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Learn how Analog Devices (ADI) tackles the complex challenge of building robust AI solutions for electric vehicle battery management systems in this 22-minute conference talk. Discover the multifaceted nature of EV batteries, including their various parameters, chemical compositions, and associated risks that necessitate machine learning models as core solutions. Explore how automotive industry requirements and regulations like ASPICE drive the need for comprehensive experiment management, reproducibility, and audit trail capabilities. Understand the lessons learned from battery data collection processes and the continuous tracking of data, experiments, models, and results using Weights & Biases. Examine the unique nuances and limitations of implementing AI at the edge, along with ADI's innovative approaches to overcoming these challenges in the automotive sector.
