bd7-bf58-c4df3793fda7 https://xcancel.com/__alpoge__/stat…

It depends on the levels. People with differing fitness levels and ages run at very different paces. Now, do cars make them more equal or less? On the bottom end, the tide lifts all boats. Most healthy people can learn to drive and will drive "fine", they get from A to B. Out there in the city streets the car flattens the differences, everyone roughly takes the same time to get from A to B in a car. But at the top of…

So you're saying that it depends whether you're measuring "success at task X" (where in average everyone improves) vs comparative success (where people with knowledge can do far and away better at specific tasks).
Post reply on HN