Tech

IBM and Nvidia Partner Up To Create Faster Deep Learning Hardware In Bid To Improve Artificial Intelligence

By Adie Pie , Nov 15, 2016 05:37 AM EST

As technology continues to develop, there is an increasing demand for computers to be quicker and more accurate. And because different companies have different specialities and strengths, the tech world often times sees the partnership between competitors. The most recent release from IBM and Nvidia is the perfect example, as the companies unveil PowerAI.

Venture Beat notes that the two companies have partnered together in order to solidify the foundation of artificial intelligence. In essence, the project aimed to speed up the process of training computers in order to think and learn more like how humans do. PowerAI runs on the newly announced IBM server, which was specifically built for artificial intelligence and runs on Nvidia's NV Link technology.

IBM PowerAI is optimized for the company's most powerful server in its OpenPower LC lineup, the IBM Power S822LC for High Performance Computing (HPC). This features the Nvidia NVLink technology, which is optimized for Power architecture and Nvidia's graphics chips. However, PowerAI will work with Watson.What results two times more performance than its current competitors.

TechRepublic adds that IBM and Nvidia promised that PowerAI is the "world's fastest deep learning enterprise solution" and will "help train computers to think and learn in more human-like ways at a faster pace." The press release also confirmed that the new technology is already in place in various banks for fraud protection, as well as in facial recognition applications and even self-driving vehicles.

"Coupled with our high performance computing servers built for AI, IBM provides what we believe is the best platform for enterprises building AI-based software, whether it's chatbots for customer engagement, or real-time analysis of social media data," the press release said.

Deep learning is a machine-learning method that has currently been prefered in almost all traditional industries because of its speed and efficiency. It quickly extracts information from millions of pieces of data and correspondingly ranks these based on importance.

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