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HBO and The Ringer's Bill Simmons hosts the most downloaded sports podcast of all time, with a rotating crew of celebrities, athletes, and media staples, as well as mainstays like Cousin Sal, Joe House, and a slew of other friends and family members who always happen to be suspiciously available.
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Epic recently unveiled Comet, a new AI model trained on 118 million patient records to predict future health events. The scale is unprecedented, and its initial ability to outperform specialised models is a huge leap forward for clinical AI.
But what is it really learning from our messy, real-world data? In this today's episode, we break down why Comet is a landmark achievement but also an important wake-up call. We explore the challenges of "semantic drift" and documentation artifacts, and why the model's success will ultimately depend on an organisation's own data quality.
Is Comet a true crystal ball, or a reflection of medicine's past?
Paper: Generative Medical Event Models Improve with Scale by Waxler et al
Link: https://arxiv.org/abs/2508.12104
#HealthAI #EpicComet #ClinicalAI #DataQuality #DigitalHealth #FoundationModels #RWE #ai in medicine Music generated by Mubert https://mubert.com/render
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