Building the Android for Robots | Jan Liphardt, founder of OpenMind
Jan Liphardt is the founder of OpenMind, where they're building an operating system for intelligent machines. He is an associate professor at Stanford and was previously an associate professor at UC Berkeley. He got his PhD from University of Cambridge.Jan's favorite books: The Little Prince (Author: Antoine de Saint-Exupéry)00:01 — Introduction00:32 — Gap Between Movie Robots and Real-World Robotics02:35 — Vision for a New Robotics OS07:14 — Robotics OS Stack Breakdown11:01 — Biggest Technical Challenges in Robotics15:06 — Data Volume, Processing, and Cloud vs. Local19:09 — Shared Intelligence Layer: What is Fabric?23:15 — Filtering Good vs. Bad Ideas in a Robot Network26:06 — Business Model for Robots and Machine Economy29:55 — Standards and Interoperability in Robotics33:14 — Most Exciting AI Advancements Today35:00 — Rapid Fire Round --------Where to find Jan Liphardt: LinkedIn: https://www.linkedin.com/in/jan-liphardt/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 X: https://x.com/prateekvjoshi
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46:43
AI Infra for Long Context Model Training | Anna Patterson, founder of Ceramic AI
Anna Patterson is the cofounder of Ceramic, an AI infrastructure platform for large scale model training. They raised their seed round led by NEA along with amazing investors such as Lukas Biewald, Laszlo Bock, Sean Carey, Jeff Hammerbacher, Ankit Jain, Seval Oz, Joanna Rees, Gokul Rajaram, and Ram Sriram. She was previously the founder and managing partner at Gradient Ventures. She was the VP Engineering at Google for 14 years. Anna's favorite book: Books she reads with her daughters as part of their family book club(00:01) Introduction & AI Infra 101(01:11) Budget Breakdown: Training vs Inference(02:16) Mapping the AI Infra Landscape(04:18) Verticalized vs General-Purpose Infrastructure(06:22) Why Ceramic Was Built From Scratch(08:35) MVP Tradeoffs and Decision Framework(10:16) Achieving 2.5x Speedup in Long Context Training(11:50) Short vs Medium vs Long Context: A Primer(13:38) Long Context vs RAG (Retrieval-Augmented Generation)(15:24) Real-World Impact of Long Context Models(16:38) Bottlenecks at 96K Token Contexts(17:51) Data Pruning 101: What to Keep, What to Drop(21:01) What Is “Good Data” in Subjective Domains?(22:32) How to Grade Reasoning, Not Just Answers(24:15) Synthetic Data: Use Cases & Limits(26:19) Staying Current in Fast-Moving Domains(27:30) Will Every Company Have Its Own Model?(29:23) Unlocking the Next 10x in Infra(31:27) Favorite Recent AI Advancements(32:33) Rapid Fire Round--------Where to find Anna Patterson: LinkedIn: https://www.linkedin.com/in/anna-patterson-15921ba/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 X: https://x.com/prateekvjoshi
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39:31
Building an AI+Data Startup Studio | Tom Chavez, cofounder of super{set}
Tom Chavez is the cofounder of super{set}, a startup studio that founds, funds, and builds data and AI startups. Prior to this, he was the CEO and co-founder of Krux, a martech platform acquired by Salesforce in 2016. Before Krux, he was the CEO and co-founder of Rapt, a provider of software for media monetization acquired by Microsoft in 2008. He went to Harvard for undergrad and Stanford for his PhD.Tom's favorite book: The Three Musketeers (Author: Alexandre Dumas)(00:01) Origin Story and Starting Superset(02:58) How Superset Evaluates Ideas and Risk(06:24) What Is a Venture Studio and How Superset Works(10:49) Underfunded Layers in AI Infrastructure(14:55) Orchestration Opportunities in LLM Workflows(15:49) The Future of Data Infra and ETL in the AI Era(20:46) Code Infra: Code Quality and AI-Generated Software(24:55) Model Infra, MLOps, and Why It’s Underwhelming(27:22) Cloud Economics and Gross Margins in AI Companies(32:15) Early Team Structure in AI Infra Startups(34:49) Full Stack vs Composable Infra in AI(37:52) Fragmentation vs Consolidation in AI Tooling(41:02) Where Moats Will Accumulate: Data In, AI, Data Out(45:10) Biggest Challenge in Building Superset(46:23) Rapid Fire Round--------Where to find Tom Chavez: LinkedIn: https://www.linkedin.com/in/tommychavez/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 X: https://x.com/prateekvjoshi
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52:57
Decentralized Data Foundry for AI | Rowan Stone, CEO of Sapien
Rowan Stone is the CEO of Sapien, a decentralized data foundry where AI models can access verified human expertise worldwide. They've raised raised a $10.5M round led by Variant. He's also the co-creator of Coinbase's layer 2 network called Base.Rowan's favorite book: Outlive (Author: Peter Attia)(00:01) Introduction(01:09) The Flaws in Centralized Data Models(04:10) Mechanism of Knowledge Transfer and Expert Incentives(07:08) Supply, Demand, and Market Dynamics for Training Data(10:22) Chain of Thought Reasoning and 3D/4D Data Use Cases(12:22) Building the MVP: What Worked and What Didn’t(15:17) Acquiring the First Five Customers(17:59) What They Got Right and What They’d Change(20:15) How to Scale from Early Customers: Advice to Founders(22:02) Data Infrastructure Opportunities in 2025(25:57) Designing AI-Native Databases(28:04) Biggest Startup Challenge: Messaging and Clarity(30:22) Future of Data Collection Mechanisms (2 to 5 Years Out)(32:07) Autonomous Vehicles and Demand for 4D Data(35:33) Emerging AI Use Cases: Memory, Wearables, and Robotics(36:19) Rapid Fire Round--------Where to find Rowan Stone: LinkedIn: https://www.linkedin.com/in/rowan-stone/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 X: https://x.com/prateekvjoshi
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38:22
Converting Cameras into Autonomous AI Agents | Rish Gupta, CEO of Spot AI
Rish Gupta is the cofounder and CEO of Spot AI, a video AI platform for the physical world. They've raised $93M from amazing investors such as Scale, Bessemer, and Qualcomm Ventures.Rish's favorite book: Atlas Shrugged (Author: Ayn Rand)(00:01) Introduction(00:32) Video-AI basics: ingesting camera feeds across diverse networks (02:42) Edge-vs-cloud trade-offs for compute, storage, and bandwidth (05:40) Mapping the sector: hardware waves to cloud cameras to pure-software layer (07:43) Founding insight: why Spot AI attacked the video layer now (11:35) Bare-bones MVP: two-page dashboard that unified camera access (15:34) First-10-customer lessons & pruning the ideal customer profile (ICP) (18:54) Go-to-market experiments: ICP variants, pain points, and channels (23:00) Early-team blueprint: engineering-heavy, founders run sales (24:03) Hardware stance: free IP cameras to simplify one-vendor buying (26:01) Biggest tech hurdle: supporting thousands of camera brands & configs (27:00) Sales challenge: outbound fatigue forces novel GTM motions (28:55) Future vision: each camera becomes an autonomous AI agent with a "job" (30:25) Key AI unlock: massive context windows enabling flow-state reasoning (32:14) Rapid-fire round--------Where to find Rish Gupta: LinkedIn: https://www.linkedin.com/in/profilerish/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-91047b19 X: https://x.com/prateekvjoshi
The best place to find out how AI builders build. The host Prateek Joshi interviews world-class AI founders and VCs on this podcast. You can visit prateekj.com to learn more about the host.
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