HPE’s New Set Of Artificial Intelligence Platform And Services Aim To Ease Out Deep Learning Deployment For Enterprises
To help companies simplify the adoption of AI, HPE announced new purpose-built platforms and services capabilities, which will have an initial focus on deep learning, a key subset of AI. It is well understood that deep learning is typically implemented for challenging tasks such as facial recognition, image classification and voice recognition, and to avail these enterprises need a high performance computer infrastructure that can build and train learning models and manage large volumes of data to recognize patterns in audio, images, videos, text and sensor data. Many organisations lack several integral requirements to implement deep learning and to help customers overcome these challenges and realise the potential of AI, HPE is coming up with following offerings: HPE Rapid Software Installation for AI: Based on the HPE Apollo 6500 system in collaboration with Bright Computing, this integrated hardware and software solution can enable rapid deep learning application development. This solution includes pre-configured deep learning software frameworks, libraries, automated software updates and cluster management optimised for deep learning and supports NVIDIA® Tesla V100 GPUs. HPE Deep Learning Cookbook: Built by the AI Research team at Hewlett Packard Labs, the deep learning cookbook is a set of tools to guide customers in selecting the best hardware and software environment for different deep learning tasks. HPE AI Innovation Centre: This would serve as a platform for research collaboration between universities and enterprises on the cutting edge of AI research and HPE researchers. The centres are currently based in Houston, Palo Alto, and Grenoble. Enhanced HPE Centers of Excellence (CoE): HPE CoE offers select customers an access to the latest technology and expertise including the latest NVIDIA GPUs on HPE systems, to help IT departments and data scientists to realise better ROI from their deep learning deployments. The current CoE are spread across five locations including Houston; Palo Alto; Tokyo; Bangalore, India; and Grenoble, France. “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.” With AI becoming mainstream, it aims at transforming lives by automating task that don’t require complex human thinking, and has been adopted in various industries with its various applications such as voice interfaces, personal assistants, image tagging and much more.
To help companies simplify the adoption of AI, HPE announced new purpose-built platforms and services capabilities, which will have an initial focus on deep learning, a key subset of AI. It is well understood that deep learning is typically implemented for challenging tasks such as facial recognition, image classification and voice recognition, and to avail […]
To help companies simplify the adoption of AI, HPE announced new purpose-built platforms and services capabilities, with initial focus on deep learning
["HPC Data Management Software"]
["Go", "API", "artificial intelligence", "AI", "innovation", "HPC Data Management Software", "Aim", "deep learning", "GAN", "V100", "R"]
["AI", "artificial intelligence", "deep learning", "Aim", "R", "Go", "API", "GAN", "innovation", "V100"]
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.