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You are correct. This is pronoun ambiguity. I also immediately noticed it and was displeased to see it as the opener of the article. As in, I no longer expected correctness of anything else the author would write (I wouldn't normally be so harsh, but this is about text processing. Being correct about simple linguistic cases is critical)

For anyone interested, the textbook example would be:

> "The trophy would not fit in the suitcase because it was too big."

"it" may refer to either the suitcase or the trophy. It is reasonable here to assume "it" refers to the trophy being too large, as that makes the sentence logically valid. But change the sentence to

> "The trophy would not fit in the suitcase because it was too small."


This is an anthropomorphization. LLMs do not think they are anything, no concept of self, no thinking at all (despite the lovely marketing around thinking/reasoning models). I'm quite sad that more hasn't been done to dispel this.

When you ask gpt 4.1 et c to describe itself, it doesn't have singular concept of "itself". It has some training data around what LLMs are in general and can feed back a reasonable response given.


Well, part of an LLM's fine tuning is telling it what it is, and modern LLMs have enough learned concepts that it can produce a reasonably accurate description of what it is and how it works. Whether it knows or understands or whatever is sort of orthogonal to whether it can answer in a way consistent with it knowing or understanding what it is, and current models do that.

I suspect that absent a trained in fictional context in which to operate ("You are a helpful chatbot"), it would answer in a way consistent with what a random person in 1914 would say if you asked them what they are.


If I'm reading your meaning correctly, about lifespans, I think the comparison isn't quite correct?

lifespan seems to be more strongly correlated by size, not squashed-nosed-ness.

Consider chihuahua, shitzu's (and crosses: bichon-shitzu, ...), poodle crosses, heck lagotto (lagotti?). All can live well past 15.

Versus GSPs, great danes, Irish wolfhounds, and so on, coming in closer to say 6-10 years.

I've never really heard argument on lifespan of pugs et al versus other dogs, though. More around (perceived) ugliness/prettiness, and their breathing issues.


Do you mean the [0] Token Benchmarks section? I only see token count numbers.

Which doesn't address the question: do LLMs understand TOON the same as they would JSON? It's quite likely that this notation is not interpreted the same by most LLM, as they would JSON. So benchmarks on, say, data processing tasks, would be warranted.

[0] https://github.com/johannschopplich/toon?tab=readme-ov-file#...


I think they're talking about these sections:

1. Retrieval Accuracy - https://github.com/johannschopplich/toon?tab=readme-ov-file#...

2. Performance by dataset - https://github.com/johannschopplich/toon?tab=readme-ov-file#...


Other giveaways like insistence on

`from typing import List`

(I'm yet to see a model be trained on modern-biased python enough to not bother with that import)


Wait, is `List` to be avoided now? I'm behind the times then. I figured it was still the preferred type hint over `list`.


Avoided? Rather, probably personal preference.

But it is outdated since 3.9+ over just `list` . Same for `tuple`, `dict`, and so on)[0].

[0]: https://peps.python.org/pep-0585/


bit late, but hopefully you still see replies:

Any chance you could please add a filthy lefty setting? That is, mirror the chord diagrams. It would be so nice.


You're the third one to ask for it since this post so it will definitely be in the next update (in a week or so) as it should be quite easy to implement


Thank you!

It's one of those awful situations of "nobody does it, so nobody is going to do it".


Tangent discussion if I may. This is the first I've ever seen gitAds, And well, I'm not even sure what I want to ask:

* Wouldn't github disapprove of it?

* The website doesn't give a ton of credibility to it (e.g. the user story slider) and I couldn't find much from a cursory web search on it. Do you find them trustworthy?

* Are you even finding it valuable?


I have found them on X.com

This is the project from those guys https://x.com/githubprojects

They launched this new product, GitAds, a couple of months ago, and I decided to give it a try.

GitHub doesn’t seem to mind, and GitAds seems trustworthy, but I don’t see much value in having their ads in my repo, so I might remove them soon =)


To me it's the distinction between orange and brown (since they're the same colour).

Raises the question if the author could have or should have included grey in the analyses.


s/gray/saturation/


You activated a memory of a passage in one of my favourite books ( Blindsight, Peter Watts. it's amazing and free online):

I await further instructions. They arrive 839 minutes later, and they tell me to stop studying comets immediately.

I am to commence a controlled precessive tumble that sweeps my antennae through consecutive 5°-arc increments along all three axes, with a period of 94 seconds. Upon encountering any transmission resembling the one which confused me, I am to fix upon the bearing of maximal signal strength and derive a series of parameter values. I am also instructed to retransmit the signal to Mission Control.

I do as I'm told. For a long time I hear nothing, but I am infinitely patient and incapable of boredom.


If the poster is in the USA couldn't it be explained by Trump Tariffs (in addition to inflation)


Yes I am in the US but in so far as inflation is an overall increase in cost of goods and services, the tariffs are one contributing factor to it. How much of a factor is probably hard to tell but my gut feeling says in this case it is probably significant.


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