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.

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Showing developments with attributable Research & technical analysis reactions.

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Building & implementation Research & technical analysis
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Multiple readings Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models Research & technical analysis · 3 attributable reactions
Showing signals surfaced by Kevin Patrick Murphy ×
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The developments commanding sustained expert attention

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

Established Models & releases Research 11d ago
⚡ 109 h early
model discovery agent Bayesian paper

Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models

3 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 2 attributable expert contributions · Sung Kim, Artificial Intelligence Papers
“Paper: arxiv.org/abs/2608.09696 Repo: github.com/murphyk/neur...” evidence ↗
3 experts 1 community 1 sources clustered
Kevin Patrick Murphy Sung Kim Artificial Intelligence Papers
How the network is reacting Experts are approaching this through 2 distinct lenses.
Multiple readings

Research & technical analysis

2 experts

Evidence, methods and technical implications.

“Paper: arxiv.org/abs/2608.09696 Repo: github.com/murphyk/neur...”

Building & implementation

1 expert

How teams are shipping and applying it.

“Some updates on my "Model Discovery Agent" paper. 1) Significant new version posted to https://t.co/CUfwMhQdpP; 2) video of a talk I gave at U Toronto posted to https://t.co/y2izltTO1o ; 3) I now have a cute picture of the (polyglot) MDA workflow :) https:/…”

Primary source arxiv.org ↗