Theory

Overview Speaker: Lei Zhang Date: Friday, September 4, 2026, 2:30 PM Room: PM103 Recursive self-improvement is one of the more plausible candidates for the next big thing in AI, and the real technical pivot under most AGI-timeline arguments. The system applies itself to itself. The essential move is self-application, which is why you can’t discuss RSI without fixed points. But “fixed point” here is three different things: Kleene’s second recursion theorem The Y combinator x* = f(x*) They don’t substitute for each other, and conflating them flips conclusions. The talk separates the three, then uses that ruler on deep equilibrium models (DEQs), neural architecture search (NAS), self-referential weight matrices, and neural quines. ...

Overview On October 3, 2025, Md. Toyaha Rahman Ratul, a Ph.D. student at Northern Illinois University, presented a recent paper titled “On the Theoretical Limitations of Embedding-Based Retrieval,” authored by researchers from Google DeepMind and Johns Hopkins University. The paper formally examines and reveals the inherent limitations of single-embedding-based retrieval methods—approaches widely adopted in both industry and academia—thereby having a significant impact on the research community. ...