What are the tracks?
summary
Four tracks spell out concrete takeaways: AI in research shows how teams run large and smaller LLMs, which libraries get used, and tradeoffs in model size and latency; industrial applications lists real-world deployments across automotive, manufacturing, agriculture and healthcare, the data collection and training bottlenecks encountered, and the innovations that reduce labeling cost; economies of data science drills into MLOps practices for scaling, lifecycle orchestration, and how organizations version, monitor and serve models at scale.
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chapters (3)
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