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
Build my stream Create my edition
Filter the conversation Who is saying what?

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

Clear all
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.

Building & implementation Opportunity & adoption Research & technical analysis
2 live reaction maps in this view Jump to the evidence ↓
Reaction converging Kimi K3.1 Pro Tech Blog: Advancing Open Intelligence Research & technical analysis · 3 attributable reactions Reaction converging Verbalizable Representations Form a Global Workspace in Language Models Opportunity & adoption · 5 attributable reactions
Showing signals surfaced by Nafnlaus 🇮🇸 🇺🇦 ×
New & accelerating

What is moving across the network now

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

Accelerating AI field signal Signal 3h ago

Kimi K3.1 Pro Tech Blog: Advancing Open Intelligence

6 experts across 4 network communities independently surfaced this.

6 experts 4 communities 1 sources clustered
Nathan Lambert Ted Underwood Tim Kellogg Max Woolf Nafnlaus 🇮🇸 🇺🇦 jeremymorrell.dev
Primary source kimi.ai ↗
Developing Models & releases Research 2d ago
⚡ 3 h early
global workspace theory language models paper

Verbalizable Representations Form a Global Workspace in Language Models

6 experts across 4 network communities independently surfaced this.

6 experts 4 communities 1 sources clustered
Mark Riedl Tim Kellogg Matthew Kirschenbaum Edouard Machery Nafnlaus 🇮🇸 🇺🇦 david-p-reichert.bsky.social
How the network is reacting 4 experts are independently emphasizing opportunity & adoption.
Reaction converging

Opportunity & adoption

4 experts

New capabilities, benefits and practical upside.

“here is the Anthropic blog: transformer-circuits.pub/2026/workspa... I don't really like the framing of whether LLMs are conscious or not. It's completely unnecessary. As is the hand-waiving about whether LLMs have something equivalent to the (functional) g…”

Building & implementation

1 expert

How teams are shipping and applying it.

“Anthropic uses the word “conscious” 206 times in their latest research Specifically, they’re showing that LLMs implement one of the leading explanations of consciousness in humans (see pic) transformer-circuits.pub/2026/workspa...”

7 experts discussed this · 203 posts
Anil Dash: this is not an accurate description of what's happening. not least because I can write code and get them to output something different there. I can understand why it *seems* that way, but this is j…
Anil Dash: Who are you explaining this to?
Anil Dash: Do you see why explaining "All output from AI has to be validated" in a reply to me here is... not a useful contribution?
Open the full discussion →
Primary source transformer-circuits.pub ↗
Debates gaining attention

What experts are discussing without an anchoring article

4 experts · 21 posts · 1d ago
Eugene Vinitsky Adam Wiemerslage Sam Barrett, PhD Nafnlaus 🇮🇸 🇺🇦
Multiple readings Concern & critique · 1 Research & technical analysis · 1 Opportunity & adoption · 1
Eugene Vinitsky: It takes so long to write a paper because we are crazy about not making mistakes and checking as many edge cases as we can. This stressful responsibility is, I suppose, not obvious. so, if you’re n…
Eugene Vinitsky: Lots of new folks trying to write papers so it’s important to know: if there’s a mistake in the paper, the responsibility falls on you. You cannot offload it to the AI assistant.
Open the thread →
3 experts · 10 posts · 4d ago
Gus austin Nafnlaus 🇮🇸 🇺🇦
Gus: I replied to a Gemma user asking what they would like to see in future Gemma models, and somehow this became my most popular post ever! With great insights and requests. Thanks everyone! 🤩🙏🏼 I trie…
Nafnlaus 🇮🇸 🇺🇦: Something dense in the ~8-9B range would be great. The best thing out there right now is Qwen 3.5 9B, which is several generations old. Builtin speculative decoding would be great :)
Open the thread →