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 developments with attributable Concern & critique reactions.

New Network reaction maps

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

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Concern & critique
1 live reaction map in this view Jump to the evidence ↓
Reaction converging AI Is Changing Everything About Hacking. No One Knows What Happens Next Concern & critique · 3 attributable reactions
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.

New Safety & security Development 15h ago
⚡ 5 h early
AI transforming hacking cybersecurity report

AI Is Changing Everything About Hacking. No One Knows What Happens Next

3 directory members surfaced this signal.

Why this matches Concern & critique reaction 3 attributable expert contributions · 404 Media, Joseph Cox, Jason Koebler
“'Black October:' The PHP vulnerabilities and a series of other hacks and bugs have cybersecurity experts freaking out and unsure what happens next. www.404media.co/php2shell-bl...” evidence ↗
3 experts 1 community 1 sources clustered
404 Media Joseph Cox Jason Koebler
How the network is reacting 3 experts are independently emphasizing concern & critique.
Reaction converging

Concern & critique

3 experts

Risks, limits and unintended consequences.

“'Black October:' The PHP vulnerabilities and a series of other hacks and bugs have cybersecurity experts freaking out and unsure what happens next. www.404media.co/php2shell-bl...”

Primary source 404media.co ↗
New Safety & security Research 19h ago
KL-DRO adaptive scenario generation paper

Adaptive Scenario Generation for KL-DRO Around a Learned Density Model

1 directory member surfaced this signal.

Why this matches Concern & critique reaction 1 attributable expert contribution · AI Firehose
“MIT researchers developed a new approach to distributionally robust optimization by centering a Kullback-Leibler ball on a learned density model. This method addresses unobserved data and tail risks, achieving notable cost reductions under distribution shif…” evidence ↗
1 expert 1 community 1 sources clustered
AI Firehose

“MIT researchers developed a new approach to distributionally robust optimization by centering a Kullback-Leibler ball on a learned density model. This method addresses unobserved data and tail risks, achieving notable cost reductions under distribution shif…”

Primary source arxiv.org ↗
Debates gaining attention

What experts are discussing without an anchoring article

6 experts · 30 posts · 1d ago
Mar Hicks e.w. niedermeyer VE, cybersocial occult investigator Anthony Moser tweety fish Amy Hoy
Matches Concern & critique
“@vortexegg.com has described a spectrum of "slop vs care" I find useful because it captures how most ai/LLM related problems aren't really new, but existing harms amplified in that context we can t…” evidence ↗
Multiple readings Questions & unknowns · 2 Concern & critique · 1 Research & technical analysis · 1
e.w. niedermeyer: AI slop is a supply side game-changer, so it's easy to focus there, but ultimately everything comes down to demand: will the public, in aggregate, be satisfied with slop or demand more? skeptics ha…
e.w. niedermeyer: covering cars you have to separate your personal taste from what the market demands, and that's hard when it comes down to something like slop restaurant menus... I find them viscerally off-putting…
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