#mechanisticinterpretability
Live, measured metrics for the hashtag #mechanisticinterpretability from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #mechanisticinterpretability
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mas.to (Mastodon public tags API) · fetched 2026-09-26 03:22 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mas.to (Mastodon public search API) · fetched 2026-09-26 03:22 UTCNo related tags with measured usage found for #mechanisticinterpretability.
Live pulse
measured · mas.to (Mastodon tag timeline) · fetched 2026-09-26 03:22 UTCEverything below is measured over the latest 16 public posts (spanning ~30397 hours).
Posting hours (UTC) — busiest: 07:00
Languages: English (11) · Russian (1)
Avg boosts / post: 0.7
Top of the latest posts
We can inspect an AI’s prompt, output and activity log. What we usually cannot see is how the model arrived at its decision. With companies including Google DeepMind and Goodfire working in this field, mechanistic interpretability is beginn
Morning, today we're looking at #MechanisticInterpretability , a subfield of AI Safety that attempts to understand the inner workings of artificial intelligence by analysing concrete structures, algorithms and circuits. Why do we even need
Calling LLMs stochastic parrots is... frankly wrong. It's true that pre-training LLMs is literally matching the empirical distribution of human text, so this would be the only place where "stochastic parrot" is a coherent description of the
#mechanisticinterpretability across platforms
every network with a public tag surfaceFollow #mechanisticinterpretability straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/mechanisticinterpretability