Using HPE
AI and Machine Learning But
there is a real method to the madness. As envisioned, “Swarm Machine Learning”
is targeted at scenarios involving privacy or regulation that preclude or
discourage data from getting moved. That’s the rationale for the blockchain.
For instance, you may have a group of hospitals that are cooperating in a study
for applying machine learning to disease prevention, detection, or outcomes,
but patient data is the immovable barrier. HPE implements a blockchain based on
Ethereum technology that allows data to stay in place, models trained and run
locally, in an environment where model results that are exchanged become
tamper-proof. HPE sets up a Swarm network where individual nodes register, and
then those nodes perform the modeling. It incorporates several components. It
starts with Swarm Learning libraries that are delivered as containers that can
run on any target infrastructure that is HP HPE2-N69 Exam Dumps based on Kubernetes. The models
themselves stay intact; HPE claims that the models can be deployed on the swarm
with just four additional lines of code. Then there is the Swarm Network, which
is the blockchain, a control plane, and a license server. Potential Use Cases
There are numerous potential use cases for distributed learning. In the
healthcare domain, hospitals around the world can apply ML to identify cancer
on MRI images, providing a large base of training data that does not have to be
moved into a central place.
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