InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Chatting with Your Knowledge Graph
Jonathan Lowe discusses how to enable an LLM to chat with a structured graph database. He explains the process of using semantic search and knowledge graphs to answer natural language questions.
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The Data Backbone of LLM Systems
Paul Iusztin discusses the evolution of AI engineering, highlighting the shift from model training to foundational models. He shares insights on scalable LLM systems and optimizing RAG.
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Achieving Sustainable Mental Peace at Work Using GenAI
John Gesimondo shares a framework for achieving sustainable mental peace at work using GenAI. He provides practical prompts and recipes for leveraging AI to overcome being stuck and enhance planning.
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GenAI at Scale: What it Enables, What it Costs, and How to Reduce the Pain
Mark Kurtz discusses scaling GenAI and optimizing LLM deployments. He shares how to overcome technical and financial challenges using open-source tools like vLLM, LLM Compressor, and InstructLab.
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Multidimensionality: Using Spatial Intelligence x Spatial Computing to Create New Worlds
Erin Pañgilinan explains how AI is revolutionizing XR development. She shares how this tech stack, which includes spatial intelligence and ambient computing, empowers engineers to build new realities.
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Slack's AI-Powered, Hybrid Approach for Large-Scale Migration from Enzyme to React Testing Library
Sergii Gorbachov discusses how Slack saved thousands of hours by using a hybrid AST/LLM approach to automate complex code migration, sharing a transferable model for other companies.
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AI for Food Image Generation in Production: How & Why
Iaroslav Amerkhanov discusses how his team at Delivery Hero leveraged GenAI to generate food images, detailing the architecture, optimization, and business impact.
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Orchestrating AI Services with the Spring AI Framework
Loiane Groner discusses Spring AI and how developers can build powerful, production-ready AI solutions in Java.
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Making AI Agents Work for You (and Your Team)
Hannah Foxwell explains how to design agent teams for high-quality output and shares a vision where AI agents handle toil, freeing humans to focus on creativity and customer relationships.
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10 Reasons Your Multi-Agent Workflows Fail and What You Can Do about It
Victor Dibia discusses multi-agent systems, detailing how to build them with AutoGen, common failure points, and strategic approaches for senior software developers and engineering leaders.
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From Autocomplete to Agents: AI Coding State of Play
Birgitta Böckeler explains how to use AI coding assistants effectively and responsibly, from fighting complacency to fostering a healthy team culture.
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Key Lessons from Shipping AI Products beyond the Hype
Phil Calçado shares key learnings from building and scaling an AI startup, offering a product-centric approach for engineering leaders and architects navigating generative AI.
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