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generation, hyperscaler capital expenditures, the paradox of building bigger clusters despite claims that pretraining is obsolete, inference-time compute, NVIDIA's comparison to Cisco, evolving memory technology, chip competition, future predictions, & more.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