LLMs are now good enough to be better than all but the experts in any given domain.
LLMs are now good enough to be better than all but the experts in any given domain. Which produces a problem: how can you judge if its answer is good in a...
Topic: llms
1,749 mentions · 790 chunks · 131 episodes
184.9× distinctiveness vs baseline
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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
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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.
Topic summary
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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
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Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Observations
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The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
LLMs should be good at generating possible multi-disciplinary insights.
LLMs should be good at generating possible multi-disciplinary insights. LLMs are worse than domain experts, but better than most everyone else nowadays. B...
LLMs are a good dowsing rod: is your hunch good enough to be worth digging deeper on?
LLMs are a good dowsing rod: is your hunch good enough to be worth digging deeper on? There are lots of questions where even an approximate answer says "y...
An idea for a science fiction story: humanity has had a cataclysmic event that destroyed nearly all society.
...running an LLM. The ruined society doesn't (yet) know how to build a way to run LLMs themselves. That would require millions of specialists with knowhow to produce all the inputs necessary to build chips and servers and program them, ...
An agent is a bit of software that is animated by LLMs.
An agent is a bit of software that is animated by LLMs. Not normal software that does precisely what it was programmed to do, agentic software that has some squishiness. Expensive, dangerous, intrinsicall...
The most important characteristic of LLMs is their patience.
The most important characteristic of LLMs is their patience[apc]. They can do tasks that real humans would get distracted or bored by. For example, carefully reading many pages of material to...
Don't use an LLM to write for you, use it as a thinking partner.
Don't use an LLM to write for you, use it as a thinking partner. LLMs' ideas are never good. They're always mush, just frog DNA. I was chatting with an author who told me he refuses to use an LLM. He told me you "write ...
LLMs are never blunt.
LLMs are never blunt.[ape][apf] When someone is blunt they're definitely a human. You might love or hate their taste but they're definitely human.
LLMs are great at giving you the superficial vibe of quality.
LLMs are great at giving you the superficial vibe of quality. But the closer you look, the more you realize it's fundamentally hollow. A gilded turd. "Wow...
LLMs compress nearly all of humanity's background context into a teensy weeny little hyperobject package.
LLMs compress nearly all of humanity's background context into a teensy weeny little hyperobject package. They have effectively infinite background contex...
Last week I observed that the spec seems more important than the code in the world of LLMs.
...eek I observed that the spec seems more important than the code in the world of LLMs. Which layer is the most important? The layer where you spend most of your time iterating. This is especially true if there is a robust, automatic tr...
How many thousands of papers in the 70's, 80's, 90's, and 2000's had great ideas that were just ahead of their time?
...object with near infinite background context? If you sprinkle the pixie dust of LLMs on those old ideas, how many could spring to life?
Applications don't pop into existence, fully formed.
...opelling them through the problem. This same ability is important in a world of LLMs too, where the hard part now is to sequence the incremental extensions of work in the same way a human programmer would, but have an LLM turn the exe...
One of LLMs' primary superpowers: they have human-level ability, but they never get bored.
One of LLMs' primary superpowers: they have human-level ability, but they never get bored. For example, human engineers get bored very quickly writing tests for ...
Frog DNA is average, mush, generic.
Frog DNA is average, mush, generic. That's one of the reasons LLMs pull everything to the bland centroid; they fill any ambiguities with mush. What if you could make it so instead of using frog DNA, it used shark DNA...
English specs can now be "compiled" to runnable code by LLMs.
English specs can now be "compiled" to runnable code by LLMs. When we make programs, we compile the source code down to an executable binary. But then we make sure to keep the source code, so when we tweak it i...
Having a background in things like sociology gives a leg up for understanding LLMs.
Having a background in things like sociology gives a leg up for understanding LLMs. Most tech is understood best with a straightforward math/computer science frame. But LLMs are a cultural technology. They are best understood throug...
LLMs didn't train on images, but pictures.
LLMs didn't train on images, but pictures. An image could be any random bit of noise expressed as a 2D array of pixels. A picture, in contrast, was a thin...
Imitation and innovation are both important.
...stem pulls to an extreme, rigid, brittle, centroid. A heat death of the system. LLMs just imitate, following the innovation that humans that came before have done. In a world where we use LLMs for more things, how can we make sure tha...
Everyone is so focused on AGI that they're ignoring applications of cheaper, lower end AI.
...he top models. We can now take an IQ of 90 for granted with cheap off the shelf LLMs… and it will only get cheaper. What happens when you take IQ-90 LLMs for granted, and assume it's too cheap to meter?