A Unified Memory Perspective for Probabilistic Trustworthy AI

Researchers present a unified framework for probabilistic AI computation that treats deterministic and stochastic data access under a common perspective. The study identifies memory systems as performance bottlenecks in trustworthy AI and proposes compute-in-memory approaches to address scalability challenges.