A recent survey of 475 AI researchers reveals that 76% believe adding more computing power and data to current AI models is «unlikely» or «very unlikely» to.
Why it matters: Major tech players have spent the last few years betting that simply throwing more computing power at AI will lead to artificial general intelligence systems that match or surpass human cognition. But a recent survey of AI researchers suggests growing skepticism that endlessly scaling up current approaches is the right path forward.
A recent survey of 475 AI researchers reveals that 76% believe adding more computing power and data to current AI models is «unlikely» or «very unlikely» to lead to AGI.
The survey, conducted by the Association for the Advancement of Artificial Intelligence (AAAI), reveals a growing skepticism. Despite billions poured into building massive data centers and training ever-larger generative models, researchers argue that the returns on these investments are diminishing.
Stuart Russell, a computer scientist at UC Berkeley and a contributor to the report, told New Scientist: «The vast investments in scaling, unaccompanied by any comparable efforts to understand what was going on, always seemed to me to be misplaced.
