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Create more accurate digital twin models. Digital twin models can also be trained using federated learning by combining data from different sensors and systems.
Both Apache Wayang and Flower are well-known FL platforms with distinct use-cases. When these two components are combined, we have an OpenAI-like system with GPT3.
Should you put a data mesh in place? We discuss benefit and drawbacks, as well as terminology and when it makes sense to invest in that technology.
Federated Learning can be especially useful for sensitive data that cannot be shared with a central location like personal information or medical data.
Federated Learning can be used to train models on device data, such as sensor readings, in order to perform tasks like image recognition and anomaly detection.
