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Nvidia is at the forefront of deep-learning-based artificial intelligence (AI) applications by providing key enabling technology: graphics processing units (GPUs). The company's bread-and-butter revenue comes from GPUs that power the computer gaming market, which is worth $100bn and growing, and this feeds into its research and development for advanced programmable GPUs. These GPUs are used in the high-performance computing market as well as real-world business applications and engineered products. With deep learning algorithms accelerated on GPUs, Nvidia’s future prospects will increase with the growth in the “massively parallel computation”-based AI market. Ovum predicts this market to become significant in the next decade, for example with applications enhancing speech and vision ranging from autonomous vehicles to robots in the home and office.

Business applications for deep learning are emerging from stealth mode

At Nvidia's GPU Technology Conference (GTC) 2015 in San Jose, CEO Jen-Hsun Huang announced the Titan X, the newest and fastest GPU yet with 8 billion transistors creating 3,072 CUDA cores and the ability to provide 7 teraflops in single precision. Huang also interviewed the CEO of Tesla Motors, Elon Musk, whose vehicles Huang described as “computers with wheels on” – Tesla already provides driver assistance powered by GPUs under the bonnet. Other vehicle manufacturers such as Audi, BMW, and Volkswagen exploit GPUs in similar manner.

The GTC saw a number of emerging companies with deep-learning-based technology that are already bringing in revenue. London-based Chase IT Services offers an appliance with GPUs running its Intelligent Voice technology to monitor trader phone conversations for financial services compliance purposes. Intelligent Voice is able to process multiple low-quality phone conversations and convert these into text within five minutes, and the solution then presents the user with advanced visual analytics to mine the text data and identify unusual conversations – those that depart from the norm in the given environment. Chase IT Services’ customers include investment banks, which have increased their trader scrutiny since the 2008 financial crisis on the back of multimillion pound regulatory fines. Another example, also London-based, is Multi-Agent Technology, which offers real-time scheduling and other logistics solutions for a growing client base, for example in the transportation business, and which exploits the powerful parallel processing of GPUs. The market for AI-based applications powered by GPUs is at an early stage, and as these systems provide enhanced human-machine interfaces, for example for understanding human speech at first hearing and for robot vision and other tasks involving understanding images, its growth is likely to accelerate.


Further reading

“Open source is accelerating artificial intelligence innovation," IT0022-000328 (March 2015)

Machine Learning in Practical Business Applications (forthcoming)


Michael Azoff, Principal Analyst, Ovum Software.

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