Using Synthetic Data for AI Training Is 'a Big Mistake,' Says AI Pioneer Rich Sutton

A Turing Award winner says the industry’s fix for running out of data is ‘a big mistake’

Richard Sutton thinks the AI industry’s answer to running out of training data is a mistake, and he has picked a blunt word for it. “ That’s just a big mistake,” he said of the turn to synthetic data on Sequoia Capital’s Training Data podcast, published on Tuesday and hosted by Sonya Huang and Pat Grady. The […] This story continues at The Next Web

Using synthetic data for AI training is 'a big mistake,' says AI pioneer Rich Sutton

Richard Sutton said synthetic data is not the solution for scaling AI.Business Wire/APRich Sutton criticized tech's reliance on synthetic data, urging real-world experiential learning.Tech giants like Google and OpenAI are going out of their way for real-world data.Sutton's Oak Lab focuses on teaching AI agents from experiences, not made-up datasets.Rich Sutton helped pioneer the technology behind today's AI boom. Now he thinks Big Tech's push t…

KI-Pioneer Sutton calls synthetic data a "big mistake" in the face of an infinitely complex world

Turing Award winner Richard Sutton calls synthetic data a "big mistake" for scaling large language models. The world is infinitely complex, and any simulation of it is "microscopic," with human expertise acting as a bottleneck that blocks real scaling. Sutton's alternative is agents that learn continually from their own experience instead of relying on frozen models. The article KI-Pioneer Sutton calls synthetic data a "big mistake" in the face …