- 1 Reflections from #AIES2025 ↗
- 2 Deep learning-powered biochip to detect genetic markers ↗
- 3 Half of AI health answers are wrong even though they sound convincing – new study ↗
- 4 Gradient-based planning for world models at longer horizons ↗
- 5 It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea ↗
- 6 Making AI systems more transparent and trustworthy: an interview with Ximing Wen ↗
- 7 Report on foundation model impacts released ↗
- 8 Forthcoming machine learning and AI seminars: May 2026 edition ↗
- 9 AI for Science – from cosmology to chemistry ↗
- 10 AIhub monthly digest: April 2026 – machine learning for particle physics, AI Index Report, and table tennis ↗
- 11 The Machine Ethics podcast: organoid computing with Dr Ewelina Kurtys ↗
- 12 #AAAI2026 invited talk: Yolanda Gil on improving workflows with AI ↗
- 13 Maryna Viazovska’s proofs of sphere packing formalized with AI ↗
- 14 Interview with Deepika Vemuri: interpretability and concept-based learning ↗
- 15 As a ‘book scientist’ I work with microscopes, imaging technologies and AI to preserve ancient texts ↗
- 16 Sony AI table tennis robot outplays elite human players ↗
- 17 Causal models for decision systems: an interview with Matteo Ceriscioli ↗
- 18 A model for defect identification in materials ↗
- 19 ‘Probably’ doesn’t mean the same thing to your AI as it does to you ↗
- 20 Interview with Xinwei Song: strategic interactions in networked multi-agent systems ↗
- 21 2026 AI Index Report released ↗
- 22 Formal verification for safety evaluation of autonomous vehicles: an interview with Abdelrahman Sayed Sayed ↗
- 23 Water flow in prairie watersheds is increasingly unpredictable — but AI could help ↗
- 24 Identifying interactions at scale for LLMs ↗
- 25 Interview with Sukanya Mandal: Synthesizing multi-modal knowledge graphs for smart city intelligence ↗
- 26 Emergence of fragility in LLM-based social networks: an interview with Francesco Bertolotti ↗
- 27 Scaling up multi-agent systems: an interview with Minghong Geng ↗
- 28 Forthcoming machine learning and AI seminars: April 2026 edition ↗
- 29 #AAAI2026 invited talk: machine learning for particle physics ↗
- 30 AIhub monthly digest: March 2026 – time series, multiplicity, and the history of RoboCup ↗