The a16z Show

MTS host Sophia Dew visits the Open Source AI Summit in San Francisco to ask researchers and founders across the AI stack a central question: can open source prevent AI power from concentrating in the hands of a few companies?
Lukasz Kaiser, co-author of Attention Is All You Need, argues that today’s concentration may be a feature of the current technological paradigm rather than a permanent feature of AI. Transformers reward enormous amounts of data and compute, but future breakthroughs could make smaller, more specialized models far more capable.
Across conversations with researchers and builders working on open models, infrastructure, and applications, Sophia explores why China has taken the lead in open-weight models, whether the U.S. needs more open-model startups, what it means for companies to own their own intelligence, and where openness alone falls short, particularly when access to compute remains concentrated.

Resources:
Follow Lukasz Kaiser on X: https://x.com/lukaszkaiser
Follow Sophia Dew on X: https://x.com/sophiadew
Follow MTS on X: https://x.com/mtslive



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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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a16z General Partner Julie Yoo joins MTS host Sophia Dew to explain why she believes healthcare could benefit more from AI than almost any other industry, and why decades of slow technology adoption may actually give healthcare an advantage in the AI era.
Julie traces healthcare’s evolution from paper records and fax machines through electronic health records and telehealth, and explains why AI represents something different: an organic adoption wave driven by tools that doctors and patients actually want to use. Because healthcare never built the same layers of legacy software as other industries, it may now be able to leapfrog directly into agentic AI.
They also explore how AI could dramatically lower the cost of care, why consumers are becoming a more important payer, where Julie sees the biggest opportunities for healthcare founders, and a future where everyone has a highly personalized AI doctor in their pocket for life.

Resources:
Follow Julie Yoo on X: https://x.com/julesyoo
Follow Sophia Dew on X: https://x.com/sophiadew
Follow MTS on X: https://x.com/mtslive



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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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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.
Aaron 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.
They 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.

Resources:
Follow Aaron Levie on X: https://x.com/levie
Follow Theo Jaffee on X: https://x.com/theojaffee
Follow Sofia Puccini on X: https://x.com/schisofrenia
Follow MTS on X: https://x.com/mtslive


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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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World Labs co-founders Fei-Fei Li, Justin Johnson, and Ben Mildenhall join a16z General Partner Martin Casado to discuss Atlas, their latest world model, and what it reveals about the pursuit of spatial intelligence.
At the center of Atlas is what the team calls “new view prediction”: given images or views of a scene, the model predicts what that environment should look like from a different position in space and time. This brings generation and 3D reconstruction into the same model, and raises a broader question about whether predicting views could become a useful primitive for understanding the physical world.
They discuss the technical bets behind the model, what it can and can’t yet capture, and the importance of dynamics, editability, and simulation as world models develop. The conversation also explores applications in creative work, architecture, and robotics, where Fei-Fei argues that one of today’s biggest constraints is access to real-world training data.

Resources:
Follow Fei-Fei Li on X: https://x.com/drfeifei
Follow Justin Johnson on X: https://x.com/jcjohnss
Follow Ben Mildenhall on X: https://x.com/BenMildenhall
Follow Martin Casado on X: https://x.com/martin_casado
Learn more about Atlas: https://www.worldlabs.ai/blog/atlas



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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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Erik Torenberg is joined by a16z General Partner Alex Rampell and Affirm Co-Founder and CEO Max Levchin for a conversation on 25 years of fintech, from the early days of digital payments to the origins of Affirm and the next generation of agentic commerce.
Max and Alex revisit what surprised them most about how payments evolved, why the card interface has been so difficult to displace, and why even the smallest corners of payments can become enormous markets. They also trace the early idea maze behind Affirm, from "pay with your identity" and the pajama problem to the realization that installment financing could dramatically increase merchant conversion.
The conversation also gets into real versus "fake" 0% financing, what people misunderstand about Affirm today, why negative customer acquisition cost can be such a powerful business model advantage, and why Max is more bullish on agentic payments than on agents choosing what people buy.

Resources:
Follow Max Levchin on X: https://x.com/mlevchin
Follow Alex Rampell on X: https://x.com/arampell



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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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