InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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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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The Form of AI
Savannah Kunovsky, who leads IDEO's Emerging Tech Lab, explains how combining engineering rigor with design thinking creates impactful, user-centered AI products.
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Maximizing Deep Learning Performance on CPUs using Modern Architectures
Bibek Bhattarai demystifies Intel AMX, explaining how this CPU architecture accelerates deep learning workloads via low-precision matrix multiplication and efficient data handling.
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Stream and Batch Processing Convergence in Apache Flink
Jiangjie Qin discusses stream and batch processing convergence in Apache Flink, explaining how Flink unifies computing and execution models for enhanced efficiency & reduced data infrastructure costs.
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Enhance LLMs’ Explainability and Trustworthiness with Knowledge Graphs
Leann Chen discusses how knowledge graphs provide structured data to enhance LLM accuracy, tackling common challenges like hallucinations and the "lost-in-the-middle" phenomenon in RAG systems.
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