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Is AI running out of things to learn from? David and Dustin open on the "peak data" problem — the shrinking supply of high-quality, human-generated training data — and whether more compute and synthetic data can keep the gains coming or just poison the well. From there: the device that finally replaces your smartphone (Qualcomm's CEO is betting on always-on glasses within ten years; David is very much not sold), PwC's two-track AI jobs market and the entry-level rung quietly disappearing beneath it, and the first randomized clinical trial of ambient AI scribes in the exam room — modest time savings, but real relief from burnout. Plus a KCL tip that kills the "does Tuesday work?" email chain for good, and parting shots on building your own AI skills and HBO's Chernobyl.
Chapters
Email us at [email protected] with questions, thoughts, or topic ideas.
By David Hotchkiss and Dustin J. MartinIs AI running out of things to learn from? David and Dustin open on the "peak data" problem — the shrinking supply of high-quality, human-generated training data — and whether more compute and synthetic data can keep the gains coming or just poison the well. From there: the device that finally replaces your smartphone (Qualcomm's CEO is betting on always-on glasses within ten years; David is very much not sold), PwC's two-track AI jobs market and the entry-level rung quietly disappearing beneath it, and the first randomized clinical trial of ambient AI scribes in the exam room — modest time savings, but real relief from burnout. Plus a KCL tip that kills the "does Tuesday work?" email chain for good, and parting shots on building your own AI skills and HBO's Chernobyl.
Chapters
Email us at [email protected] with questions, thoughts, or topic ideas.