I like this. I thought to iterate on it a bit, for the folk who respond better to higher-tact phrasing:
"Thanks. I have access to ChatGPT as well. But I ask people for help when it fails. Your thoughts are smarter than GPT's, please provide those, next time."
Yes, if OP did a full vocabulary comparison and took just those sub-threshold, it would be hacking. I'm not sure that's the case here, though? Given that (the post) OP started with em-dash, and probably didn't do repeated sampling, then it should be a pretty fair hypothesis that em-dash usage is a marker.
Your comment about p<0.05, feels out of place to me. The p-values here are << 0.05. Like waaaaay lower.
Perhaps Fisher's exact is more appropriate, on the per-word basis?
Like OP, I've been similarly struggling to get as much value from CC (grok et c) as "everyone" else seems to be.
I'm quite curious about the workflow around the spec you link. To me, it looks like quite an extensive amount of work/writing. Comparable or greater than the coding work, by amount, even. Basically trading writing code files for writing .md files. 150 chat sessions is also nothing to sneeze at.
Would you say that the spec work was significantly faster (pure time) than coding up the project would have been? Or perhaps a less taxing cognitive input?
Thanks for putting this together!
Couple QoL features I'd love to see:
1. filter slider, decreasing on price, to see places closest to me disappearing
2. on the left panel, when I click on a low priced area, it should highlight it on the map, so I know where it is. The 'go to pump' button, I guess is good. but I'd only want to commit to gmaps if I already know that it's a reasonable place for me to. be going.
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.
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.
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?
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.
I'm in the same boat and feel like this is the only logical approach. Such a potential timesink for such low odds. I think the effort should be somewhat symmetric: spend as much time as YC will in reviewing.
Especially without feed back signal, you'll never get to improve your application/odds. Dang says above that feedback won't happen because it doesn't scale -- not everything has to scale, Dang.
Christ in pijamas. TLAs should be a capitol offence. Even worse so, somehow, when undefined.