🎙️ NEW EPISODE: Synopsys Will Take a Royalty on Amazon's Chips and Sell GPT-Synopsys: Ravi Subramanian Ravi joins Austin to discuss why the company is moving to a royalty-based model for its custom "application optimized IP", starting with a billion-dollar deal with Amazon. Ravi also unpacks the OpenAI partnership and AI "agent engineers", and explains why physics-based simulation remains the ground truth. Insights: - Because 1-2 applications drive most of a hyperscaler's revenue, companies like Amazon now want custom "application optimized IP" instead of standards-based IP - The custom model has three parts. There is a license fee, a "customization fee" to prioritize scarce engineers, and for the first time a royalty on the final chip - The royalty model mirrors the Arm-Amazon partnership from a decade ago and fits 12-month design cycles. It also expands Synopsys's role to system-level bring-up - Customers can "hire" an AI agent engineer with a specific skillset, which fits existing budgets and team structures - GPT-Synopsys with OpenAI bundles a specialized LLM, the compute, and forward-deployed engineers - A CFET needs 200x more device equations than a planar FET, so physics-based simulators stay the ground truth This episode is presented by @CrusoeAI. Try Crusoe's managed inference for open models with $5 in free credits: Chapters: 0:00 Intro: The Amazon & OpenAI Deals 2:39 Application Optimized IP 6:04 The New Royalty Business Model 12:14 How Standard IP Differentiates 18:20 The Arm-Amazon Analogy 22:00 Synopsys's Role in Test Chips 26:06 The Three Stages of Chip Design 31:27 The 'Agent Engineer' AI Model 36:20 The GPT-Synopsys Partnership 39:27 In AI We Believe, In Physics We Trust Get more of Austin and Vik daily, free! Sign up: Connect with Vik and Austin: Vik's Paid Substack: Austin's Paid Substack: @austinsemis @vikramskr @Synopsys