20VC: NVIDIA vs Groq: The Future of Training vs Inference | Meta, Google, and Microsoft's Data Center Investments: Who Wins | Data, Compute, Models: The Core Bottlenecks in AI & Where Value Will Distribute with Jonathan Ross, Founder @ Groq

Jonathan Ross is the Founder & CEO of Groq, the creator of the world’s  first Language Processing Unit (LPUTM). Prior to Groq, Jonathan began  what became Google’s Tensor Processing Unit (TPU) as a 20% project where he  designed and implemented the core elements of the first-generation TPU chip.  Jonathan next joined Google X’s Rapid Eval Team, the initial stage of the famed  “Moonshots Factory”, where he devised and incubated new Bets (Units) for Google’s  parent company, Alphabet.

In Today’s Episode We Discuss:

04:20 Interview with Jonathan Ross Begins

04:59 Scaling Laws and AI Model Training

06:22 Synthetic Data and Model Efficiency

12:01 Inference vs. Training Costs: Why NVIDIA Loses Inference

17:06 The Future of AI Inference: Efficiency and Cost

18:15 Chip Supply and Scaling Concerns

20:57 Energy Efficiency in AI Computation

25:40 Why Most Dollars Into Datacenters Will Be Lost

31:05 Meta, Google, and Microsoft's Data Center Investments

41:11 Distribution of Value in the AI Economy

42:10 Stages of Startup Success

43:17 The AI Investment Bubble

45:00 The Keynesian Beauty Contest in VC

48:40 NVIDIA's Role in the AI Ecosystem

53:39 China's AI Strategy and Global Implications

57:51 Europe's Potential in the AI Revolution

01:10:14 Future Predictions and AI's Impact on Society