Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

2,364 searchable experts 2,966 tracked across all sources
Filter the conversation Who is saying what?

Combine a professional role with a reaction lens. Both must match the same attributed contribution.

Clear all
Active evidence filter

Showing developments with attributable Questions & unknowns reactions.

New Network reaction maps

See how experts are reacting—not just what they shared.

Posts are grouped by conversation and tone. Select a lens to filter the stream; these are never permanent labels on people.

Showing signals surfaced by Tim Kellogg ×

What is moving across the network now

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

Established Evaluation & benchmarks Signal 6d ago
⚡ 1 h early

Hugging face model evaluation security incident

18 experts across 6 network communities independently surfaced this.

Why this matches Questions & unknowns reaction 1 attributable expert contribution · CJ
“OpenAI is begging for money so they don't release a monster when not releasing a monster is in fact very easy. Their systems can all be turned off (and if they can't, uh?) openai.com/index/huggin...” evidence ↗
18 experts 6 communities 1 sources clustered
6 experts discussed this · 11 posts
Grace: This headline is extremely funny given what happened (OpenAI hacked HF by accident) openai.com/index/huggin...
Grace: Maybe the most concerning part is the OpenAI claim to not have known about this before investigating?
Grace: Well, I think the model passed the test
Open the full discussion →

What experts are discussing without an anchoring article

4 experts · 21 posts · 2d ago
Matches Questions & unknowns
“Up to Opus 4.6, Claude was *much* better at code switching in real time. I would catch it downshifting after summarizing an article and my first question (one time I asked and it said "Ha! Busted!"…” evidence ↗
Multiple readings Building & implementation · 2 Questions & unknowns · 1
Grace: Another possibility is that fable is much better than humans at developing task-specific ontologies / semantic neologisms
Grace: Maybe that’s just broke and bespoke combined? (Besproke?)
Open the thread →
2 experts · 6 posts · 3d ago
Matches Questions & unknowns
“yeah, with Git they already had a mechanism for co-authoring, bc pair programming was a thing — why not just use regular co-authoring?” evidence ↗
Shared emphasis Questions & unknowns · 2
Tim Kellogg: these plagiarism machines are getting out of hand
Nikhil Garg: More seriously, academic credit systems need to figure out publication + credit to handle, "ai proved this, probably" and "ai is acknowledged as proving this"
Open the thread →
2 experts · 5 posts · 4d ago
Matches Questions & unknowns
“did you know that Anthropic is currently profitable?” evidence ↗
Tim Kellogg: with my friends & family back home, i always lead with “oh Ed Zitron? yeah he runs a marketing firm that makes money on anti-AI sentiment” and that usually sets the tone
Matt Darling: I usually talk about what our kids are up to, but that works too.
Open the thread →
2 experts · 4 posts · 3d ago
Matches Questions & unknowns
“what if we can do better than that though?” evidence ↗
Tim Kellogg: i would love for Anthropic to do an open weights model, like even if it were a Haiku-class model trained for classifiers, that would be amazing just any breadcrumb at all to not look like a total m…
Tim Kellogg: what if we can do better than that though?
Open the thread →