May 08, 2026

How Transformers Finally Ate Vision – Isaac Robinson, Roboflow

Isaac Robinson from Roboflow explains why Vision Transformers (ViTs), despite their initial disadvantages in computational complexity and lack of inductive bias, ultimately surpassed Convolutional Neural Networks (CNNs) for computer vision tasks. The talk covers the critical roles of massive, ViT-specific pre-training methods like MAE and DINO, the architectural evolution through models like Swin, ConvNeXt, and Hiera, and optimizations borrowed from the LLM ecosystem. It culminates in a discussion on the practical deployment challenges of large foundation models like SAM and how Neural Architecture Search can bridge the gap.

May 07, 2026

Inside China's AI Labs with Interconnects & SAIL Media

Firsthand reflections from a visit to China’s most prominent AI labs, exploring the human side of the Chinese AI ecosystem, the technical constraints they face from chip supply, and how their research culture compares to the Bay Area.

May 07, 2026

Playground in Prod - Optimising Agents in Production Environments — Samuel Colvin, Pydantic

Samuel Colvin, creator of Pydantic, demonstrates a hands-on workflow for continuously optimizing AI agents in production. The session covers using Logfire for running evaluations, GEPA (Genetic Pareto) for autonomously evolving better prompts, and managed variables to deploy these improvements to live services without redeployment.

May 07, 2026

Language-Agnostic Detection of Bugs in Zero-Knowledge Proof Programs

A summary of a talk on a new language-agnostic approach using abstract interpretation to find critical vulnerabilities in Zero-Knowledge Proof (ZKP) programs by modeling and detecting mismatches between prover computations and verifier constraints.

May 07, 2026

Everything You Need To Know About Agent Observability — Danny Gollapalli and Ben Hylak, Raindrop

Agent failures are unlike traditional software failures. This workshop provides a practical framework for monitoring production agents, moving beyond evals to real-world observability by using explicit signals (errors, latency) and implicit signals (user frustration, refusals, self-diagnostics) to catch regressions and understand agent behavior.

May 07, 2026

Beyond the Basics: Production Serverless Patterns for Extreme Scale • Janak Agarwal • GOTO 2025

This presentation by Janak Agarwal from AWS provides a deep dive into scaling serverless applications for mission-critical, high-traffic workloads. It explores AWS Lambda's rapid scaling capabilities for handling extreme traffic bursts and introduces advanced patterns like Provisioned Concurrency for cost optimization during steady-state operations.