Jul 13, 2026

Stop Evaluating Models Like It's the 50s - Alejandro Vidal, Mindmakers

This talk introduces the transformative potential of Item Response Theory (IRT), a psychometric model, for evaluating AI models. It addresses the limitations of current evaluation methods by demonstrating how IRT can precisely measure model intelligence, audit and optimize benchmarks, detect data leakage, implement adaptive testing, identify item bias, and even fingerprint models based on their error patterns, opening new avenues for understanding and improving LLM capabilities.

Jul 12, 2026

The AI bugpocalypse is here. Now what? - Jack Cable, Corridor

Jack Cable discusses the "AI bug apocalypse" driven by advanced AI models finding and exploiting vulnerabilities and AI coding tools increasing attack surfaces. He champions a "secure by design" approach, advocating for systemic changes like using memory-safe languages to prevent common vulnerability classes rather than just patching. He also addresses AI's role in introducing new vulnerabilities, the shift towards autonomous AI in development, and policy recommendations for securing the future of AI-powered coding.

Jul 11, 2026

Claws Out: Securing and Building with OpenClaw - Nick Taylor, Pomerium

This talk details how the speaker contributed a "trusted-proxy auth mode" to the OpenClaw project to enhance security and user experience by eliminating the need for tokens and device pairing. It explains the technical implementation of this mode using Identity-Aware Proxies like Pomerium. The speaker also demonstrates a unique workflow, building and live-editing a Multi-Modal Chatbot Protocol (MCP) application directly within ChatGPT, controlled by their OpenClaw instance via Discord, showcasing the power of secure, natural language-driven web development.

Jul 11, 2026

Stop AI Agent Hallucinations: 5 Techniques + Production Patterns - Elizabeth Fuentes, AWS

Explore five research-backed techniques to overcome common AI agent architectural limitations like hallucination, inefficient tool use, and rule violations. Learn how to implement semantic tool selection, Graph-RAG, multi-agent validation, neurosymbolic guardrails, and agent steering through code changes, not prompt engineering, and deploy them using AWS Bedrock Agent Core for robust and cost-effective AI agents.

Jul 11, 2026

Why AI Agents Don't Actually Understand You — Danielle Perszyk, Amazon AGI Lab

Daniel from Amazon AGI Lab details a cognitive science-driven vision for human-aligned AI, focusing on collective intelligence, real-time interaction, and redefining reliability through user mind modeling. He emphasizes aligning AI representations with human cognition to foster generalization, prevent reduced human agency, and revolutionize areas like education, advocating for diverse AI systems and frontier research over immediate productization.

Jul 11, 2026

State of the Union: Why Local, Why Now — NVIDIA, Osmantic, Roboflow, EXO Labs, @matthew_berman

This panel discussion explores the inflection point of Local AI, driven by advanced models, improved hardware, and a robust ecosystem. Experts discuss how this shift addresses critical concerns around privacy, cost, sovereignty, and resilience, emphasizing the pivotal role of open-source AI and specialized models. They delve into technical optimizations, the evolution from generalized to specialized AI, and the challenges of making local AI accessible and performant for both enterprise and individual users.