Maybe they studied the same subject but at a different school, or maybe they specialize in something else entirely.

Maybe their first language is different from yours, since language idioms can affect the way we frame problems.

Maybe they want to get into the field you're working on, and your thinking can also be teaching.

For me, this is a big part of the value of a hackerspace/makerspace. The tools are nice, but the intellectual environment is amazing.

>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.

Trying to train an LLM on two 1080ti's on the StackOverflow corpus in my living room was a vibe though. Good times.

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.

Thinking silently fits Asian Americans better than Euro Americans*.

https://www.psychologytoday.com/us/blog/sex-murder-and-the-m...

Yes! I love that someone wrote this down!

This seems so obvious to me now. I often ask LLMs to cite their sources (they do hallucinate from time to time), and they often give me sources that don't say what is claimed. "How would the LLM know not to give this to me?" I wonder. They're trained to explain but not to convince, so they don't know what's convincing, and they should.

I think humans hallucinate at least as much as LLMs—arguments of any complexity are impossible to formulate without leaping at least a bit—but other humans ground us. That's why when people become socially isolated, they join cults or adopt conspiracy theories or the like.

Conversely, "this is convincing to an expert" converges on “this is true" as our collective expertise grows over time. This is the foundation of the scientific method, of progress in all engineering disciplines, etc.

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.