Here's the paper with Zoë Hitzig: https://
nber.org/system/files/c
hapters/c15303/c15303.pdf
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RESEARCH
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New Research Paper on AI Policy with Zoë Hitzig
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Transformative AI Centralizes Decision-Making Power and Embedded Knowledge
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Our argument focuses on the potential of transformative AI (TAI) to codify judgment, heuristics, and know-how that once stayed embedded in people, teams, and local settings. TAI can shift decision-making toward whoever controls the models, data, and compute.
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AI May Drive Extreme Economic and Political Concentration Risk
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The @nytimes piece today by @ByrneEdsal13590 highlights a concern I share: “If we stay on the current path, the risk of extreme concentration — both economic and political — is very real.” In work with @zhitzig
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Google Street View Aerial Data Powers Grounded AI Genie
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it's all over when google realizes the treasure trove that is street view + aerial data and launches a version of genie grounded in the real world… https://t.co/CWQ0vPjNuJ
— Bilawal Sidhu (@bilawalsidhu) 17 mars 2026it's all over when google realizes the treasure trove that is street view + aerial data and launches a version of genie grounded in the real world…
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Princeton Review Highlights Persistent LLM Reliability Issues
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BREAKING: Reliability, which I have been harping on here since 2019, continues to be deep problem, even with the latest models. A new @Princeton review below offers a taxonomy of some of the many ways in which reliability continues to haunt LLMs seven years and a trillion
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Comparing AI Model Performance: Sonnet vs Opus Benchmarks
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The label didn't fit in, it is slightly below Sonnet and Opus 4.5 – but I wouldn't read it too precisely, they are all about same ballpark, see here: https://
petergpt.github.io/bullshit-bench
mark/viewer/index.v2.html
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AI-Science Feedback Loop: Models and Scientists Advancing Together
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The feedback loop between domain experts and AI engineers is exactly what makes AI for science so exciting. The model gets better from the scientist, the scientist gets to explore more because of the model.
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AI Medical Breakthroughs Moving Beyond Human Knowledge
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tu vois qu'il donne des réponses de bot. Non la vraiment y'a une avancé phénoménale et moi je le vois côté avancées en médecine, on commence a s'éloigner du "c'est un humain qui l'a déjà dit"
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AI Secret: Scale versus Proprietary Techniques
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Is there a "secret sauce" driving the development of AI models?
— MIT CSAIL (@MIT_CSAIL) 17 mars 2026
FutureTech researchers at MIT CSAIL found that at the frontier, sheer scale drives LLM performance, but proprietary techniques & algorithmic advances matter more away from it: https://t.co/zi6jCN7twT pic.twitter.com/UpDdLG7c6YIs there a "secret sauce" driving the development of AI models? FutureTech researchers at MIT CSAIL found that at the frontier, sheer scale drives LLM performance, but proprietary techniques & algorithmic advances matter more away from it: bit.ly/4l76v2g [Translated from EN to English]
→ View original post on X — @mit_csail, 2026-03-17 16:00 UTC
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AstraZeneca and Tempus AI Achieve 15% Survival Benefit with Contrastive Learning
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AstraZeneca and Tempus AI used contrastive learning to find biomarkers that predict treatment response. Outcome: 15% survival benefit over traditional immuno-oncology trial designs. AI catching what human researchers couldn't. That's not incremental. #AI
→ View original post on X — @svenphilipsen, 2026-03-17 16:00 UTC