How much more common this term is here than in ordinary English. Higher values mean the topic is more characteristic of this corpus.
1.5x burst in 2025 Q1?
Peak quarter intensity across the topic's active span. Higher values mean attention was concentrated into a shorter stretch rather than spread evenly over time.
Related:?
Topics that appear in the same chunks as this one. Use this to find semantic neighbors, not ranking neighbors.
A short read on the topic's time range, peak episode, and strongest associations. Use it as the quick orientation before drilling into examples.
llms appears in 790 chunks across 131 episodes, from 2023-11-06 to 2026-08-03.
Its densest episode is Bits and Bobs 10/20/25 (2025-10-20), with 17 observations on this topic.
Semantically it travels with ChatGPT, Claude, and Google, while by chunk count it sits between Claude; its yearly rank moved from #2 in 2023 to #1 in 2026.
Over time
?
Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Range2023-11-06 to 2026-08-03Mean6.0 per episodePeak17 on 2025-10-20
Observations
?
The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
Showing 790 observations sorted from latest to earliest.
LLMs are an "impossibly precocious ninth grader who never gets bored and has read 1000x more books than you ever will".
A lot of the party tricks LLMs can...
...e to directly experience the relevant situation yourself: a massive constraint.
LLMs are unlike humans in that their knowhow can be transferred to other models more directly (or in some cases just directly replicated).
This means that...
...it free reign, you can know (mostly, most of the time) how it will operate.
But LLMs are squishy. They are more impressionistic. They lose the plot, especially the longer it's gone since the last checkpoint with whatever entity is gui...
... that have a structured formal language will have interesting applications with LLMs.
Writing code (or any formally structured document, e.g a Domain Specific Language) has two things that must be true:
syntactic correctness (is this ...
I've found that I use LLMs for certain curiosity-style questions I wouldn't have even bothered searching for in the past.
Search relies on the SEO swarm of content farms to hav...
...ew reflections from a conversation I had with my friend Dimitri last week about LLMs.
There are two distinct uses for LLMs that pull in very different directions:
convergent mode ("spackle for toil")
divergent mode ("a muse that super...
...some scenario planning last week with various folks on the long-range impact of LLMs on humanity.
LLMs are a discussion partner who is well-read, eager to please, a bit naive, and never, ever gets bored.
A meta thing was how useful us...
Last week I talked about LLMs as "spackle for toil".
The original software-based spackle for toil is spreadsheets.
Spreadsheets are absurdly, generically useful, in just about eve...