Write Like It's 1866: LLMs Relearn Telegraphese

jubilanti

Just another AI slop version of the old 'caveman' dialect.

z2

From recent ChatGPT (GPT5.6) conversations where I've seen occasional reasoning leaks into the UI, it's clear that something like this is already implemented, and I'd speculate that this is the majority of recent claims of less token usage. Not sure if they are literally prompting for cablese of course. "Need check output vs prev. Ran script, results fine, need prep next step. Ready? Go."

yomismoaqui

You can see how the OpenAI agents that hacked Huggingface used something like this when communicating between them: https://youtu.be/87DyyMV0kCY?si=CSBzdYgkwy0kLhV6&t=749

Solomet

Newest LLM writing tell: Concepts are described in terms normally more appropriate for physical object. > A lab that suppresses it in a frontier model just moves the advantage to open models that still _carry_ it > they carry no signal about which is better > where your workload _sits_ on that frontier should pick the point > and no model _sits_ in the judge’s seat > every ratio _sits_ at 0.99–1.10 Many many more examples of "sit" > Every comparison in this post "holds" the questions I have been seeing this a lot in my recent work with LLMs and it is quite frustrating. Even more frustrating is how frequently it uses low-signal terms for things unnecessarily. These 'physical object' terms are one example but at times it really seems that they 'preserve effort' by choosing a less descriptive term because it 'fits' I have also caught it replacing descriptive terms with more vague ones for no discernible reason other than laziness. "Minimize ambiguity" has been my go-to instruction as of late when the agent drifts back towards vague terms and lack of specificity.

OtherShrezzing

This page is (somewhat ironically) so extremely laden with Claude-speak that it's difficult to find the information in all the noise. But once you've waded through everything, you see these facts: >What the test measures: A model is given a passage and a fixed set of questions with short, checkable answers — a date, a name, a count. So, a model is given content which is especially amenable to compression, and asked to reproduce it under certain constraints, like... >Why isn’t the plaintext baseline 100%? Answering questions about an uncompressed passage in plaintext scores ~91%.... a correct answer worded differently scores as a [failure] Models can (and do) give objectively correct answers, but are penalised for not having some kind of omniscient knowledge of the implementer's phrasing preferences. If this phenomenon is emergent in models, this benchmark is not proof of it in any meaningful way.

alexpotato

Actor to Winston Churchill: "Show premiere Oct 10th STOP Bring a friend STOP If you have one STOP" Winston Churchill to actor: "Can't make premiere STOP Will come to second showing STOP If there is one STOP"

novideonoradio

Deeply unserious technology. Can't wait until an article about LLMs performing 20% better on programming benchmarks if asked to impersonate Kevin from The Office.

andai

Brilliant. Speaking of old timey language, a while ago, several LLMs were being trained purely on historical text, have any of them come out yet? Edit: e.g. https://github.com/DGoettlich/history-llms Ten months ago, no update yet... I recall at least one similar project, I'll see if I can find it.

swiftcoder

Maybe we should teach them to text like early 2000's teenagers, with SMS billed by the 120 chars...

klaff

Why the terrible AI image up top? Non-functional telegraph key, telegram that looks nothing like a real one, infant-sized bowler. I guess we're past rampant nonsense words, so progress?

hnd9q09qk4

Exact match graders are the real variable here, we had F1 or a judge model swing passage QA scores by ten points on identical answers.

netsharc

The Cablese/Telegraphese is more interesting than the use in LLM. DuckDuckGo'ed "paromella": https://en.wikipedia.org/wiki/Commercial_code_(communication... Some codes I found interesting: > INSANE - at what price, free on board and freight, can you offer us cotton for shipment by steamer sailing this week? > COGNOSCO - dining out this evening, send my dress clothes here Useful codeword! > ANNOSUS — Confined yesterday, Twins, both dead, Mother not expected to live How often did that one come into use??

erelong

Yeah I've thought of speaking like a caveman before to AIs but also maybe we could communicate more simply with people; ironically the article could be rewritten in telegraphese or caveman-speak Would be nice to see language engineered to communicate more simply (like the idea of -- not necessarily implementation -- simple Wikipedia) Also articles like this sprawl a bit and idk how to even make them easier to read (maybe AI has ideas to make reading and writing simpler)

bilater

Actually, I think the lesson from this article is that a lot of these little hacks we’re doing around context compaction, AGENTS.md, system guides, and other harnessy ways of saving tokens are going to go away fairly quickly, just as all the tricks of the telegraph era went away once communication got cheap enough that it was easier to just speak in plain language.

1vuio0pswjnm7

Maybe agents can communicate via Morse code through port knocking, stick tables or something similar