HPE Swarm Learning increases accuracy and reduces bias in training AI models

Hewlett Packard Enterprise unveils HPE Swarm Learning, a breakthrough AI solution to accelerate insights to the edge, from disease diagnosis to credit card fraud detection, by sharing and unifying AI model learnings without compromise data confidentiality.

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

The solution provides customers with containers that easily integrate with AI models using the HPE Swarm API.

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

“Swarm learning is a powerful new approach to AI that has already made strides in addressing global challenges such as improving patient healthcare and improving anomaly detection that aids efforts 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 providing an enterprise-class solution that uniquely enables organizations to collaborate, innovate, and accelerate the power of AI models, while preserving standards ethics, data privacy and governance of each organization. ”

HPE Swarm Learning enables organizations to use distributed data at its source, increasing the size of the dataset for training, build machine learning models to learn fairly, while preserving governance and data privacy.

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

Additionally, by sharing only learnings, HPE Swarm Learning allows users to take advantage of large training datasets, without compromising privacy, and helps eliminate bias to increase model accuracy.

HPE Swarm Learning can help a range of organizations collaborate and improve their knowledge:

  • Hospitals can learn from imaging recordings, CT and MRI scans and gene expression data to be shared across hospitals to improve the diagnosis of diseases and other conditions, while protecting information from patients.
  • Banking and financial services can combat the expected global loss of over $400 billion in credit card fraud over the next decade2 by sharing fraud knowledge with more than one financial institution at a time .
  • Manufacturing sites can benefit from predictive maintenance to better understand and respond to equipment repair needs before they fail and cause unwanted downtime. By leveraging swarm learning, maintenance managers can gain better insights by collecting learnings from sensor data across multiple manufacturing sites.

For more information on this news, visit https://www.hpe.com/us/en/solutions/artificial-intelligence/swarm-learning.html.