Training Data

Jason Kelly, founder and CEO of Ginkgo Bioworks, who builds automated biological foundries to make biology programmable. He explains how robotic, AI-driven labs run experiments at scale and a collaboration where a reasoning model plus robotics outperformed prior biochemistry results. He describes why automating lab work, cloud labs, and shared data will accelerate discovery and reshape biotech infrastructure.

Philip Johnston, founder and CEO of StarCloud, builds space-based data centers and led the first StarCloud satellite. He explains why falling launch costs make orbital compute cheaper, how radiative cooling and solar power work in vacuum, and the thermal and networking designs that scale to gigawatts. He also previews latency tradeoffs, security and regulatory angles, and the larger economic shift toward space-based compute.

Jason Hoch, cofounder of Nominal, builds test and validation tooling for complex hardware. Cameron McCord, cofounder of Nominal, designs data and AI platforms for hardware engineering. They discuss bringing software practices to hardware testing. They cover the simulation versus real-world testing gap, using AI to automate repetitive test work, and how telemetry and validation infrastructure enable physical AI.

Johannes Hagemann, researcher and co-founder building environment design and RL tooling. Will Brown, AI researcher and co-founder focused on large-scale training infra and post-training workflows. They discuss Environments Hub, environments as evals and product surfaces, harnesses and agent interaction, democratizing frontier training, cybersecurity sims, recursive language models, synthetic data, and companies becoming AI research labs.

Jamie Cuffe, founder and CEO of Pace who builds AI agents to automate insurance BPO workflows. He explains why insurance is ripe for agentic process outsourcing. He describes practical agent design, onboarding with forward‑deployed engineers, and how Pace achieves 50–75% cost savings. He discusses selecting high‑impact workflows, building trust with top carriers, and a vision to aggregate vertical AI services.

Zach Lloyd, CEO and founder of Warp, reimagines the developer terminal into an agentic workbench for professional developers. He talks about why the terminal is ideal for orchestrating cloud agents, how IDEs and terminals are converging around prompting, and how Warp competes and prices in a market with subsidized model providers. He also explores agent run-times, harness engineering, and the limits of current models.

Harrison Chase, cofounder of LangChain and a pioneer in AI agent frameworks, dives into the world of long-horizon agents capable of autonomous operation. He explains how context engineering has become vital for agent development, emphasizing improvements in harnesses over mere model upgrades. Harrison shares fascinating applications of coding agents and highlights the importance of traces as new sources of truth. He also contrasts building agents with traditional software, revealing insights into memory and self-improvement mechanisms that set them apart.

Azalia Mirhoseini and Anna Goldie, co-founders of Recursive Intelligence, revolutionized chip design at Google with AlphaChip, drastically speeding up the process. They discuss how chip design bottlenecks hinder AI's progress and their vision for 'designless' custom silicon, making it accessible for all companies. The duo shares insights into using AI for advanced placements, novel chip shapes, and recursive self-improvement, where AI enhances its own designs. Their optimism for AGI and a 'Cambrian explosion' of custom silicon applications paints an exciting future for technology.

Karol Hausman and Tobi Springenberg from Physical Intelligence discuss the groundbreaking potential of robotic foundation models. They argue that the intelligence bottleneck, not hardware, limits robotics and explain their mission to create models capable of performing diverse tasks. The duo dives into their end-to-end learning approach, emphasizing recent improvements in reinforcement learning and real-world deployment. Insights into unexpected applications from open-sourced models and the aspiration for continual robot learning highlight a pivotal shift in intelligent machine design.

Sanjit Biswas, Co-founder and CEO of Samsara, shares his unique insights on scaling AI in the physical world. He explains the key differences between physical AI and cloud-based systems, especially how real-world data like weather influences outcomes. Sanjit also reveals how Samsara leverages extensive driving data to enhance safety and efficiency, while highlighting the role of AI in coaching frontline workers. He discusses the future of autonomy in various industries, emphasizing edge computing's advantages in operational control.