Overview
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Explore the transition from proprietary to open source models in production environments through this informative 23-minute talk by Philip Kiely at the AI in Production conference. Discover how AI-native companies, from startups to enterprises, are leveraging open source ML models to power core production workloads efficiently and at scale. Learn about the importance of security, privacy, compliance, reliability, and control over model inference in production settings. Gain insights into achieving high-quality results, low latency, and cost-effectiveness when scaling AI applications. Understand the advantages of using model endpoints for prototyping ML-powered applications and the considerations for moving to production-ready solutions. Benefit from Philip Kiely's expertise as a software developer and author, drawing from his experience at Baseten and his background in Computer Science.
Syllabus
Graduating from Proprietary to Open Source Models in Production // Philip Kiely // AI in Production
Taught by
MLOps.community