Topic: intuition

112 mentions · 20 chunks · 19 episodes

21.2× 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.
2.8x burst in 2025 Q3
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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.
  • intuition appears in 20 chunks across 19 episodes, from 2023-11-06 to 2026-04-13.
  • Its densest episode is Bits and Bobs 7/7/25 (2025-07-07), with 2 observations on this topic.
  • Semantically it travels with Wikipedia, opportunity cost, and Anthropic, while by chunk count it sits between writing code and google search; its yearly rank moved from #64 in 2023 to #93 in 2026.

Over time

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Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Mean 1.1 mentions per episode across the full range2023-11-06: 1 mention2024-01-29: 1 mention2024-02-05: 1 mention2024-03-25: 1 mention2024-04-01: 1 mention2024-04-15: 1 mention2024-06-17: 1 mention2024-08-12: 1 mention2024-09-09: 1 mention2025-02-18: 1 mention2025-07-07: 2 mentions2025-08-04: 1 mention2025-08-25: 1 mention2025-09-02: 1 mention2025-10-20: 1 mention2025-12-15: 1 mention2026-03-09: 1 mention2026-03-17: 1 mention2026-04-13: 1 mention2023-11-06: 12024-01-29: 12024-02-05: 12024-03-25: 12024-04-01: 12024-04-15: 12024-06-17: 12024-08-12: 12024-09-09: 12025-02-18: 12025-07-07: 22025-08-04: 12025-08-25: 12025-09-02: 12025-10-20: 12025-12-15: 12026-03-09: 12026-03-17: 12026-04-13: 12023-11-062026-04-13

Observations

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The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.

Why is LLM training convergent?

from Bits and Bobs 8/25/25 ·

...ergent; diffusing through an unfathomably vast hyper-dimensional space. But our intuitions for hyper-dimensional spaces are often wrong. Hyperdimensional spaces are interconnected in surprising and weird ways. Wormholes that teleport from ...

Using LLMs properly requires LLM-fu.

from Bits and Bobs 3/25/24 ·

.... Just like Google-fu back in the day. The kinds of people who had developed an intuition on how to formulate their query (sometimes in non-obvious ways!) to get great results. In the early days of Google, some people literally got paid fo...

A few riffs on LLMs.

from Bits and Bobs 2/5/24 ·

A few riffs on LLMs. An intuition for things that LLMs will get right: if Wikipedia has explained the concepts well. Those facts are likely to also ripple out and inform lots of other...