InfoQ Homepage Artificial Intelligence Content on InfoQ
-
AI Innovation in 2025 and beyond
Tejas Kumar discusses the evolution of AI from 1906 to 2026, explaining how agentic RAG and the Model Context Protocol (MCP) are shifting the industry from complex UIs to a prompt-driven future.
/presentations/ai-innovation-2025/en/mediumimage/tejas-kumar-medium-1771407414338.jpg)
-
DevOps Modernization: AI Agents, Intelligent Observability and Automation
The panelists explain how AI is redefining DevOps and SRE practices by moving teams beyond reactive monitoring toward predictive, automated delivery and operations.
/presentations/devops-modernization-ai-agents/en/mediumimage/infoq-live-medium-1771422477828.jpg)
-
Building Embedding Models for Large-Scale Real-World Applications
Sahil Dua explains the architecture and training of embedding models. He shares practical tips for distilling large models and scaling RAG applications for real-time production environments.
/presentations/llm-large-scale-applications/en/mediumimage/sahil-dua-medium-1769590214923.jpeg)
-
Foundation Models for Ranking: Challenges, Successes, and Lessons Learned
Moumita Bhattacharya explains how Netflix unifies search and recommendations using the "UniCoRn" model and leverages Transformer-based foundation models to personalize the experience for 300M+ users.
/presentations/foundation-models-ranking/en/mediumimage/moumita-bhattacharya-medium-1768986504738.jpg)
-
Ecologies and Economics of Language AI in Practice
Jade Abbott explains how to build sustainable AI using "Little LMs." She discusses environmental impacts, linguistic justice, and technical optimizations like quantization and model distillation.
/presentations/llm-ai-africa/en/mediumimage/jade-abbott-medium-1766064709735.jpeg)
-
DevOps Is for Product Engineers, Too
Lesley Cordero explains how DevOps and platform engineering drive sociotechnical excellence. She shares strategies for joint optimization, distributed leadership, and organizational sustainability.
/presentations/devops-product-engineers/en/mediumimage/lesley-cordero-medium-1766062025530.jpg)
-
Lessons Learned from Shipping AI-Powered Healthcare Products
Clara Matos shares lessons from shipping AI in healthcare at Sword Health. She discusses building guardrails, utilizing LLM-as-a-judge evals, and optimizing RAG to ensure safety and reliability.
/presentations/ai-healthcare-learnings/en/mediumimage/clara-medium-1765443423391.jpeg)
-
Powering Enterprise AI Applications with Data and Open Source Software
Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale.
/presentations/feast/en/mediumimage/francisco-javier-medium-1765446460483.jpg)
-
Securing AI Assistants: Strategies and Practices for Protecting Data
Andra Lezza reviews the OWASP Top 10 for LLMs and contrasts security controls for independent vs. integrated copilot architectures.
/presentations/securing-ai-assistants/en/mediumimage/andra-lezza-medium-1764846784380.jpg)
-
Humans in the Loop: Engineering Leadership in a Chaotic Industry
Michelle Brush discusses engineering leadership in the age of AI/ML and automation.
/presentations/ai-ml-jobs/en/mediumimage/michelle-brush-medium-1761904230413.jpg)
-
AI-Driven Software Delivery: Leveraging Lean, ChOP & LLMs to Create More Effective Learning Experiences at QCon
Wes Reisz details building a RAG-powered QCon certification in 4 weeks. He dives into the serverless pipeline, RAG architecture, lessons on using supervised coding agents, and Lean thinking.
/presentations/chop-rag-llm-qcon/en/mediumimage/wes-reisz-medium-1761903660830.jpg)
-
Achieving Precision in AI: Retrieving the Right Data Using AI Agents
Adi Polak discusses achieving precision in GenAI by moving beyond RAG to Agentic RAG. She details agent patterns, feedback loops, and using data streaming architectures to scale real-time AI.
/presentations/ai-precision-rag-agents/en/mediumimage/adi-polak-medium-1761732116601.jpg)