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- Hacker News
- Heinrich von Kleist – On the gradual production of thoughts during speech
is a classic german text from 1805 on this subject that I have always valued deeply
https://franxfiction.com/on-the-gradual-fabrication-of-thoug...
by baumgarn - Really interesting someone brings this up here. It's kind of an obscure little piece of text. But I always thought, yeah, this is more or less how we produce thought, and how LLMs operate, too.by nakedneuron
- A collection of thoughts on this.
Pierces Firstness is exactly what drives this.
The move from thinking to semantic conversion is important for investigation/introspection.
Arguing with yourself also seems to engage your brains "theory of mind" centers, so different pathways get activated to examine the problem space.
The problem with Ai is the fact that it hallucinates and if you're doing anything truly novel in an integration or framing sense it bottoms out very quickly and can't engage. A human operator can decompose the problem and get accuracy checks for known areas in the training data of course.
Now to be I'm not saying Ai can't produce novel work on the edge but in my experience it is antagonistic towards those goals.
Case in point, CRDTs, many don't use tombstones but they are the minority, and if you try iterate a new CRDT off of one that doesn't use tombstones, let's say diamond-types, it will keep pulling you back to tombstones.
The problem is that the number of humans who understand dynamic investigation and the push pull of exploring an idea you don't hold with someone has always been very small, and now with reflexive internet argument culture driving how we view "debate" and "discussion".
I don't know if we've reduced the leisure to think or what but things are not great for finding speculative thinking partners.
- Communicating ideas helps, but thinking out loud may not work better to some people.
Thinking silently fits Asian Americans better than Euro Americans*.
https://www.psychologytoday.com/us/blog/sex-murder-and-the-m...
by Congeec - Thank you for sharing this. Growing up Asian American many teachers disciplined me and made assumptions about my intelligence for not being as vocal as the other kids. Culture shapes cognition and vice versa.by wrathofquan
- I started my web dev career in 1999 so my main code references were a combination of O’reilly and “for dummies” books. As a wet behind the ears engineer I’d find myself regularly walking over to my more senior friend Dan’s cubicle for help.
Half the time on the walk over, trying to frame the question in my mind I’d figure out the answer or at least next step. It got to the point where Dan would see me heading towards him and suddenly turn around and he’d as “Figure it out?” And I’d throw him a thumbs up on the way back to my desk.
by mikeryan - In the nineties I was a junior copywriter at BMP DDB in London. The creative department was made up of loads of small offices, each with a two-person creative team working out loud all day. The best ideas rarely came from one person thinking alone. Someone would say something half-formed about a brief and their partner would catch it, often bouncing ideas back and forth. Reckon the whole building ran on that. Well, apart from the late and brilliant John Webster, who had his own office at the top of the corridor. We were lucky enough to have ours opposite his.by Etymon
- btw Pangram says 100% of the original article was written by AIby 383toast
- This proves nothing but, in my earlier days, I'd come home with something on my mind from work and tell my wife about how I couldn't get something to work the way I wanted. She had no clue what I was talking about but she'd offer up clues and suggestions to which I would try to explain to her how things actually worked.
Somewhere in that process it would lead to a solution that I would bring to work the next day!
- Why are you making your wife work for free :(by LtWorf
- It's simpler than this. Explaining a question/issue to someone involves going back to basics and covering all the foundational info that a third party would not have. When thinking alone, you gloss over this, and may not realize that a foundational assumption is incorrect. When you are forced to explain every step explicitly, these errors or gaps can become apparent without any intervention by the listener.
I have my younger kid explain each math problem to me before she submits it on Khan Academy. My older kid thinks in her head how she would explain a problem before turning in a test. It's a good habit to form.
by apparent - As much as people make fun of "new math", it is really neat to see my 3rd grader working through a math problem step by step in a way that makes sense to them instead of the rote memorization I had to do as a kid. While they don't like showing their work, it helps them to work through each step to make sure their assumptions are correct, like you said.by THansenite
- Tangentially, Regarding pair programming (as a special case of thinking together):
Programming is serializing ideas into the computer language. Communicating them with someone else first serializes them into human language, which is already much less abstract compared to the thought cloud in your head.
In the case of an effective pair programming collaboration, you also get to debate approaches, discuss details, alternate between coding and watching.
