
An analyst went through sixty-eight AI models and found that exactly zero of the downloadable ones qualify as open source. In this episode, host Emily Laird explains what open weights actually gets you (the house, not the blueprints) and why the training data you never see is the only part that matters. She also walks through Jensen Huang's first post on X, the distillation argument buried inside it, and the EU AI Act exemption that vanishes right when a model gets capable enough to be worth using. If you have told your board you are running open source AI, consider this a correction.
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