InfoQ - AI, ML & Data Engineering - Presentations

Presentation: Postgres for Production Agents: Your Relational Foundation for Enterprise AI

Gwen Shapira — Wed, 15 Jul 2026 12:57:00 GMT

Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector indexing - to deliver deterministic and semantic context to LLMs. She also discusses vector quantization to speed up queries by 4x and strategies for managing agentic memory.

By Gwen Shapira

Presentation: Chaos Engineering GPU Clusters

Bryan Oliver — Fri, 10 Jul 2026 13:42:00 GMT

Bryan Oliver discusses the frontier of AI infrastructure: chaos engineering for large-scale GPU clusters. He shares how engineering leaders can handle complex topologies, network protocols like RDMA, and NUMA misalignments. Discover seven practical fault-injection strategies to maximize multi-million dollar hardware efficiency and build robust observability loops.

By Bryan Oliver

Presentation: Accelerating Netflix Data: a Cross-Team Journey from Offline to Online

Rajasekhar Ummadisetty, Ken Kurzweil — Thu, 09 Jul 2026 15:20:00 GMT

Raj Ummadisetty and Ken Kurzweil share Netflix's architectural pivot to CloudStream, a repeatable capture, conversion, and deployment framework. They discuss shifting key-value abstractions from stateless to stateful to move terabytes of bulk data safely. Software architects will learn to exploit data access patterns, use "Pathfinder" prototypes, and maintain a 99% faster rollout.

By Rajasekhar Ummadisetty, Ken Kurzweil

Presentation: The Multi-Agent Approach: Building Reliable and Controllable Software Development Automation

Itamar Friedman — Wed, 08 Jul 2026 14:06:00 GMT

Itamar Friedman discusses how architects and engineering leaders can break through the AI productivity ceiling using adaptive multi-agent systems. He shares insights on moving past simple autocomplete to resilient workflows by integrating autonomous testing, intelligent code review, and robust arbitration. Learn how to govern agent communication and build a context-driven SDLC that scales.

By Itamar Friedman

Presentation: Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery

Aaron Erickson — Tue, 07 Jul 2026 08:03:00 GMT

Aaron Erickson explains how NVIDIA designs and tests purpose-built AI agent hierarchies. For senior developers and architects, he outlines why balancing deterministic tools with agentic discovery is crucial. Discover how to leverage rare context, implement LLM-as-a-judge test pyramids, and avoid the paradox of choice to build highly reliable, production-grade AI systems at scale.

By Aaron Erickson