Master Production-Ready Machine Learning, Step by Step
Master Agentic AI, GANs, Fine-Tuning & LLM Apps
Overview
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Explore real-world deployment of open source software in automotive systems through practical lessons learned from mass production vehicle implementations. Discover how open source communities and academic research contribute to solving security gaps and improving system stability in software-defined vehicles. Learn about proven approaches for managing software supply chains and reducing dependency risks in MQTT-based remote vehicle diagnostics systems. Examine the critical connections between system utilities and safety functions, including time synchronization, dependency management, and data integrity within Linux systems. Understand the impact of these factors on file system selection and handling sudden customer requirements like STR (Suspend-to-RAM). Gain comprehensive insights into creating secure, safe, and compliant open source-based automotive systems that meet stringent safety and security demands while achieving faster time-to-market and higher performance in the software-defined vehicle landscape.
Syllabus
Driving Safety Forward: Lessons Learned From Deploying OSS in Real-world Automotive - Jaylin Yu, EMQ
Taught by
Linux Foundation