Oct 13, 2026

David Silver and Lasse Espeholt of Ineffable Intelligence: A Superlearner for the Age of Experience

David Silver, co-founder of Ineffable Intelligence, outlines his bold vision for building a "superlearner"—an AI that discovers science, mathematics, and language autonomously, free from human data or explicit guidance. Drawing parallels to AlphaGo Zero's success, Silver argues that human-language reasoning is a ceiling, not a foundation, for advanced AI. He details their approach using complex simulated "crucibles" and simple rewards, aiming to develop the "science of superintelligence" in simulation for safety and accelerated progress. With a powerful GPU cluster and a small, elite team, Silver forecasts strong evidence within a year and superintelligence within three.

Oct 12, 2026

Build a Research Agent with Claude Managed Agents (Part 2 of 4) — Anthropic

A hands-on walkthrough of Claude Managed Agents, building a research desk for SEC filing analysis with a chat UI on the session event stream, skills, subagents, custom tools, shared memory, rubric-graded outcomes and vault-based credential injection.

Oct 12, 2026

Claude Managed Agents Q&A: Evals, CI/CD and Multi-Tenancy (Part 4 of 4) — Anthropic

A Q&A from the final part of Anthropic's Claude Managed Agents workshop, covering CI/CD for agent configs in YAML with the ant CLI, eval practices, workspace-based resource sharing and tenant isolation, agent-driven code review, GPU-enabled self-hosted sandboxes, multiplayer Slack agents, long-running sessions, and the coordinator pattern for custom tools.

Oct 11, 2026

AI Apps in a Flash: Ship to GPUs Without Docker — Dean Quiñanola, Runpod

Dean Quiñanola, a staff engineer at Runpod, presents Runpod Flash, a way to run Python on cloud GPUs as if they were local, with no Dockerfiles, image builds, or registry pushes. The talk covers serverless and load-balanced endpoints, endpoint-to-endpoint calls, network volumes with warm caching, and live serverless iteration. A live demo moves from GPU detection to text and image generation and then deploys to production with a single command.

Oct 11, 2026

Building AI Agents with Real-Time Web Data — Yohan Raju, Bright Data

Yohan Raju of Bright Data shows how an AI agent can combine a live Amazon listing with Reddit sentiment to produce a purchase recommendation, arguing that agents need fresh, structured web data rather than relying only on pre-trained knowledge or pre-indexed retrieval.

Oct 11, 2026

RAG Needs a Map: Using GraphRAG to Retrieve Connected Context — Nyah Macklin, Neo4j

A hands-on GraphRAG workshop from Neo4j showing how combining vector search with a knowledge graph gives an agent connected context, multi-hop traversal, and explainable answers. It covers the difference between semantic similarity and relationships, LLM-driven entity and relationship extraction under a fixed schema, building an Aura database and Python pipeline, and configuring an Aura agent with similarity search and text-to-Cypher, with a closing check that shows why visible query evidence matters.