Google DeepMind study finds LLMs can’t reliably roll their own dice
Photo: Crypto Briefing
New research shows large language models produce biased random outputs, but sample accurately when handed random numbers from code Ask a large language model to pick a random number, and it will happily oblige. According to new research from Google DeepMind, it just won’t be very random about it. A paper titled “The Illusion of Stochasticity in LLMs” argues that reliable random sampling is a basic requirement for AI agents. It also argues that today’s models don’t meet it. The study was produced by Google DeepMind in collaboration with the National University of Singapore.
Source: Crypto Briefing
