NVIDIA - How Ai Changes Industries: A Software Challenge by iThink Media

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Jaap Zuiderveld, Vice President EMEA at NVIDIA, says harnessing AI capabilities helps organisations to gain a competitive advantage.

Written by Anna McMahon | Produced by Danielle Harris

NVIDIA WAS STRONGLY FOCUSED ON GAMING UP UNTIL AROUND 10 YEARS AGO WHEN IT MADE THE SHIFT TOWARDS AI AND THE ENTERPRISE MARKET.

oday, the company helps large organisations to get started with AI in order to gain a competitive advantage. To understand how this is achieved, Jaap Zuiderveld, Vice President EMEA at NVIDIA, says you must first unravel the definition of AI. He explains, “When we talk about AI, it is not the

definition everyone uses. We start by looking at the challenges that are really difficult to solve and try to find a solution. For many years, AI was viewed as complex and expensive, but we have now made it available to everybody by making the technology accessible and making sure everyone can understand the

benefits of AI. That is how NVIDIA started life, and it remains where we are today.” NVIDIA’s approach has been to democratize AI, thus enabling the company to move fast in the market. Jaap provides the example of the use of AI in gaming, allowing shadows to be formed in a natural way. He says, “Gamers appreciate that the image is not just black and white. We used AI to program the software to cast ‘natural’ 6

shadows, helping us to quickly do what we could not have done before. Also, in the case of the development of the Covid-19 vaccine, NVIDIA computer systems were used to help scientists do their work in a much faster way. One of the biggest challenges NVIDIA faces surrounds a lack of knowledge here in Europe, as well as in other countries around the world. Jaap explains, “Knowing what to do with the technology

“NVIDIA’S APPROACH HAS BEEN TO DEMOCRATIZE AI, THUS ENABLING THE COMPANY TO MOVE FAST IN THE MARKET” because the investment in AI is significant, but what you can get back from it will be even greater.”

and how to use it is a big problem. The second challenge is the awareness of the market from a competitive point of view. You need to start investing in the technology because failure to do so means your competitors will invest in it first. Finally, companies must collaborate, rather than approach their markets in silos. I think, for me, it is clear that all the different verticals need to work together – government, research, education, as well as industry. You cannot work in silos anymore

So, how does NVIDIA work with organisations to realise the benefits of AI? Jaap answers, “We start by asking how we can teach someone to consider what is important. It is not through holding their hand, but by giving examples and communicating our view, that we can leave it up to the prospective buyer to make their decision. We purely give them guidance.” Having acknowledged a real interest in the market, NVIDIA recently invested in building Cambridge-1, the UK’s fastest 7

The New Era of Artificial Intelligence Today, artificial intelligence (AI) is the emerging technology that is accelerating the pace of change across our world and beyond. Rapid change in AI has been driven by change in 3 areas: Mathematics, Compute, and Data culture. The emergence of modern data science, the use of new algorithms in machine learning, Deep Learning and Neural Network space, and new data platforms that enable quick, accurate data storage and processing at the right place and time.

the underlying engineering platform. This is where Dell Technologies, together with partners like NVIDIA, bring true innovation to the AI space. Data Science, the use of advanced mathematics and mathematical functions to prise open information from “Data,” ultimately results in outcomes. Combined with advancements in Compute Technology and our attitude toward and relationship with “Data,” it has indeed accelerated our world into the new era of AI.

Data science, advancements in computer technology, and our attitude and relationship with data has led us into this new era of AI. It relies on the availability of real-world data and the speed at which it converts that data into usable and valuable information. However, as AI technology advances, we must ensure data accuracy is maintained. Therefore, training machinelearning models at high-speed while maintaining accuracy and precision is vital for data scientists.

Along with algorithms and advanced computation facilities, the accuracy of the models constituting AI rely heavily on the availability of real-world data and the speed at which we can access, cleanse, and convert it into usable and valuable information. In AI training, we strive to train networks faster, but this can lead to a decrease in accuracy. As a result, training machine-learning models at high-speed while maintaining accuracy and precision is a vital goal for Data Scientists.

The time required to train AI machines is influenced by computing and communication time. Adopting more straightforward computational methods increases speed without sacrificing accuracy. Driving new AI applications and workloads also requires changes to

Similarly vital is the architecture and the methodology used during the training process. The time required to train AI machines is affected by the complexity of building and tuning an architecture, at the Software and Hardware Platform level, as well as computing and communication time.

