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Ion Stoica - The Limits of AI Coding Agents: Two Fundamental Gaps in Agentic Software Engineering
Keynote: Reliability in AI (Agentic) Systems - Ion Stoica, Databricks and Anyscale, OPAQUE
Ray Train on Anyscale: Observability and Reliability at Scale | Anyscale | Ray Summit 2026
Ion Stoica on Agentic Systems and AI Reliability | Ray on the Road – NYC 2025
Leveraging Agent Skills for Ray Workloads | Anyscale | Ray Summit 2026
From Agents to Action: Scaling Agentic AI with Ray on Intel Xeon | Intel | Ray Summit 2026
What Makes RL the Hardest Workload in AI | Robert Nishihara (Anyscale) | Ray Summit 2026
Production-Ready Distributed Inference with Ray Serve | Anyscale | Ray Summit 2026
Ray Summit 2022 - Day 1 Keynote - Ion Stoica
Agents and Robots: The Human Effort Putting AI Into Production | Encord | Ray Summit 2026
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Last Updated: October 3, 2026
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Summary
Join us at the premier vendor-neutral open source conference, where developers and technologists come together to collaborate, ... Modern models can span thousands of GPUs and months of training. At this scale, failures become the norm, costing GPU hours ... Reinforcement learning is one of the hardest distributed systems problems in "Github repository: github.com/ Whether it's an agent or a robot, production
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