Training Data
podcast@sequoiacap.com
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Booking Overview
Metrics
Episodes: 100
Frequency: Irregular
Rating: 4.3/5.0
Estimated listeners: 1k-10k
Gender skew: Male
Location: USA
Contact Information
podcast@sequoiacap.com
For verified host and producer emails, sign up to view.
Host
Sonya Huang - Hosts conversations with leading AI builders and researchers on evolving AI technologies and their implications for technology, business, and society (Sequoia Capital).
Pat Grady - Hosts conversations with leading AI builders and researchers to ask critical questions about AI and its implications for technology, business, and society (Sequoia Capital).
Konstantine Buhler - Hosts episodes featuring major AI industry leaders, asking questions about the shift in computing and AI’s implications for technology, business, and society (Sequoia Capital).
Booking Intelligence
Booking Requirements
Recent Guest Discussions
Joon Sung Park - Simulating Human Society With Generative Agents; Model Architectures For Representing Values And Preferences; Applications Like Concept Testing And Forecasting; Long-term Societal Modeling Potential
Logan Kilpatrick - Agent Harnesses; Models Absorbing Scaffolding; Google’s Bets Across Products; Omni As A Single Model Strategy; Implications For Outcomes And Timeline Toward High-capability Systems
Jensen Huang - Shift From Retrieval To Generation; AI Hardware/“ai Factories”; Investment Stack (energy, Chips, Infrastructure, Models, Applications); Workforce Impact Framing And Competitive Advantage
Recent Topics
Episodes
Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
June 30, 2026
Dylan Patel, founder of SemiAnalysis, argues the biggest gains in AI don't come from faster chips, they come from software-hardware co-design. Optimizing the model, the kernels, and the silicon together turns a 2x here and a 2x there into 100x. He explains why DeepSeek's experts were shaped for Nvidia's Hopper (and why TPUs struggle to run it), why OpenAI's sparser models and Anthropic's denser ones pull them toward different hardware, and why the so-called CUDA moat was never really about CU...
Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin
June 24, 2026
Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and continual learning, which they call two sides of the same coin. Their contrarian premise: instead of stuffing ever-larger prompts into the context window or bolting on RAG, bake a team's knowledge directly into the model's weights, so it knows your company the way an employee of several years does. The payoff: matching or beating frontier models while consuming up to 100x fewer tokens. Working with pa...
Simulating Humans at Scale: Simile's Joon Sung Park
June 16, 2026
The race to build superintelligence is producing models that keep getting better at objective problems, but not at behaving like actual people. Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agents study, argues that simulating human society requires a fundamentally different kind of model. He frames today's frontier models as the "CPU of intelligence"—rational, superhuman at problems with right answers—and Simile as creating the "GPU of intelligen...
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