Why Physical AI Needed a Completely New Data Stack

More from Gradient Dissent: Conversations on AI All episodes →

1. 

   S1 · E138 · 15 Apr 2026 · 46 min

   Uber, Nissan, and Mercedes Chose This Self-Driving Startup | Alex Kendall, Wayve

   "Every vehicle is capable of driverless operation. That's clearly the steady state of where we're going." Wayve started in a rented house in Cambridge with $1.5M, a car in the garage, and an aim to integrate end-to-end AI into driving. A decade later it's driven across 506 cities without a single HD map and is worth over $8.6 billion. In this episode, CEO Alex Kendall joins Lukas Biewald to talk about how he built the AI driver Uber, Nvidia, Mercedes, and Nissan all backed, and why putting self-driving AI into 100 million cars a year is a far bigger bet than 10,000 robotaxis. Waymo and Tesla…

2. 

   S1 · E137 · 31 Mar 2026 · 44 min

   Why Netflix, Uber, and Spotify Never Lag: The Database Nobody Talks About | Aaron Katz

   "Companies designing for agents, not humans, are going to get a lot of lift." ClickHouse started as an internal tool at Yandex. Today it's the database Anthropic, OpenAI, Meta and Tesla all run on. In this episode, CEO Aaron Katz joins Lukas Biewald to talk about how he turned an open source project into a $15B company, why he acquired LangFuse knowing it could cost him customers, and what he's actually building for the agent era. Snowflake, Datadog and Databricks all come up. He doesn't shy away. Connect with us here: Aaron Katz: https://www.linkedin.com/in/aaron-katz-5762094 ClickHouse:…

3. 

   S1 · E136 · 5 Feb 2026 · 51 min

   The $64M Bet on an AI That Has to Be Right | Carina Hong, CEO of Axiom

   Formal verification already consumes years of human effort. In this episode, Lukas Biewald talks with Carina Hong, Founder & CEO of Axiom, about why verification is becoming the real bottleneck in high stakes AI systems. They discuss how Axiom uses AI to take on the tedious checking that stretches verification cycles across years, starting with formal mathematics and extending to hardware and software. Carina also explains why Axiom’s approach to auto-formalization mirrors spec driven models like Kiro from AWS. Connect with us here: Carina Hong: https://www.linkedin.com/in/carina-hong/…

4. 

   S1 · E135 · 20 Jan 2026 · 1 hr 8 min

   What a $42B Software Co. Really Spends on AI Tools

   “I don't worry about being replaced by AI. I worry about being replaced by someone who's really good at using AI.” Atlassian has 10,000+ engineers currently split-testing the world’s top AI coding tools, from GitHub Copilot and Cursor to Claude Code. In this episode, Co-Founder & CEO Mike Cannon-Brookes joins Lukas Biewald to share what their data reveals about the world's best AI tools today. Hear how 24 years of building a tech giant and a massive internal study on AI productivity have shaped Mike's vision for the future of dev jobs. Connect with us here: Mike Cannon-Brookes:…

5. 

   S1 · E134 · 6 Jan 2026 · 53 min

   Inside the $41B AI Cloud Challenging Big Tech | CoreWeave SVP

   The future of AI training is shaped by one constraint: keeping GPUs fed. In this episode, Lukas Biewald talks with CoreWeave SVP Corey Sanders about why general-purpose clouds start to break down under large-scale AI workloads. According to Corey, the industry is shifting toward a "Neo Cloud" model to handle the unique demands of modern models. They dive into the hardware and software stack required to maximize GPU utilization and achieve high goodput. Corey’s conclusion is clear: AI demands specialization. Connect with us here: Corey Sanders:…

6. 

   S1 · E132 · 1 Dec 2025 · 15 min

   The Engineering Behind the World’s Most Advanced Video AI

   Is video AI a viable path toward AGI? Runway ML founder Cristóbal Valenzuela joins Lukas Biewald just after Gen 4.5 reached the #1 position on the Video Arena Leaderboard, according to community voting on Artificial Analysis . Lukas examines how a focused research team at Runway outpaced much larger organizations like Google and Meta in one of the most compute-intensive areas of machine learning. Cristóbal breaks down the architecture behind Gen 4.5 and explains the role of “taste” in model development. He details the engineering improvements in motion and camera control that solve…

7. 

   S1 · E131 · 18 Nov 2025 · 59 min

   The CEO Behind the Fastest-Growing AI Inference Company | Tuhin Srivastava

   In this episode of Gradient Dissent, Lukas Biewald talks with Tuhin Srivastava, CEO and founder of Baseten, one of the fastest-growing companies in the AI inference ecosystem. Tuhin shares the real story behind Baseten’s rise and how the market finally aligned with the infrastructure they’d spent years building. They get into the core challenges of modern inference, including why dedicated deployments matter, how runtime and infrastructure bottlenecks stack up, and what makes serving large models fundamentally different from smaller ones. Tuhin also explains how vLLM, TensorRT-LLM, and…

8. 

   S1 · E130 · 16 Sep 2025 · 56 min

   The Startup Powering The Data Behind AGI

   In this episode of Gradient Dissent, Lukas Biewald talks with the CEO & founder of Surge AI, the billion-dollar company quietly powering the next generation of frontier LLMs. They discuss Surge's origin story, why traditional data labeling is broken, and how their research-focused approach is reshaping how models are trained. You’ll hear why inter-annotator agreement fails in high-complexity tasks like poetry and math, why synthetic data is often overrated, and how Surge builds rich RL environments to stress-test agentic reasoning. They also go deep on what kinds of data will be critical to…

9. 

   S1 · E129 · 5 Aug 2025 · 44 min

   Arvind Jain on Building Glean and the Future of Enterprise AI

   In this episode of Gradient Dissent, Lukas Biewald sits down with Arvind Jain, CEO and founder of Glean. They discuss Glean's evolution from solving enterprise search to building agentic AI tools that understand internal knowledge and workflows. Arvind shares how his early use of transformer models in 2019 laid the foundation for Glean’s success, well before the term "generative AI" was mainstream. They explore the technical and organizational challenges behind enterprise LLMs—including security, hallucination suppression—and when it makes sense to fine-tune models. Arvind also reflects on…

10. 

    S1 · E128 · 8 Jul 2025 · 43 min

    How DeepL Built a Translation Powerhouse with AI with CEO Jarek Kutylowski

    In this episode of Gradient Dissent, Lukas Biewald talks with Jarek Kutylowski, CEO and founder of DeepL, an AI-powered translation company. Jarek shares DeepL’s journey from launching neural machine translation in 2017 to building custom data centers and how small teams can not only take on big players like Google Translate but win. They dive into what makes translation so difficult for AI, why high-quality translations still require human context, and how DeepL tailors models for enterprise use cases. They also discuss the evolution of speech translation, compute infrastructure, training…