HPE Swarm Learning Increases Accuracy and Reduces Biases in AI Model Training

Hewlett Packard Enterprise is unveiling HPE Swarm Learning, a breakthrough AI solution to accelerate insights at the edge, from diagnosing diseases to detecting credit card fraud, by sharing and unifying AI model learnings without compromising data privacy.

HPE Swarm Learning, which was developed by Hewlett Packard Labs, HPE’s R&D organization, is a privacy-preserving, decentralized machine learning framework for the edge or distributed sites.

The solution provides customers with containers that are easily integrated with AI models using the HPE swarm API.

Users can then immediately share AI model learnings within their organization and outside with industry peers to improve training, without sharing actual data.

“Swarm learning is a new, powerful approach to AI that has already made progress in addressing global challenges such as advancing patient healthcare and improving anomaly detection that aid efforts in fraud detection and predictive maintenance,” said Justin Hotard, executive vice president and general manager, HPC & AI, at HPE. “HPE is contributing to the swarm learning movement in a meaningful way by delivering an enterprise-class solution that uniquely enables organizations to collaborate, innovate, and accelerate the power of AI models, while preserving each organization’s ethics, data privacy, and governance standards.”

HPE Swarm Learning uniquely enables organizations to use distributed data at its source, which increases the dataset size for training, to build machine learning models to learn in an equitable way, while preserving data governance and privacy.

To ensure that only learnings captured from the edge are shared, and not the data itself, HPE Swarm Learning uses blockchain technology to securely onboard members, dynamically elect a leader, and merge model parameters to provide resilience and security to the swarm network.

Additionally, by only sharing the learnings, HPE Swarm Learning allows users to leverage large training datasets, without compromising privacy, and helps remove biases to increase accuracy in models.

HPE Swarm Learning can help a range of organizations to collaborate and improve insights:

  • Hospitals can derive learnings from imaging records, CT and MRI scans, and gene expression data to be shared from one hospital to another to improve diagnostics of diseases and other ailments, while protecting patient information.
  • Banking and financial services can fight the expected global loss of more than $400 billion in credit card fraud over the next decade2, by sharing fraud-related learnings with more than one financial institution at a time.
  • Manufacturing sites can benefit from predictive maintenance to gain insight into equipment repairing needs and address them before they fail and cause unwanted downtime. By leveraging swarm learning, maintenance managers can gain better insight by collecting learnings from sensor data across multiple manufacturing sites.

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