Guido Appenzeller

Raghu Raghuram × Guido Appenzeller × Pat Gelsinger

AI is compressing logic design faster than silicon, packaging, and rack deployment, shifting value toward manufacturing, memory, power, cooling, and integration.With roughly 100 AI processor vendors, consolidation is likely as workloads evolve and winners require major capital, software, and customer backing, though agent-generated kernels may preserve some heterogeneity.Memory may be positioned for its first major reset in 30 years, while optical scale-up I/O around 2028–2029 and power shortages, including eight-year turbine lead times, define key catalysts and risks.

Erik Torenberg × Dylan Patel × Sarah Wang × Guido Appenzeller

Nvidia’s $5 billion Intel investment, following SoftBank’s $2 billion and the U.S. government’s $10 billion, could lower Intel’s cost of capital and redraw PC and data-center competition, though Patel says Intel still needs roughly $50 billion.Huawei has credible 7 nm designs and ambitious custom-HBM products, but HBM3 yields, etch capacity, and domestic volume remain unresolved as Nvidia’s upside depends on $450–500 billion of hyperscaler capex rather than further share gains.

Dylan Patel × Erin Price-Wright × Guido Appenzeller × Erik Torenberg

GPT-5’s router is an economic release, directing simple queries to mini models while reserving “ungodly amounts of compute” for transactions OpenAI could monetize through agentic commerce.Flat-rate subscriptions face heavy-user losses, while custom silicon threatens Nvidia mainly if demand stays concentrated among hyperscalers; powered sites, grid equipment, and Intel’s capital needs remain near-term constraints on broader deployment.