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generated. That approach reduces bandwidth requirements and helps agencies achieve what AI promises, which is faster and more accurate decisions.
For any AI project, agencies need
to identify the data that is immediately actionable and the data that is historically valuable. Not all historically valuable data is immediately actionable, but all immediately actionable data is historically valuable.
Federated learning allows agencies to train models using historically valuable data and then push the algorithm to
the edge where it can process new data fast. It allows agencies to leapfrog the technical debt and network latency that are associated with moving data. And it allows them to make smart decisions on which data to move, which data is time sensitive and, better yet, which data can
be processed at the edge.
Industry leaders like Dell can help
agencies sort through their many options for quickly deploying scalable architectures so they can incorporate AI into their daily operations.
Al Ford is AI alliances manager and Brian Carnell is chief AI architect at Dell Technologies.
Learn more at Carah.io/FCW-AI-Dell
Federated learning allows agencies to train models using historically valuable data and then push the algorithm to the edge where it can process new data fast.
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