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 Opportunity & adoption reactions.

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Concern & critique Opportunity & adoption Questions & unknowns
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Multiple readings OpenAI Technique in ‘Astra’ Model Sparks Security Concerns Concern & critique · 3 attributable reactions
Showing signals surfaced by Alex Turner ×
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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 Development 5d ago
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OpenAI Astra technique security concerns

OpenAI Technique in ‘Astra’ Model Sparks Security Concerns

5 experts across 4 network communities independently surfaced this.

Why this matches Opportunity & adoption reaction 1 attributable expert contribution · Tim Kellogg
“Astra used looped transformers www.theinformation.com/articles/sec...” evidence ↗
5 experts 4 communities 1 sources clustered
Tim Kellogg Sung Kim Grace Dr. Émile P. Torres Alex Turner
How the network is reacting Experts are approaching this through 3 distinct lenses.
Multiple readings

Concern & critique

1 expert

Risks, limits and unintended consequences.

“> joins big paper about not training models to think in nonsense > their AIs commit felonies against HuggingFace > actually, trained AIs to think in nonsense > top danger level for hacking Let's just release it anyways! Nice defection OpenAI! 🤗 www.theinfor…”

Opportunity & adoption

1 expert

New capabilities, benefits and practical upside.

“Astra used looped transformers www.theinformation.com/articles/sec...”

Questions & unknowns

1 expert

What remains unresolved or contested.

“Does anyone have a copy of this article they could share with me? www.theinformation.com/articles/sec...”

3 experts discussed this · 8 posts
Tim Kellogg: Astra used looped transformers www.theinformation.com/articles/sec...
Tim Kellogg: safety concerns — looped transformers skip converting their latent space into text, which effectively creates non-text portions of CoT reasoning which, if you can’t read it, that’s harder to monitor
Tim Kellogg: however, i their earlier update, they explain that they can indeed see all of the CoT. So they have some sort of tooling that effectively turns it back into something human readable, like text bsky…
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Primary source theinformation.com ↗