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