I wonder to what extent this is the result of suboptimal RLHF versus the inherent intelligence of the model making its language more intricate and difficult for humans to easily parse? On the one hand, it's a common trope that highly educated people can talk in a way that's confusing and annoying to regular people who don't know all the jargon. But on the other hand, it's a mark of a skilled communicator to be able t…
Show HN: The load-bearing vocabulary of Claude
101–110 of 328 posts
Re: Show HN: The load-bearing vocabulary of Claude
#102The search on this website suggests it is indeed 3.6x more likely in the claude cluster
Re: Show HN: The load-bearing vocabulary of Claude
#103Author here! Grateful for the kind words, human communities like HN really hit differently when you spend the whole day chatting with sycophantic and bullshitting agents (including to make this page). I'm currently adding a search bar as well as increasing the data to 1000 PR per day. A nice thing that is not obvious on the main page is that the dataset and analysis are updated daily using Github Actions (at least wh…
Very cool! I'm trying to understand the graph, so the bottom-most section seems to be the cluster identifying Claude written PRs. What are the other 7, any reason there are 8 in total? I've been scraping instagram posts recently to identify AI misinformation accounts that all repost each other's carousels and get hundreds of thousands of likes in engagement. Thinking of ways to present it and your dashboard looks ver…
I did experiment and a stacked chart seemed the most clear, with the important cluster at the bottom.
Re: Show HN: The load-bearing vocabulary of Claude
#104Re: Show HN: The load-bearing vocabulary of Claude
#105Earlier quoted context omitted.
I don’t think they’re “talking down”. If anything - it’s way more difficult to distill something into a genuinely easy to digest format. I personally think that they aren’t immediately capable of this, and so we get word salad instead. Extra prompting required to strip extraneous prose out. Maybe I am dumb and it IS talking down to me, but there have been many occasions where I’m reading AI generated docs / plans and…
It doesn't seem like word salad as such. There's normally a coherent point expressed, it's just obscured by circuitous sentence structures, unusual word choices, "verbing weirding nouns", metaphors, etc. Could be a result of training that rewards novel/surprising language, but it also feels like it could be an artifact of models imperfectly compressing high-level multidimensional reasoning into language that's easy f…
Re: Show HN: The load-bearing vocabulary of Claude
#106Surprised I don’t see footgun. That’s as common as load bearing in my interactions.
Re: Show HN: The load-bearing vocabulary of Claude
#107A lot of these “Claudeisms” are simply jargon I’ve seen or heard firsthand myself while working at tech companies. I don’t think it’s limited to Claude either; I’ve seen Codex use load-bearing and many of these phrases as well. I think using agents is just like speedrunning the whole experience of working with technical coworkers. Whereas you might have had a few coworkers at your company who used some of these phras…
Re: Show HN: The load-bearing vocabulary of Claude
#108I wonder to what extent this is the result of suboptimal RLHF versus the inherent intelligence of the model making its language more intricate and difficult for humans to easily parse? On the one hand, it's a common trope that highly educated people can talk in a way that's confusing and annoying to regular people who don't know all the jargon. But on the other hand, it's a mark of a skilled communicator to be able t…
Re: Show HN: The load-bearing vocabulary of Claude
#109Re: Show HN: The load-bearing vocabulary of Claude
#110I love what I can build now, but I sure as hell don't love the headaches this trend has been giving me.
> So the full honest arc on the case we set out to fix: the expiry rules and day note tripled the loose version of the story, the relay fix carried the device’s own guardrail through the pipeline, the fair replay then revealed the last mechanism — ticket-anchoring — which none of the shipped layers reach. Remaining options, in order of my confidence: making the resolved-ticket summaries in the AI’s context carry their day so the expiry rules have something to bite on (small, mechanical, targeted at the observed anchor); and the plan-B second-model check, which structurally catches this class no matter how the model reasons. About $25 of headroom remains. Which way?
Yikes.
(The worst part is that I understand it)