NVIDIA’s Jack Watts: Our GPUs Break Down Barriers to Deep Learning in Business

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NVIDIA’s Jack Watts: Our GPUs Break Down Barriers to Deep Learning in Business

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NVIDIA. Long-standing titans of the gaming and mobile computing market with their cutting-edge graphics processing units (GPUs), now key players in the artificial intelligence and deep learning space.
So how does NVIDIA’s processing power translate into the enterprise – how might it come into play in a practical business setting?
To find out, AI Business spoke to Jack Watts, Industry Business Development for Deep Learning at NVIDIA. Jack works with industry start-up and commercial companies who are leveraging NVIDIA technology in their artificial intelligence or deep learning research and applications, so was perfectly placed to discuss the implementation of NVIDIA’s platform in the business world.

 

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Jack Watts of NVIDIA

Thinking about the impact of AI and deep learning on business overall, Jack sees limitless potential for application:

“It’s difficult to overstate how significant the impact of AI is going to be on every aspect of business. Artificial intelligence won’t be an industry, it will be part of every industry, as well as impacting our day to day lives as consumers.

“An important aspect of artificial intelligence, and in particular the branch of AI called deep learning, is its ability to make sense of big data. From retail and healthcare to banking and manufacturing, organisations are producing data on a scale that’s simply too massive for manual processing to be an option. In combination with graphics processing units (GPUs), which deliver the extreme processing power required, deep learning offers a way to turn the ‘black box’ of big data into solutions that will transform business”.

 

Jack cites a number of examples across several industries in which AI is either playing a key role already, or is set to transform industries in the future.

“We’re already seeing companies using AI to customise the way consumers interact, procure and receive services from vendors. Retailers like Amazon and Netflix suggest products that fit our preferences, a technique that uses deep learning to analyse not only our own purchasing and browsing history but that of thousands of other consumers to deliver uncannily accurate results.

“In warehouses and manufacturing plants, AI will also be revolutionary. Industrial robots which can learn new processes, rather than require costly modification or replacement, will bring huge gains in effectiveness and flexibility to production lines. There’s some exciting work being done in this ‘future factories’ field by companies like French start-up Akeoplus. And in warehouses, we’ve already seen online retailing giant Zalando achieve impressive improvements in its systems by implementing deep learning to calculate the most efficient picking routes.

“At a more personal level, there is exciting work being done with deep learning in the medical space. Thanks to AI, we can expect more personalised care and improvements in the detection time for devastating diseases like cancer. We also have the opportunity to begin predicting diseases with much greater accuracy. Start-up DreamQuark is using GPUs to analyse medical records and data, developing prediction and care solutions for healthcare and insurance providers”.

 

Jack explains NVIDIA’s approach to this from the perspective of deep learning:

“The advantage of deep learning is that you can use feature detectors in a neural network to train a model which can then be deployed. Unlike conventional computing approaches, it doesn’t require a domain expert because deep learning algorithms are extremely versatile in the problems they can address. The process of training a neural network is hugely computationally expensive, which is why our massively parallel GPUs are being leveraged to accelerate training and create more accurate models.

“In addition to NVIDIA GPUs, a lot of companies now are utilising our DIGITS software platform. DIGITS enables data scientists to train neural networks with bespoke data on common frameworks without an expert-level understanding of how the frameworks are coded, making the process much more accessible”.

 

Discussions turns to The AI Summit in London in May. We first asked Jack for his key takeaways from the event:

“One of the main takeaways for me was the huge diversity in industries and professionals seeking information around the buzz of AI and how they can take advantage of it. I was pleasantly surprised to see a lot of CxO level attendees – I’m more used to seeing developers or end-users at conferences. It’s encouraging that this level of attendee wants to understand first-hand how to drive their organisations into the AI era and better serve their employees, customers and shareholders. It’s a real testament to the importance of this technology”.

 

So how does all this sit from NVIDIA’s perspective – and how will Jack’s experience of The AI Summit impact his approach to business at NVIDIA?

“NVIDIA has been attracting a lot of attention in the AI space recently. This is really the culmination of years of investment in developer relations, software tools and engagement with academia. The experience of being at The AI Summit has been instrumental in helping me understand the levels of knowledge out there in the attendee base. I’m looking forward to working more closely with the companies and individuals I met at the event and giving them the support to leverage NVIDIA’s deep learning and AI platforms and deploy this transformative technology within their organisations”.

 

Looking more specifically at NVIDIA, Jack shared his thoughts on the short- and long-term future of the company in the enterprise.

“Several years ago we committed ourselves as a company to investing in deep learning. Now that commitment is bearing fruit and we find ourselves in a position of leadership as this new computing model takes the world by storm. We will continue to work very closely with the developer community to ensure that all the major frameworks, libraries and applications on which deep learning relies are extremely compatible with the GPU.

“Here in Europe, an important ingredient in our strategy is the introduction of our GPU Technology Conference to Europe. Taking place in Amsterdam on September 28 and 29, it will bring together Europe’s brightest minds and best ideas focused around three technology mega-trends: deep learning, autonomous vehicles and virtual reality.

“In the longer term, we already have our eye on what’s next. Our mission is to serve the world’s most demanding customers and help them solve the most challenging, complex problems”.

 

As the biggest player in Visual Computing, the advancements made by NVIDIA could dramatically influence the scale of AI and its adoption in business. Jack elaborates on this notion, describing the trends that he foresees in the near future.

“The next big trend we expect to see is the widespread deployment of deep learning-based applications in the enterprise datacentre. At the International Supercomputing Conference, held recently in Frankfurt, industry analysts IDC identified deep learning and big data as two of the most important growth drivers in the high performance computing space. To support this, we’ve already announced our latest-generation GPU architecture, called Pascal. The Tesla P100 has been specifically designed to meet the demand for high performance and hyperscale computing in the accelerated datacentre.

“We’re seeing huge demand from organisations that just can’t wait to get started in deploying AI. We responded to this by creating a ‘plug and play’ deep learning supercomputer in a box, called the NVIDIA DGX-1, that makes is quick and easy for enterprises to innovate and get to market. “The combination of GPUs and our supporting NVIDIA SDK, containing a range of software tools for developers, means the barrier to entry for organisations to deploy deep learning is falling. We’re already seeing this technology delivering new business models and solutions in sectors from drones and robots to PCs and servers, from cloud services to autonomous vehicles. Deep learning and artificial intelligence are in the grip of a ‘big bang’ and our technology platforms will be instrumental in realising its potential for businesses”.

 

We spoke to Jack after he attended the inaugural AI Summit in London on 5 May together with over 400 other influential AI and business leaders. The second, larger AI Summit takes place in San Francisco on 28-29 September. To find out more, and to join us at the Fort Mason Center in September, visit: theaisummit.com

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