Hacker News Reader

Comment by 5555watch | Hacker News Reader

I'm probably a weird outlier. Coming from academia, it's ranging from 1x to infinity-x (as in, certain tasks wouldn't even be touched if not for AI).

For stuff that I'm used to (R) I can write nice and compact spaghetti (long %>% pipes). I'm not comfortable when a working script doesn't fit the screen (plus a few scrolls max). My style is probably easy only to me. When I teach, I don't teach it in particular.

AI gives me thousands of lines of codes for those. 10k once. It's cool if it suffices to source it all, but working with that is not pleasant.

But if I can reproduce a paper in a one-shot (it used to be an hour, but recently it got so much better), that's a task that would not have been even attempted years ago. And I'm talking about a methods paper with no available Github (or, as often happens, when the existing Github is useless)

View on HN

I would have said 0x to infinity-x. Some stuff I think it would be a good idea and waste a bunch of time and then give up and just write it myself. And like you say, there’s lots of stuff I would just never have done, basically any kind of front end for example, if I didn’t have an LLM to do it.

I also do mostly research or one-of script development, for which I find LLMs less useful, as I want simplicity and I want to understand exactly what is happening. The only time I find LLMs help really there is if there’s some part I can abstract away like writing and interface to an api or something.

For me, I find the biggest benefit is that I actually do all the things I know I’m supposed to do, but usually don’t bother if I’m the only audience.The first time a model asked me, “do you want me to wrap this in an easy to use CLI?” I was like, “Yes. Yes I do.”

Interesting. Framing it as 1x to infinity-x matches my experience too. I've have good success with it reproducing papers with existing code, but not such much with one-shotting new code. Do you have any particular setup for this i.e. special validation prompts or multi-agent stuff or do you just ask something like reproduce paper X until it gets results Y?

I used to chat with "the paper" until both me and the AI were roughly on the same page at what's happening. It's important, as a "full read" of the "full paper" is not always used efficiently if not discussed, I've noticed. I then ask it for a detailed step by step realization (of the algorithm, or the paper/section/whatever), plus some context. Then I pass this as a prompt to a fresh new instance, and task it to implement in full based on the description (Gemini Deep Think was quite good with that).

Now I feel like 5.6 Sol Ultra is capable of doing roughly the same with its Agents, so it's getting easier in my experience. With the Codex, it can adjust or correct until the output is suitable.

I'm sure it depends on the field and the method.

Thanks a lot for sharing! I'll try the discussion to unpack context, that sounds interesting. I end up having such discussions in separate chats anyways to understand what's happening so it makes sense to do it upfront.

I have many problems dealing with statements that use Infinity, especially if I think about the math or physics implication of that :)

Infinity is a ridicilous statement. Even the work that wouldn't have been done before is now time away from work that needs to be done. At worst it's negative x.

Pretty sure this was one of those so-called “jokes” I have read about in a research paper once. American humor tends to rely on overstatement. This is contrast with British humor that more often builds on understatement.

It's a division by zero. We can change infinity to 'undefined'

Reply on news.ycombinator.com