InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Navigating LLM Deployment: Tips, Tricks, and Techniques
Meryem Arik shares best practices for self-hosting LLMs in corporate environments, highlighting the importance of cost efficiency and performance optimization.
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AI in the Age of Climate Change
Nischal HP shares insights on building a data-driven economy to incentivize sustainable farming and reduce carbon emissions.
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How GitHub Copilot Serves 400 Million Completion Requests a Day
David Cheney explains the architecture powering GitHub Copilot, detailing how they achieve sub-200ms response times for millions of daily requests.
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The Harsh Reality of Building a Real-Time ML Feature Platform
Ivan Burmistrov shares how ShareChat built their own Real-Time Feature Platform serving more than 1 billion features per second, and how they managed to make it cost efficient.
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Recommender and Search Ranking Systems in Large Scale Real World Applications
Moumita Bhattacharya overviews the industry search and recommendations systems, goes into modeling choices, data requirements and infrastructural requirements, while highlighting challenges.
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Powering User Experiences with Streaming Dataflow
Alana Marzoev discusses the fundamentals of streaming dataflow and the architecture of ReadySet, a streaming dataflow system designed specifically for operational workloads.
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Pioneering the Future: Advancing Infrastructure for AI Agents
AI agents, powered by RAG and vector databases, will anticipate needs, automate workflows, and supervise agents. This talk explores infrastructure, security, and impact to help enterprises harness AI.
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Elevate Developer Experience with Generative AI Capabilities on AWS
Olalekan Elesin discusses how generative AI tools can improve productivity, streamline workflows, and foster a more efficient and effective development environment.
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Prompt Engineering: Is it a New Programming Language?
Hien Luu debates if prompt engineering is a programming language, arguing the case for both sides and exploring how this may impact learning and skill acquisition for software developers.
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Flawed ML Security: Mitigating Security Vulnerabilities in Data & Machine Learning Infrastructure with MLSecOps
Adrian Gonzalez-Martin introduces the motivations and the importance of security in data & ML infrastructure through a set of practical examples showcasing "Flawed Machine Learning Security".
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Leveraging Open-source LLMs for Production
Andrey Cheptsov discusses the practical use of open-source LLMs for real-world applications, weighing their pros and cons, highlighting advantages like privacy and cost-efficiency.
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Modernizing DevOps with AI, Boosting Productivity, and Redefining Developer Experience
The panelists discuss how generative AI is boosting productivity, redefining the developer experience, and affecting software development in 2025.
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