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.

2,397 searchable experts 4,280 tracked across all sources
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Showing signals surfaced by David Smith ×
Most important

The developments commanding sustained expert attention

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

Established AI research Research 20d ago
medieval manuscript normalization paper

Pre-Editorial Normalization for Automatically Transcribed Medieval Manuscripts in Old French and Latin

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered
David Smith

“At a lower level, it can also be helpful to disentangle different stages in the noisy channel from material evidence to seemingly-clean reading in an edition. arxiv.org/abs/2602.13905”

Primary source arxiv.org ↗
Established Models & releases Research 20d ago
Apollo Restore ancient Greek LLM paper

Apollo Restore: A Foundation LLM for Historical Greek Optimized for Fill-in-the-Middle Restoration of Ancient Greek Texts

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered
David Smith

“To take a simple example, Doric forms of Greek are rarer than Attic ones in our sources, but if you have enough context in an inscription, models can infer that they need to use Doric forms. arxiv.org/abs/2609.22455”

Primary source arxiv.org ↗
Debates gaining attention

What experts are discussing without an anchoring article

4 experts · 8 posts · 14d ago
Maria Antoniak David Smith Henry Farrell Hoyt Long
Maria Antoniak: This talk by @himself.bsky.social was wonderful. Models mechanize, map, + remix the "house of intellect", connecting together previously disconnected hallways of knowledge. LLMs are not stochastic …
David Smith: This talk by @himself.bsky.social was wonderful. Models mechanize, map, + remix the "house of intellect", connecting together previously disconnected hallways of knowledge. LLMs are not stochastic …
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