AIThe case for training AI on physiological signals, not just words
A post sharing an interview with Stanford professor James Zou presents his argument that superintelligence needs training on physiological signals because text captures only a fraction of brain and body activity.
TLDR
A post sharing an interview quotes Stanford professor James Zou describing written language as a “downstream artifact” representing “less than 1%” of actual thoughts. The post presents his argument for training AI on physiological signals rather than just text. It also highlights his lab’s Virtual Lab, described as autonomous AI agents modeled on his team; Paper2Agent, which turns papers into interactive “virtual authors”; and SleepFM, which the post says predicts risk for about 130 diseases from one night of sleep data.
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The case for training AI on physiological signals, not just words
A post sharing an interview with Stanford professor James Zou presents his argument that superintelligence needs training on physiological signals because text captures only a fraction of brain and body activity.