{"href":"https://api.simplecast.com/oembed?url=https%3A%2F%2Fa16z.simplecast.com%2Fepisodes%2Faaron-levie-on-why-open-ai-wins-YUnuv_hR","width":444,"version":"1.0","type":"rich","title":"Aaron Levie on Why Open AI Wins","thumbnail_width":300,"thumbnail_url":"https://image.simplecastcdn.com/images/0d97354a-306b-45f5-bf26-a8d81eef47ec/ed2664df-9371-438e-8baf-dd2ee0fdde87/thea16zshow-podcastcoverart-3000x3000.jpg","thumbnail_height":300,"provider_url":"https://simplecast.com","provider_name":"Simplecast","html":"<iframe src=\"https://player.simplecast.com/fa4d1de0-221c-4305-9b44-d8ee5ef2a0db\" height=\"200\" width=\"100%\" title=\"Aaron Levie on Why Open AI Wins\" frameborder=\"0\" scrolling=\"no\"></iframe>","height":200,"description":"Box co-founder and CEO Aaron Levie joins MTS hosts Theo Jaffee and Sofia Puccini to make the case for open-weight AI, unpack the economics of open versus closed models, and explain why he believes more openness could strengthen rather than undermine the U.S. AI ecosystem.\nAaron argues that open models create more use cases, push closed labs to innovate faster, and don't fundamentally change where the economics of AI ultimately accrue. They debate model distillation, America's competition with China, why restricting access may simply accelerate competing AI ecosystems, and whether U.S. labs should begin releasing open-weight versions of previous-generation models.\nThey also get into what the latest frontier models mean for knowledge work, how AI has changed software engineering at Box, and why Aaron believes companies cutting engineers may simply not be ambitious enough. Finally, they discuss why enterprises are unlikely to bet on a single model and why the layer that routes between models, data, and workflows could become increasingly valuable.\n"}