GPUs to drive the future of artificial intelligence – Both traditional chips and graphics processors are behind the leaps in the AI-powered services.
We have witnessed some eventful moments from the launch of affordable 4G to the arrival of the first Indian robot, and all the way to autonomous vehicles and more. These breakthroughs have shown a world where imagination and intelligence are amplified by technology. My outlook for 2017 is singular: human intelligence will be simulated widely, and computers, robots and self-driving cars will perceive and understand the world. This confidence stems from a few forces that have converged in 2017.
We are well on track to achieve one of the world’s loftiest goals for supercomputing: exascale computing. The next generation of supercomputers will tackle the most complex computational science challenges, such as predicting physical and biological behaviour. We won’t just have intelligent computers, but intelligent supercomputers helping solve our biggest problems. And these computing resources will be more accessible than ever before, thanks to cloud-based usage models. For example, startup incubator T-Hub will house the first AI supercomputer-in-a-box for startups in India. Such democratization of supercomputing will enable entrepreneurs to harness accelerated computing and AI to create a new class of intelligent applications that can learn, see and perceive the world as humans do.
Next, as India moves towards sustainable, tech-enabled Smart Cities, there will be a strong focus on security, intelligence and investigative capabilities. This includes advanced search and facial recognition analytics using multiple visual resources. Intelligent video analytics will contribute to safer, more secure communities and infrastructure.
These innovations will be driven by a compute platform called the graphics processing unit or GPU. This processor was originally invented for immersive 3D graphics in gaming, but its versatile nature has proved a match for many of our most important computing problems, from supercomputing to artificial intelligence.
The secret of the GPU’s power is its ability to handle large amounts of information at the same time, an approach known as parallel processing. The know-how to code applications in parallel and unleash the power of GPU has already become a ‘must have’ skill for application developers. As a compute model called GPU-accelerated deep learning, in which computers learn to write their own software, ignites the big bang of AI, the skills to apply this technology will be in massive demand. Data scientists and developers with an eye to career development are adding parallel programming and deep learning expertise to their CVs. GPU’s power is its ability to handle large amounts of information at the same time, an approach known as parallel processing. The know-how to code applications in parallel and unleash the power of GPU has already become a ‘must have’ skill for application developers. As a compute model called GPU-accelerated deep learning, in which computers learn to write their own software, ignites the big bang of AI, the skills to apply this technology will be in massive demand. Data scientists and developers with an eye to career development are adding parallel programming and deep learning expertise to their CVs.
Deep learning helps computers unlock the ‘black box’ of big data to make sense of huge amounts of information in the form of images, sound, and text. By discovering patterns and insights in data too vast and complex for humans or conventional computing to analyse, companies are already creating new services, becoming more efficient and growing their business.
All these factors are combining to make 2017 the year of artificial intelligence in India. AI won’t be an industry – it will be part of every industry, not to mention enabling exciting new experiences for consumers via their apps and devices. The possibilities are endless – and we’ve only just begun.
– Vishal Dhupar, Managing Director, NVIDIA – South Asia
