InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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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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AI Agents & LLMs: Scaling the Next Wave of Automation
The panelists discuss AI agents and LLMs, exploring their definitions, architectures, use cases, reliability, and impact on the SDLC and future of automation.
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A Framework for Building Micro Metrics for LLM System Evaluation
Denys Linkov discusses critical lessons for senior developers and leaders on building robust LLM systems and actionable metrics that prevent production issues and drive business value.
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Beyond Durability: Database Resilience and Entropy Reduction with Write-Ahead Logging at Netflix
Prudhviraj Karumanchi and Vidhya Arvind share how Netflix built a Write-Ahead Log to guarantee data durability and reliability, tackling issues like data loss, corruption, and replication at scale.
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Supporting Diverse ML Systems at Netflix
David Berg and Romain Cledat discuss Metaflow, Netflix's ML infrastructure for diverse use cases from computer vision to recommendations.
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Rust: a Productive Language for Writing Database Applications
Carl Lerche discusses Rust's potential for higher-level applications & shares productivity tips.
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What to Pack for Your GenAI Adventure
Soledad Alborno discusses essential skills and new tools for building successful Generative AI products.
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Scaling Large Language Model Serving Infrastructure at Meta
Ye (Charlotte) Qi explains key considerations for optimizing LLM inference, including hardware, latency, and production scaling strategies.
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Ultra-Fast In-Memory Database Applications with Java
Markus Kett shares how to build the fastest database applications using Java & EclipseStore, bypassing traditional database limitations.
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