[FRIAM] "how we turn thoughts into sentences"

[Steve Smith]

Clicking through the linked references:  The OpenAI "research" reads 
like a list of press releases promoting their agenda; Anthropic's list 
reads much more like SciAm or similar level of popular publication 
trying to actually communicate the issues:

    https://transformer-circuits.pub/2022/toy_model/index.html#motivation

My "dive" into this is still very shallow (maybe someone can 
de-metaphorize this for me?) but it aligns well with my own ad-hoc/naive 
growing apprehensions.   Lots here (for me) including what feels like a 
strong parallel (apt for metaphorical/analogical domain transfer?) with 
genotype/phenotype thinking.


On 7/17/2025 11:20 AM, Steve Smith wrote:
>
>     https://scitechdaily.com/researchers-decode-how-we-turn-thoughts-into-sentences/
>
> I'm hoping/expecting some folks here are as fascinated with these 
> things as I am?  LLM's, interperatability, natural vs are to me as 
> weather/vortices/entropy-intuition is to Nick?
>
> As someone who spends way too much time composing sentences (in 
> writing) through this impedence-mismatched interface (keyboard) I have 
> a strong (if misleading, or at least ideosyncratic) apprehension of 
> how I might form sentences from thoughts, and perhaps even 
> forward/back propogate possible expressions and structures *all the 
> way* to where I imagine my interlocutors (often all y'all here) 
> reading and responding internally (mentally) and online.    My 
> engagement with the LLMs in "casual conversation" includes a great 
> deal of this, albeit understanding that I'm talking to "a stochastic 
> parrot" or more aptly perhaps "making faces into a funhouse mirror" 
> (reminding me that I really want to compose a good-faith answer to 
> glen's very sincere and I think pivotal questions about metaphor).
>
> I haven't parsed the linked article deeply yet and have not sought out 
> the actual paper itself yet, but find the ideas presented very 
> provocative or at least evocative?  It triggers hopeful imaginings 
> about connections with the cortical column work of Hawkins/Numenta as 
> well as the never ending topics of FriAM: " Effing the inEffabl"e and 
> "Metaphors all the way Down?"
>
>  I don't expect this line of research to *answer* those questions, but 
> possibly shed some scattered light onto their periphery (oupsie, I 
> waxed up another metapho to shoot some curls)?   For example, might 
> the electrocorticography during ideation-to-speech transmogrification 
> show us how strongly metaphorical constructions differ from more 
> concise or formal analogical versions (if they are a spectrum) or how 
> attempts to "eff the ineffable" might yield widely branching (bushy) 
> explorations, ending in some kind of truncation by fatigue or 
> (de)saturation?
>
>     https://www.nature.com/articles/s44271-025-00270-1
>     <https://www.nature.com/articles/s44271-025-00270-1>
>
> And are attempts at Interpreting LLMs in some meaningful way colinear 
> or offer important parallax (to reference the 
> "steam-engine/thermodynamics" duality)?
>
> And me, here, with obviously "way too much time" on my hands and a 
> fascination with LLMs and an urgency to try to keep traction on the 
> increasing slope of "the singularity" and a mild facility with visual 
> analytics and *I* haven't even begun to keep up...     This list 
> (ironically) was formulated by GPT and I've not (and surely will not) 
> do much double-checking beyond (hopefully) diving deep(er) inoto the 
> work.  I was mildly surprised there were no 2025 references...   I'm 
> guessing the blogs are running commentary including current work.  
> I'll go click through as soon as I hit <send> here (imagine the 
> next-token prediction I am doing as I decide to try to stop typing and 
> hit <send>?)
>
>     *“A Survey of Explainability and Interpretability in Large
>     Language Models”* (ACM Computing Surveys, 2024)
>     Comprehensive classification of methods, with comparisons between
>     mechanistic and post‑hoc approaches.
>     Preprint link on arXiv: [arXiv:2310.01789]
>     <https://arxiv.org/abs/2310.01789>
>
>     *Anthropic’s Interpretability Research Pages* (2023–2024)
>     https://www.anthropic.com/research
>
>     *OpenAI’s Technical Blog: “Language Models and Interpretability”*
>     (2023)
>     Discussion of interpretability challenges, with examples from
>     GPT‑4-level models:
>     https://openai.com/research
>
>     *NeurIPS 2023 Workshop on XAI for Large Models*
>     Video talks & proceedings with up-to-date methods:
>     https://nips.cc/virtual/2023/workshop/66533
>
>
>
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