

20VC: Mistral's Arthur Mensch: Are Foundation Models Commoditising | How Do We Solve the Problem of Compute | Is There Value in the Application Layer | Open vs Closed: Who Wins and Mistral's Position
65 snips Apr 29, 2024
Arthur Mensch, Co-founder and CEO of Mistral AI and former research scientist at DeepMind, shares insights on harnessing foundation models in AI. He discusses key lessons learned from DeepMind, emphasizing the advantages of smaller teams for innovation. Mensch reflects on the rapid success of Mistral, exploring challenges in scaling and the importance of balancing sales with research. The conversation also delves into the dynamics of open-source versus closed models and the future of AI adoption, particularly in Europe, highlighting the value of effective partnerships.
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Small Teams
- Small, uncoupled teams of five are more effective than large, coupled teams.
- Share infrastructure, codebase, and findings, but minimize coordination meetings.
Leaving DeepMind
- Arthur Mensch's decision to leave DeepMind wasn't binary, but a gradual leaning towards leaving.
- The point of no return came around March when he decided to leave and resigned shortly after.
Mistral 7B's Success
- Mistral 7B's success stemmed from addressing a gap in the efficiency-performance space.
- It targeted developers by being efficient enough to run on MacBooks and smartphones, while still being useful.