Deep learning is one of the most important advances in computing technology in our age.
While it may be in relative infancy, it’s already underpinning many of the smart services we take for granted today. As a pioneer in accelerating deep learning, NVIDIA has been developing deep learning software, libraries and tools for a number of years.
The majority of the deep learning solutions being deployed by science and industry today rely on GPU-accelerated computing to train and speed up challenging applications such as image identification, natural language processing and autonomous vehicles. NVIDIA GPUs and the Deep Learning SDK are driving advances in machine learning with organisations using their GPU-accelerated deep learning frameworks including Facebook, Microsoft and IBM.
As well as the tools to build and develop deep learning applications, NVIDIA also offer self-paced classes for deep learning that feature interactive lectures, hands-on exercises, and live Q&A with instructors through its NVIDIA Deep Learning Institute. Participants will learn everything they need to design, train, and integrate neural network-powered artificial intelligence into their applications. This is an introductory course, so previous experience with deep learning and GPU programming is not required. Anyone interested in finding out more can register for free classes and find more recommendations for resources to get started with deep learning.
The company also recently announced a global program to support the innovation and growth of startups that are driving new breakthroughs in artificial intelligence and data science. The NVIDIA Inception Program provides unique tools, resources and opportunities to the waves of entrepreneurs starting new companies, so they can develop products and services with a first-mover advantage. The program provides innovative startups with key support to help grow their businesses and bring revolutionary products to market faster. Start ups can apply to join here.
Earlier this year, Nvidia debuted their DGX-1, the world’s first supercomputer in a box designed specifically for deep learning. The turn-key system contains a new generation of GPU accelerators, delivering the equivalent throughput of 250 x86 servers.
It enables researchers and data scientists to easily harness the power of GPU-accelerated computing to create a new class of intelligent machines that learn, see and perceive the world as humans do. It delivers unprecedented levels of computing power to drive next-generation AI applications, allowing researchers to dramatically reduce the time to train larger, more sophisticated deep neural networks, therefore reducing time to market.
As part of our AI in Business festival, we recently spoke to Alex White, VP of Enterprise EMEA and Tom Bradley, Head of Developer Technology EMEA at Nvidia to hear more about how the company has become driving force behind deep learning technology.
Nvidia’s GPU Technology Conference
Taking place for the first time in Europe this September 28th – 29th in Amsterdam, the GPU Technology Conference is designed to expose the innovative ways businesses, developers and academics are using parallel computing to transform our world.
Deep learning and artificial intelligence will be a focus of the event, which includes expert sessions, hands-on labs and tutorials using the most popular deep learning frameworks, plus NVIDIA engineers on hand to answer your deep learning questions. Visit www.gputechconf.eu for more information and to register. Use discount code BELOGTCEU2016 for a 20% discount on your GTC registration!