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

Arthur Mensch is the Co-Founder and CEO of Mistral AI. Since its inception in May 2023, Mistral has raised over $520M in funding from investors like Andreeseen Horowitz, General Catalyst, Lightspeed Venture Partners, and Microsoft with a current valuation of $2 billion. Before founding Mistral, Arthur was a research scientist at DeepMind, one of the leading AI institutions in the world.

In Today’s Episode with Arthur Mensch We Discuss: 1.

From Models to Team Building: Arthur’s Greatest Lessons at DeepMind 2. •

What were Arthur’s biggest lessons from his time at DeepMind? • •

How did DeepMind shape how Arthur built Mistral? • •

Why does Arthur believe smaller teams are better for AI? • •

Why did Arthur decide to leave DeepMind and start Mistral? • 1.

Scaling Mistral to $2 Billion Valuation Within a Year 2. •

What made Mistral 7B so successful? What did Arthur learn from the model release? • •

What are the biggest barriers at Mistral today? • •

How does Arthur balance the sales and research teams at Mistral? • •

What does Arthur know now that he wishes he had known when he started Mistral? • 1.

How to Win in AI: Open Source, Cost, & Adoption 2. •

Why did Arthur open-source some models? Why did he close some? • •

How quickly will the cost of compute go down? Why does Arthur believe marginal costs will not go to zero? • •

How will open-sourcing LLMs affect the marginal cost? • •

Does Arthur think open source is ready for enterprise adoption? • •

What questions should enterprises be asking about AI adoption today? • •

What are the biggest challenges to AI adoption today? • 1.

The Future of LLMs 2. •

What does Arthur think are the largest bottlenecks of model quality today? • •

Does Arthur think future models will be more generalized or vertical-focused? • •

What does Arthur think about the future of commoditization in models? • •

Why is Arthur optimistic about the profitability of the application layer of AI? • •

How should models differentiate themselves today? •