Diverse support centers and platforms aim to speed up AI development.
Hewlett Packard Enterprise (HPE) has also moved into the artificial intelligence world with a new suite of services and platforms to aid companies in understanding deep learning tech. The company is placing emphasis on deep learning which is a crucial subset of Al.
Most times, when carrying out the implementation of this technology, companies require access to HPC or high-performance infrastructure which can train and build learning models for enhanced volumes of data. Nonetheless, many firms do not have resources and expertise in this field. The HPE is making efforts to make changes to this with its innovative offering. The goal is to simplify the adoption of Al.
The platform was created using the concept of the HPE Apollo 6500 system in partnership with Bright computing, aiding companies to quickly develop applications for quick learning. Meanwhile, the so-called “Deep Learning Cookbook” Is a set of tools that are intended to aid companies to select the most appropriate software and hardware for various deep learning requirements.
The tools aid enterprises in estimating the performance of numerous hardware platforms according to HPE. It characterizes the most recognized frameworks for deep learning and chooses the ideal software and hardware stacks to suit their individual requirements.
HPE has also constructed an innovative center to render support for research projects in artificial intelligence which are long term.
Situated in Palo Alto in California, Texas, Grenoble in the South of France and Houston, the centers will provide support for independent academics, universities, and enterprises.
It is establishing support for data scientists and IT departments looking to hasten the development for their deep learning applications as well. They will be situated in Grenoble, Houston, Tokyo, Palo Alto, and Bangalore.
The vice president of artificial intelligence business at Hewlett Packard Enterprise, Pankaj Goyal, stated that we live in a world today where we are creating an incredible amount of data and deep learning can aid in unleashing intelligence from this data.
Every enterprise has distinct requirements and need a unique approach to scale, and optimize its deep learning infrastructure. It is because of this reason that a one size fits all solution does not work.