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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: Why Google Will Win the AI Arms Race & OpenAI Will Not | NVIDIA vs AMD: Who Wins and Why | The Future of Inference vs Training | The Economics of Compute & Why To Win You Must Have Product, Data & Compute with Steeve Morin @ ZML
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

20VC: Why Google Will Win the AI Arms Race & OpenAI Will Not | NVIDIA vs AMD: Who Wins and Why | The Future of Inference vs Training | The Economics of Compute & Why To Win You Must Have Product, Data & Compute with Steeve Morin @ ZML

Harry Stebbings 1h 12m 14 months ago
The Twenty Minute VC (20VC) interviews the world's greatest venture capitalists with prior guests including Sequoia's Doug Leone and Benchmark's Bill Gurley. Once per week, 20VC Host, Harry Stebbings is also joined by one of the great founders of our time with prior founder episodes from Spotify's Daniel Ek, Linkedin's Reid Hoffman, and Snowflake's Frank Slootman. If you would like to see more of The Twenty Minute VC (20VC), head to www.20vc.com for more information on the podcast, show notes, resources and more.
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Steeve Morin is the Founder & CEO @ ZML, a next-generation inference engine enabling peak performance on a wide range of chips. Prior to founding ZML, Steeve was the VP Engineering at Zenly for 7 years leading eng to millions of users and an acquisition by Snap. 
In Today's Episode We Discuss:
How Will Inference Change and Evolve Over the Next 5 Years
Challenges and Innovations in AI Hardware
The Economics of AI Compute
Training vs. Inference: Infrastructure Needs
The Future of AI Chips and Market Dynamics
Nvidia's Market Position and Competitors
Challenges of Incremental Gains in the Market
The Zero Buy-In Strategy
Switching Between Compute Providers
The Importance of a Top-Down Strategy for Microsoft and Google
Microsoft's Strategy with AMD
Data Center Investments and Training
How to Succeed in AI: The Triangle of Products, Data, and Compute
Scaling Laws and Model Efficiency
Future of AI Models and Architectures
Retrieval Augmented Generation (RAG)
Why OpenAI's Position is Not as Strong as People Think
Challenges in AI Hardware Supply
 

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