Paul Hünermund

Professor of Empirical Economics & Data Science at TU Munich | Heilbronn Data Science Center (HDSC) | Co-founder of causalscience.org

Articles & links

According to a new NBER paper, to justify the AI investment surge we're seeing, the implied productivity gains need to be enormous. The authors calibrate a model where AI-sector productivity rises by roughly 2.7x. Link: www.nber.org/papers/w35290

What Investment Data Implies about the AI Transition nber.org
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Recent commentary

The current AI buildout only makes sense if it delivers massive productivity gains. The biggest US tech firms are on track to spend ~$755B on AI capex in 2026, up from $155B in 2022. At this point, AI is not just a tech story. It's a macro bet.

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🧵1/4 📢 Call for submissions: Causal Data Science Meeting 2026 Join researchers and practitioners from academia and industry for a virtual meeting on Nov 4–5, 2026, exploring the role of causality in machine learning and AI. #CDSM2026

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I tried Positron AI in RStudio today and it was amazing

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