InfoQ - Privacy - Presentations https://www.infoq.com InfoQ Privacy Presentations feed Presentation: Running AI at the Edge: Running Real Workloads Directly in the Browser https://www.infoq.com/presentations/local-ai-browser-inference-privacy/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Privacy-presentations <img src="https://res.infoq.com/presentations/local-ai-browser-inference-privacy/en/mediumimage/james-hall-medium-1787813225372.jpeg"/><p>James Hall discusses the strategic and technical imperative of moving AI workloads from cloud providers to local edge devices. He shares practical approaches using WebGPU, Transformers.js, and DuckDB to achieve near-native performance in JavaScript. Through real-world case studies, he explains how to minimize data privacy risks, optimize browser inference, and build rigorous evaluation suites.</p> <i>By James Hall</i> QCon London 2026 Privacy Web Browser Edge Computing GPU AI Security Cloud Computing Web Development Transcripts Local Inference Machine Learning Development Architecture & Design AI, ML & Data Engineering presentation Mon, 31 Aug 2026 11:00:00 GMT https://www.infoq.com/presentations/local-ai-browser-inference-privacy/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Privacy-presentations James Hall 2026-08-31T11:00:00Z /presentations/local-ai-browser-inference-privacy/en