🔬 Research Summary by Stephen Casper, an MIT PhD student working on AI interpretability, diagnostics, and safety. [Original paper by Stephen Casper,* Xander Davies,* Claudia Shi, Thomas Krendl Gilbert, Jérémy … [Read more...] about Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Technical Methods
A Critical Analysis of the What3Words Geocoding Algorithm
🔬 Research Summary by Rudy Arthur, a Senior Lecturer in Data Science at the University of Exeter. [Original paper by Rudy Arthur] Overview: What3Words (W3W) is a geocoding app that has been aggressively … [Read more...] about A Critical Analysis of the What3Words Geocoding Algorithm
Self-Consuming Generative Models Go MAD
🔬 Research Summary by Josue Casco-Rodriguez and Sina Alemohammad. Josue is a 2nd-year PhD student at Rice University. He is interested in illuminating the intersection of machine learning and neuroscience from … [Read more...] about Self-Consuming Generative Models Go MAD
Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
🔬 Research Summary by Faisal Hamman, a Ph.D. student at the University of Maryland, College Park. Faisal’s research focuses on Fairness, Explainability, and Privacy in Machine Learning, where he brings novel foundational … [Read more...] about Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
Open-source provisions for large models in the AI Act
🔬 Research Summary by Harry Law and Sebastien A. Krier. Harry Law is an ethics and policy researcher at Google DeepMind, a PhD candidate at the University of Cambridge, and postgraduate fellow at the Leverhulme … [Read more...] about Open-source provisions for large models in the AI Act