Jul 19, 2026

From Tokens to Cells: Foundation Models for Single-Cell Biology - Akram Baharlouei, Altos Labs

Akram Baharlouei from Altos Labs discusses the engineering hurdles in developing foundation models for single-cell biology. The talk covers the importance of single-cell analysis for cellular rejuvenation and drug discovery, the complexities and challenges of single-cell data (particularly RNA-seq), and a comparative analysis of current foundation model approaches, highlighting the limitations of transformer-based models and the potential of flow matching techniques like PrimeFlow.

Jul 19, 2026

From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud

May Walter, CTO of Hud, details a real-world case study on integrating AI agents into the SDLC for continuous performance optimization. The talk covers Hud's runtime intelligence layer, which uses production context to identify and fix high-ROI performance issues like N+1 queries and missing database indexes. It highlights the technical approach, challenges, and the development of a human-friendly reporting system that delivers measurable P90 latency improvements, enabling proactive optimization in mature codebases.

Jul 18, 2026

A Practitioner's Guide to Graphs - Tim Ainge, Good Collective

A speed-run through the fundamentals of graphs for AI engineers, covering how to build effective graphs from unstructured text using schema-first approaches and entity resolution, and then exploring powerful graph-native algorithms like Personalized PageRank, Shortest Path, and Subgraph Matching, all illustrated with real-world applications to create smarter, cheaper, and more reliable AI solutions.

Jul 18, 2026

Agents Need Receipts, Not More Tool Calls - Armanas Povilionis, Alithea Bio

Armanas Povilionis introduces Froglet, an open-source protocol addressing the critical need for verifiable agent-to-agent collaboration in AI workflows, especially in scientific research. Froglet enables agents to discover, transact with, and receive tamper-proof receipts for services across organizational boundaries, transforming them into 'executive chefs' managing distributed supply chains rather than isolated 'cooks' with more tools. The protocol streamlines interactions into a signed flow (Descriptor -> Offer -> Quote -> Deal -> Receipt) and integrates with diverse agent harnesses and execution environments, abstracting complex operations for LLM-driven agents.

Jul 17, 2026

Research to Reality with Google DeepMind — Benoit Schillings, Google DeepMind, VP of Technology

Benoit Schillings, VP of Technology at Google DeepMind, explores the evolution of AI's role in software development, highlighting the transition from human-limited coding to an AI frontier where syntax generation is solved. He delves into the power of self-play for model training, the shifting economics of software engineering, and the imperative for active guardrails. Schillings also discusses the need for inductive architecture, advanced model planning, multimodal reasoning (as seen in Gemini), and the potential for AI to drive scientific breakthroughs in fields like chemistry and biology by uncovering patterns imperceptible to human bias.

Jul 17, 2026

AI Can't Learn The Way Humans Do - This Could Fix That

This discussion explores world models as a promising path to solving sample efficiency in AI and achieving AGI. It contrasts deterministic control (Newtonian physics) with stochastic environments (RL), explaining the challenges posed by large action spaces in Go, self-driving, and robotics. The episode delves into how synthetic data, video diffusion models, and latent space architectures like JEPA are making world models practical, while also highlighting remaining open problems in physics modeling, real-time adaptation, and rich sensory integration.