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:
04:17 How Will Inference Change and Evolve Over the Next 5 Years
09:17 Challenges and Innovations in AI Hardware
15:38 The Economics of AI Compute
18:01 Training vs. Inference: Infrastructure Needs
25:08 The Future of AI Chips and Market Dynamics
34:43 Nvidia's Market Position and Competitors
38:18 Challenges of Incremental Gains in the Market
39:12 The Zero Buy-In Strategy
39:34 Switching Between Compute Providers
40:40 The Importance of a Top-Down Strategy for Microsoft and Google
41:42 Microsoft's Strategy with AMD
45:50 Data Center Investments and Training
46:40 How to Succeed in AI: The Triangle of Products, Data, and Compute
48:25 Scaling Laws and Model Efficiency
49:52 Future of AI Models and Architectures
57:08 Retrieval Augmented Generation (RAG)
01:00:52 Why OpenAI’s Position is Not as Strong as People Think
01:06:47 Challenges in AI Hardware Supply
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By Harry Stebbings
4.4
470470 ratings
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:
04:17 How Will Inference Change and Evolve Over the Next 5 Years
09:17 Challenges and Innovations in AI Hardware
15:38 The Economics of AI Compute
18:01 Training vs. Inference: Infrastructure Needs
25:08 The Future of AI Chips and Market Dynamics
34:43 Nvidia's Market Position and Competitors
38:18 Challenges of Incremental Gains in the Market
39:12 The Zero Buy-In Strategy
39:34 Switching Between Compute Providers
40:40 The Importance of a Top-Down Strategy for Microsoft and Google
41:42 Microsoft's Strategy with AMD
45:50 Data Center Investments and Training
46:40 How to Succeed in AI: The Triangle of Products, Data, and Compute
48:25 Scaling Laws and Model Efficiency
49:52 Future of AI Models and Architectures
57:08 Retrieval Augmented Generation (RAG)
01:00:52 Why OpenAI’s Position is Not as Strong as People Think
01:06:47 Challenges in AI Hardware Supply
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