Meta pulled its Avocado model after internal benchmarks exposed failures in reasoning, coding, and writing. That delay matters because it signals the gap between announced timelines and actual capability thresholds is widening, even at a lab with Meta's resources.
XAI is losing co-founders while simultaneously poaching senior product talent from Cursor, the AI coding tool. That combination, recruitment from a competitor plus internal exits, tells you something specific about where XAI thinks its product gaps are. Meanwhile, 81% of doctors now use AI for documentation, but enterprise AI adoption is still operationally stalled, a split worth understanding in detail.
Sam Altman's framing of AI as a metered utility is the thread worth pulling on in the full episode. It reframes the economics of AI deployment and connects directly to the capitalism and labor arguments the industry is circling. The reasoning behind each of these four stories, not just the outcomes, is what makes this one worth the full listen.
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