Determined AI’s open-source platform is designed to eliminate the complexity and cost associated with machine learning development


HPE building in Omaha, Nebraska. (Credit: Tony Webster/

Hewlett Packard Enterprise (HPE) has acquired San Francisco-based startup Determined AI to enhance its high performance computing (HPC) offerings.

Using its open-source machine learning (ML) platform, Determined AI provides a software stack to accelerate the training of AI models.

With the acquisition, HPE intends to integrate Determined AI’s software offering with its HPC solutions to allow ML engineers to easily implement and train machine learning models for accurate insights.

Founded in 2017, Determined launched its open-source platform in 2020. The company’s solution is claimed to be deployed by customers across a range of industries, such as biopharmaceuticals, autonomous vehicles, defence contracting, and manufacturing.

By eliminating the complexity and cost associated with machine learning development, the company’s platform helps researchers and scientists to focus on innovation speed up their time to delivery.

The platform helps in making it easy to set-up, configure, manage and share workstations or AI clusters that run on-premises or in the cloud.

HPE HPC and mission critical solutions (MCS) senior vice president and general manager said: “As we enter the Age of Insight, our customers recognize the need to add machine learning to deliver better and faster answers from their data.

“AI-powered technologies will play an increasingly critical role in turning data into readily available, actionable information to fuel this new era.

“Determined AI’s unique open-source platform allows ML engineers to build models faster and deliver business value sooner without having to worry about the underlying infrastructure. I am pleased to welcome the world-class Determined AI team, who share our vision to make AI more accessible for our customers and users, into the HPE family.”

Determined AI’s platform is also designed to enable users to train their models easily through a range of capabilities that accelerate training.

The capabilities consist of accelerator scheduling, fault tolerance, high-speed parallel and distributed training of models, advanced hyperparameter optimisation and neural architecture search, reproducible collaboration and metrics tracking.

In March this year, HPE has unveiled various innovation updates to its HPE GreenLake cloud services portfolio. The updates were rolled out with an objective to drive cloud disruption.