It also helps that the presence of someone else helps avoid many common distractions. Reading non-urgent private messages and checking out HN (I'm no longer so addicted to any other platform to check it out at work).
by aljgz - Yes, and, this is how experts should be using e.g. Claude Code.by Terretta
- OMG - strong vibes to Einstein crediting Michele Besso, his colleague at the Swiss Patent Office, with helping him discussing some concepts in the special relativity paper: see at the end of the paper https://www.fourmilab.ch/etexts/einstein/specrel/specrel.pdfby dh2022
- fwiw Pangram says 100% of the original article was written by AIby 383toast
- Interesting.
I saw a Facebook copypasta piece that claimed that Einstein's first wife came up with many or most of his ideas, and never got credit because of sexism. No proof whatsoever, other than she was a mathematician and physicist.
But "it could have happened!" is more important than even a microshred of evidence for highly emotional, online topics.
This anecdote nicely pokes a hole in that conspiracy theory: he was thoughtful enough to share credit with a layman work associate, but (supposedly) not the most important woman in his life - that seems even less likely.
by IAmBroom - Thanks,
I was wondering about the question of whether people who made very deep discoveries (Einstein and Godel come to mind) had others to talk things through with beforehand.
I know Andrew Wiles kept all of his work on Fermat's Last Theorem secret and by that I assume he never talked it through with anyone.
by joe_the_user - In 2017 LLMs weren't powerful enough to generate working code on their own, but my goal was to at least create a chatbot that could help you rubber-duck-debug your way to a solution. Unfortunately the tech wasn't quite strong enough for that, and not enough engineers even knew what rubber-duck-debugging was. RIP Duckly.
Trying to train an LLM on two 1080ti's on the StackOverflow corpus in my living room was a vibe though. Good times.
by jboggan - fwiw Pangram says 100% of the original article was written by AIby 383toast
- perhaps it is time to resurrect Duckly queue Frankenstein music and thunder in backgroundby baddash
- 2017 is a bit early to refer to them as LLMs. I'm not sure when exactly we started to refer to LMs as 'large', but I don't think it was before GPT2 (2019). That said, from the NLP work I've done, it was much more interesting working on small specialized models.by xpct
- I wonder how much is actually needed to create an automated rubber duck. How well would ELIZA work? (https://en.wikipedia.org/wiki/ELIZA) (might need some adjustment to not talk like a therapist, but you get the idea)by voidUpdate
- Duckly deserved to actually work. There’s a small irony here: the closest study I found to this, robots specifically built to simulate attentive listening, found they performed no better than an actual inanimate rubber duck for adult engineers. The mechanical signal of listening doesn’t seem to be the active ingredient. Makes me wonder if Duckly would have needed real disagreement to close a gap a duck can’t, not just better natural language.by kodesko
- It started out as an interesting read, until I got to this paragraph:
> The value didn't come from what was said at that moment. It came from what had been built across many such moments: a pattern of mutual recognition, a shared context, a baseline of trust that made the later exchange possible. The relationship was the infrastructure. The conversation was where it had been built, one cup of coffee at a time.
And that made me immediately question the worth of the entire piece. I get it, LLMS can rewrite an entire blog post in a minute, which can be quite tempting for people that don't enjoy writing itself, but it just takes so much variety away. I think people should stick to grammatical corrections only, and not rephrase entire paragraphs (never mind letting an LLM write everything in the first place).
by lowdude - lol Pangram says 100% of this was written by AIby 383toast
- This shit gets me irrationally mad. Well, the existence of such content doesn't, but the fact that other people aren't disdained by it (this dogshit has almost 300 upvotes on _HN_ right now) is what gets me.
- how can you tell it's llm that wrote this paragraphby brian138205
- Similar: as soon as I see that LLM style I bail out, you can't trust the content.
If they can't be arsed to write it, why TF should I be arsed to read it.
by stuaxo - I don't think the out loud or someone listening / reacting matters at all here. Suspect it's entirely this:
>The thought that was comfortable as a vague impression has to become a sentence, and sentences have structure.
It's not unlike what people like PG say about writing improving thinking...it's the being forced to go from fuzzy directional notions to something you can put on paper in that will stand up to critique.
Same with rubber duck debugging. The verbal part means you need to articulate it clearly but it's not the speaking that helps. Same with writing a detailed spec/prompt for an LLM - I know if its too fuzzy ("set an appropriate timeout") the LLM will spin it's wheels so it forces clarity.
Also suspect that a big part of who we consider intelligent is linked to this. Maybe their internal monologue is just more crisp - closer to what they'd tell a rubber duck.
by Havoc