Jul 20, 2026

In the Land of AI Agents, the Verifiers Are King — Tariq Shaukat, Sonar

This talk addresses the critical challenge of verification in AI agent development, moving beyond generation to ensure correctness. It highlights the problem of "AI slop" and the "productivity paradox" of AI coding agents, where initial velocity gains are offset by increased technical debt and quality issues. The speaker introduces the AC/DC (Agent-Centric Development Cycle) framework comprising three stages: Guide (providing context and constraints), Verify (zero-trust, multi-layered verification using both algorithmic and agentic methods), and Solve (active code maintenance to control technical debt). This systems-level approach, integrating verification across agentic, CI, and code maintenance loops, significantly reduces issues and transforms AI into a reliable enterprise asset.

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.

Dec 07, 2025

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to be the fundamental language for AI. It unifies the two major paradigms: the learning capabilities of deep learning (neural networks) and the transparent, verifiable reasoning of symbolic AI (logic programming), aiming to solve critical issues like hallucination and the opacity of current models.

Dec 07, 2025

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to be the fundamental language for AI. It unifies the two major paradigms: the data-driven learning of deep learning and the verifiable reasoning of symbolic AI. By treating logical rules and tensor operations as the same underlying construct, Tensor Logic enables systems that can learn logical structures and perform transparent, deductive reasoning, directly addressing critical issues like model opacity and hallucination.

Dec 07, 2025

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to unify the two major paradigms of AI—deep learning's ability to learn from data and symbolic AI's power of logical reasoning—into a single, elegant framework.

Nov 20, 2025

Inside the AI Black Box

Emmanuel Ameisen of Anthropic's interpretability team explains the inner workings of LLMs, drawing analogies to biology. He covers surprising findings on how models plan, represent concepts across languages, and the mechanistic causes of hallucinations, offering practical advice for developers on evaluation and post-training strategies.