HPE dives into deep learning

deep learning

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Hewlett Packard Enterprise (HPE) has released a range of new offerings designed to simplify adoption of artificial intelligence (AI) technologies by data scientists, developers and IT departments.

The first solutions will focus on a subset of AI known as deep learning – typically implemented for data-hungry tasks such as image and facial recognition, image classification and voice recognition. To drive deep learning scenarios, enterprises typically a high performance compute infrastructure to build and train learning models.

According to HPE, organisations typically lack several key requirements for the implementation of deep learning, including the expertise and resources, hardware and software infrastructure, and integration capabilities to enable scaling of AI systems, and so has targeted its solution suite to address these requirements.

The new offerings include HPE’s Rapid Software Development for AI, an integrated hardware and software solution; the HPE Deep Learning Cookbook, a set of tools to guide software and hardware selection; HPE Image Classification Reference Designs, providing infrastructure configurations that are optimised to train models for various use cases such as license plate verification and biological tissue classification; the HPE AI Innovation Centres, located in Houston, Palo Alto and Grenoble; and enhanced HPE Centres of Excellence, providing customers with access to technology and expertise.

“We live in a world today where we’re generating copious amounts of data, and deep learning can help unleash intelligence from this data,” said Pankaj Goyal, vice president, artificial intelligence business, Hewlett Packard Enterprise.

“However, a ‘one size fits all’ solution doesn’t work. Each enterprise has unique needs that require a distinct approach to get started, scale and optimise its infrastructure for deep learning. At HPE, we aim to make AI real for our customers no matter where they are in their journeys with our industry-leading infrastructure portfolio, AI expertise, world-class research and ecosystem of partners.”

Deep learning is expected to help AI move beyond consumer applications such as voice interfaces and personal assistants to fields such as genomic sequencing analytics, climate research, medical science, autonomous driving and robotics.

“As deep learning-based AI advances, it will transform science, commerce and the quality of our lives by automating tasks that don’t require the most complex human thinking,” said Steve Conway, senior vice president, Hyperion Research. “HPE’s infrastructure and software solutions are designed for ease-of-use and promise to play an important role in driving AI adoption into enterprises and other organisations in the next few years.”

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