Autonomous driving systems need to enable federated on-device training of models in order to manage large scale, in-vehicle machine learning.
Data challenges
Collecting data from all cars in use is expensive and in many cases impossible due to connection problems and the sheer quantity of data generated by modern cars.
Federated learning
Federated Learning addresses the challenges by training on-board machine learning models in a federated setting so that each single car can learn from individual, group and fleet data. Learn more: AI Sweden EdgeLab
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