Apr 16, 2026

Episode 16: Building AI for Life Sciences

OpenAI research lead Joy Jiao and product lead Yunyun Wang detail the development of specialized AI models for the life sciences. They discuss the new biochemistry-focused model series designed to accelerate research in genomics and protein understanding, the critical challenge of managing biosecurity risks through a "differentiated access" model, and the future vision of AI-powered autonomous labs that could revolutionize drug discovery and personalized medicine.

Apr 15, 2026

From Renting Machines by the Hour to Renting Capabilities by the MSeconds • Dhaval Nagar • GOTO 2025

Dhaval Nagar chronicles the evolution of cloud economics from hourly-billed virtual machines a decade ago to the current 'capability economy.' The talk is structured in three acts, detailing the journey from the initial launch of AWS Lambda, through the maturation of the serverless ecosystem with frameworks and new platforms, to the present day where complex capabilities like AI models are consumed as millisecond-metered APIs. This shift demands a new developer mindset focused on composing services, event-driven architecture, and eliminating infrastructure management.

Apr 10, 2026

Judge the Judge: Building LLM Evaluators That Actually Work with GEPA — Mahmoud Mabrouk, Agenta AI

This workshop by Mahmoud Mabrouk, CEO of Agenta AI, delves into building calibrated LLM-as-a-judge evaluations that reliably align with human judgment. It highlights how miscalibrated judges lead to false confidence and presents a practical workflow, including designing use-case specific metrics, detailed data annotation, and optimizing judge prompts using the GAPA algorithm. The talk emphasizes the importance of iterative debugging, model selection, and custom reflection templates for achieving trustworthy and effective LLM evaluations.

Apr 08, 2026

From Neural Networks to Digital Brains: The Next Leap in AI • Daniel Lütgehetmann • GOTO 2025

Daniel Lütgehetmann of inait introduces "digital brains," biologically accurate computational models of real brains, as a solution to current AI's limitations in physical world interaction. Unlike traditional AI that struggles with dynamic environments and skill accumulation, these digital brains leverage biologically inspired learning rules to achieve dramatically faster learning in robotics and complex systems, demonstrating potential for real-world adaptability and efficiency.

Apr 08, 2026

Platforms for Humans and Machines: Engineering for the Age of Agents — Juan Herreros Elorza

This talk by Juan Herreros Elorza explores how to design internal developer platforms for a future where AI coding agents are first-class users. It argues that the same best practices that make platforms accessible to humans—self-service interfaces, well-defined APIs, local-first workflows, and rich observability—are now critical prerequisites for agents to autonomously build, debug, and ship software. The session provides concrete principles for platform design, discusses how to manage AI-assisted contributions, and emphasizes the need to measure the impact of these changes on developer productivity and system reliability.

Apr 08, 2026

Agentic Engineering & PINNs: AI for Simulation Engineers - James Shaw | Podcast #172

James Shaw, a mechanical engineer and Ansys channel partner, delves into the current and future impact of agentic AI and physics-informed neural networks (PINs) on simulation workflows. He explores how AI is revolutionizing aspects from tech support and model setup to the solver itself, particularly in CFD. The discussion also covers the implications for the engineering job market, the 'senior-junior inversion crisis', and the continued irreplaceability of skilled engineers due to the inherent physicality of the world, emphasizing the need for robust, trustworthy data to train AI.