20VC: OpenAI and Anthropic Will Build Their Own Chips | NVIDIA Will Be Worth $10TRN | How to Solve the Energy Required for AI... Nuclear | Why China is Behind the US in the Race for AGI with Jonathan Ross, Groq Founder
Jonathan Ross is the Founder & CEO of Groq, the AI chip company redefining inference at scale. Under his leadership, Groq has raised over $3B from top investors. The company has reached a valuation of nearly $7B, positioning itself as one of NVIDIA's most formidable challengers. Previously at Google, Jonathan led the team that built the first Tensor Processing Unit (TPU), making him one of the leading architects of modern AI hardware.
AGENDA:
00:00 The Future of AI and Compute
05:07 Why the Hyperscalers Have to Keep Spending Recklessly on AI
12:49 Why OpenAI and Anthropic Will Have to Build Their Own Chips
19:47 OpenAI and Anthropic Will be $5BN Companies: The Bull Case
29:50 Why China is Behind the US in AI and Deepseek is More Expensive to Run
33:55 How Europe Could Compete in AI and Why the US is More Risk Averse Than Europe
42:51 Why AI Will Lead to Too Many Not Too Few Jobs
43:19 Deflationary Pressures and New Job Markets
45:51 The Future of Vibe Coding
47:14 Why AI Companies Should Strive to Have Low Margins
49:31 Why We Have to Have Nuclear Energy and How to Bring it Back
56:55 How Permits are Ruining the Potential of AI
01:03:58 Why OpenAI and Anthropic are so Undervalued
01:16:53 Quickfire: Biggest Fear, Nvidia: $10TRN, Zuck Buying AI: Work or Not
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
20VC: Deepseek Special: Is Deepseek a Weapon of the CCP | How Should OpenAI and the US Government Respond | Why $500BN for Stargate is Not Enough | The Future of Inference, NVIDIA and Foundation Models with Jonathan Ross @ Groq
Jonathan Ross is the Co-Founder and CEO of Groq, providing fast AI inference. Prior to founding Groq, Jonathan started Google's TPU effort where he designed and implemented the core elements of the original chip. Jonathan then joined Google X's Rapid Eval Team, the initial stage of the famed "Moonshots factory," where he devised and incubated new Bets (Units) for Alphabet.
The 10 Most Important Questions on Deepseek:
How did Deepseek innovate in a way that no other model provider has done?
Do we believe that they only spent $6M to train R1?
Should we doubt their claims on limited H100 usage? Is Josh Kushner right that this is a potential violation of US export laws?
Is Deepseek an instrument used by the CCP to acquire US consumer data?
How does Deepseek being open-source change the nature of this discussion?
What should OpenAI do now? What should they not do?
Does Deepseek hurt or help Meta who already have their open-source efforts with Lama?
Will this market follow Satya Nadella's suggestion of Jevon's Paradox?
How much more efficient will foundation models become?
What does this mean for the $500BN Stargate project announced last week?