Open Source bi-weekly convo w/ Bill Gurley and Brad Gerstner on all things tech, markets, investing & capitalism. This week they are joined by Dylan Patel, Founder & Chief Analyst at SemiAnalysis, to discuss origins of SemiAnalysis, Google's AI workload, NVIDIA's competitive edge, the shift to GPUs in data centers, the challenges of scaling AI pre-training, synthetic data generation, hyperscaler capital expenditures, the paradox of building bigger clusters despite claims that pretraining is obsolete, inference-time compute, NVIDIA's comparison to Cisco, evolving memory technology, chip competition, future predictions, & more. Enjoy another episode of BG2!
Timestamps:
(00:00) Intro
(01:50) Dylan Patel Backstory
(02:36) SemiAnalysis Backstory
(04:18) Google's AI Workload
(06:58) NVIDIA's Edge
(10:59) NVIDIA's Incremental Differentiation
(13:12) Potential Vulnerabilities for NVIDIA
(17:18) The Shift to GPUs: What It Means for Data Centers
(22:29) AI Pre-training Scaling Challenges
(29:43) If Pretraining Is Dead, Why Bigger Clusters?
(34:00) Synthetic Data Generation
(36:26) Hyperscaler CapEx
(38:12) Pre-training and Inference-tIme Reasoning
(41:00) Cisco Comparison to NVIDIA
(44:11) Inference-time Compute
(53:18) The Future of AI Models and Market Dynamics
(01:00:58) Evolving Memory Technology
(01:06:46) Chip Competition
(01:07:18) AMD
(01:10:35) Google’s TPU
(01:14:51) Amason’s Tranium
(01:17:33) Predictions for 2025 and 2026
Available on Apple, Spotify, www.bg2pod.com
Follow:
Brad Gerstner @altcap
Bill Gurley @bgurley
Dylan Patel @dylan522p
BG2 Pod @bg2pod