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.

2,364 searchable experts 2,966 tracked across all sources
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Showing developments with attributable Policy & governance reactions.

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Posts are grouped by conversation and tone. Select a lens to filter the stream; these are never permanent labels on people.

Showing signals surfaced by Jason Koebler ×

The developments commanding sustained expert attention

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

New AI field signal Development 6h ago
⚡ 6 h early
AI companies buy old books

AI Companies Are Buying Tons of Old Books Because They're Free of AI Slop

12 experts across 3 network communities independently surfaced this.

Why this matches Policy & governance reaction 1 attributable expert contribution · Jason Koebler
“this ai ripoff, which again has no link, then goes to the top of hackernews, which used to drive a considerable number of readers to us. our site is essentially banned from hackernews bc the mods are obsessively pro silicon valley even though the userbase i…” evidence ↗
12 experts 3 communities 1 sources clustered
How the network is reacting Experts are approaching this through 3 distinct lenses.
Multiple readings

Concern & critique

2 experts

Risks, limits and unintended consequences.

“It is ill-gotten gains being used to exploit legal loopholes and subsume culture, all protected from public criticism by NDAs. This should not be legal, and it is a travesty that it is going unpunished. www.404media.co/ai-companies... /end”

Research & technical analysis

2 experts

Evidence, methods and technical implications.

“companies are sourcing millions of printed books for AI labs that scan them for training data, then destroy them. printed books are more valuable because they're free of AI slop, and AI labs know destroying them is an "optics problem." www.404media.co/ai-co…”

Policy & governance

1 expert

Rules, institutions and accountability.

“this ai ripoff, which again has no link, then goes to the top of hackernews, which used to drive a considerable number of readers to us. our site is essentially banned from hackernews bc the mods are obsessively pro silicon valley even though the userbase i…”

2 experts discussed this · 2 posts
Emanuel Maiberg: companies are sourcing millions of printed books for AI labs that scan them for training data, then destroy them. printed books are more valuable because they're free of AI slop, and AI labs know d…
Meredith Broussard: companies are sourcing millions of printed books for AI labs that scan them for training data, then destroy them. printed books are more valuable because they're free of AI slop, and AI labs know d…
Neil Turkewitz: How do you spell TRAGEDY?
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Developing AI field signal Development 2d ago
⚡ 2 h early
Suno AI music scraping revealed hack

Hack Reveals Suno AI Music Generator Scraped YouTube, Deezer, and Genius

10 experts across 4 network communities independently surfaced this.

Why this matches Policy & governance reaction 1 attributable expert contribution · Mark Riedl
“Hack reveals that Suno (AI music generator) was trained on copyrighted music www.404media.co/hack-reveals...” evidence ↗
10 experts 4 communities 1 sources clustered
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.

“Interesting to see exactly where Suno's training data came from.”

Policy & governance

1 expert

Rules, institutions and accountability.

“Hack reveals that Suno (AI music generator) was trained on copyrighted music www.404media.co/hack-reveals...”

2 experts discussed this · 25 posts
Jason Koebler: Scoop: The AI music generator Suno was hacked. Hacker shared source code that shows how the tool was made and part of the music and podcasts that were scraped to create it. Decades worth of music, …
Jason Koebler: Suno also scraped episodes from roughly 420,000 different podcasts, which was at least ~1 million hours of audio. They had code that specifically sought acapella versions of songs on YouTube for vo…
Jason Koebler: Customer emails/phone numbers & Stripe payment details were also hacked; no one was ever notified because the company deemed it wasn't important to
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