What Happens After A 1,000,000x AI Compute Leap? | Jeff Dean
Jeff Dean argues there is still plenty of training data left despite fears LLMs are running out.
“it's true we've like used quite a lot of of the public text data in the world”— Jeff Dean
In a Two Minute Papers interview, Google chief scientist Jeff Dean pushes back on the widespread 'data wall' narrative, conceding that most public text has been consumed but maintaining substantial untapped data remains. As a leading figure behind MapReduce, TensorFlow, and Google Brain, his stance on data scarcity carries weight for how the industry frames the limits of LLM scaling.