Adopting a simple computational method to replace the more traditional methods used previously makes computation much faster without losing accuracy. As communication time is affected by the size of data blocks, we are now looking at communication techniques that will combine smaller pieces of data into larger ones, optimising the transmission pattern and thereby improving the efficiency of communication during AI training. At Dell Technologies, we have always looked at complexity and cost across entire ecosystems and how with industry, we can drive focus into “Democratisation” and “Commoditisation” of technology to simplify and standardise at the technology-level to drive value. This is where Dell Technologies make a serious impact in AI and Modern Analytics. There is an onslaught of Data being generated at “The Edge” or at the Data source and this is where the power of AI and machine learning becomes real – when organisations can deliver better products, services, solutions, and experiences based on data-driven decisions, with speed and accuracy. Our heritage is steeped in exceptional and essential Compute Technology that is designed to drive for better outcomes made possible by end-to-end solutions fuelled by Data. We improve both speed and energyefficiency by performing AI calculations

in the traditional analogue domain at the location of the data – in our Hospitals, and Manufacturing Facilities. Additionally, in automobiles and mobile devices, across business, industry, and right across society. These technologies, enabled by significant advances in software, will underpin the formation of a new human-machine partnership, with the potential to solve complex problems and surface new insights that have been unattainable, up to now. We are using AI to solve some of the most important and complex problems on our planet today, and the work we continue to do in AI at industry-level, will evolve new technologies that will drive significant change into our world today, and into the future. Over the last few years, Dell Technologies and NVIDIA have established a strong partnership to help organizations fast-track their AI initiatives. Our partnership is built on the philosophy of offering flexibility and informed choice across a broad portfolio which combines best of breed GPU accelerated compute, scale-out storage, and networking Learn more at DellTechnologies.com

“WE SUPPORT COMPANIES TO MAKE THEM SUCCESSFUL, GUIDING THEM IN THE ACCELERATION OF THEIR AI APPROACH. WE ARE WORKING WITH DELL, FOR EXAMPLE, MOSTLY ON LARGER AI ENVIRONMENTS”

supercomputer dedicated to healthcare research. It will be used both by NVIDIA researchers and developers, as well as by researchers at UK healthcare and life sciences companies and academic institutions, to address pressing medical challenges, including those presented by Covid-19. It is only now that partners understand the technology that, Jaap says, they can see the potential of investing in it. He adds, “It is not just about the hardware; that is the easy part. What is more important is understanding the ecosystem.” NVIDIA provides its customers with a full package comprising the software and a team of 10

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solution architects to work directly with them to address their individual needs. Jaap continues, “Our aim is to teach our customers what to do, but we also offer different packages, fine-tuning them to meet a specific requirement. We start by asking ‘How can we help you?’. That is the important piece of the puzzle. Many companies say they have an AI strategy, but there are often a lot of gaps, which lie mostly in their lack of knowledge. We advise companies to firstly understand what they are looking for before investing in a solution.” The benefits of harnessing AI capabilities for organisations are broad in context and broad in scope, as Jaap explains, “There are millions of advantages to using AI. First of all, if you take healthcare, for example, Oxford Nanopore Technologies have been able to do genome sequencing using our technology, which has been crucial during Covid times, as they were able to quickly trace from where the virus had 14

“5G IS NOT JUST ABOUT CONNECTIVITY SPEED, BUT CHANGING THE WAY PEOPLE WORK THROUGH THEIR COMPUTERS. WE ARE JUST AT THE BEGINNING OF THE JOURNEY, BUT IT IS SURE TO HAVE A HUGE IMPACT ON THE MARKET”

originated. If you think about the automotive industry, self-driving cars have been designed to have a huge impact on the way we move from A to B. Plus, our technology can also do image recognition, voice recognition, fraud detection, and natural language processing, improving the customer experience and making it more secure.” Jaap says the key to success is having a strong focus on the different market verticals, be it healthcare, automotive or finance, for instance. He continues, “We have a specialist on board, who comes from that particular market and speaks the language. When we get feedback, we can then understand what we need to do whilst listening to what our customers have to say. It is so important to understand the individual needs of our customers, specific to each market vertical.” Another key factor is making the software accessible to accelerate other business applications, as Jaap says it is

not just about solving AI problems. He adds, “If you want to have an outcome from a database, it can sometimes take two or three days before you have an answer. But, with AI, you can have an answer in an hour, and your decision might be completely different. We are exploring topics such as this when embedding our technology in the servers of the big players.” Speaking of which, Jaap agrees that forming great partnerships with other organisations is crucial. He says, “We support companies to make them successful, guiding them in the acceleration of their AI approach. We are working with Dell, for example, mostly on larger AI environments. In general, we train companies to learn how to reach a larger market, as well as understanding what we can do differently to allow them to succeed even more. It is a twoway street. You are only successful if you both see an advantage. Customers are starting to ask these questions, so now is the right time to invest in AI to get a competitive advantage.” As for the future, NVIDIA is working heavily on initiatives such as the Cambridge-1 project to help industries see the advantage

in leveraging supercomputer capabilities. Jaap enthuses, “The whole industry is starting to work together with research, education and the different market verticals. I am really excited about the recent BMW collaboration where we introduced the Omniverse platform, enabling them to design and change a robotic production line remotely, and as a result, transform the production line environment. It is mindboggling! 5G is not just about connectivity speed, but changing the way people work through their computers. We are just at the beginning of the journey, but it is sure to have a huge impact on the market.” Around 2,000 European AI start-ups are part of NVIDIA’s Inception start-up incubator, with the majority in the healthcare sector. Jaap concludes, “There are so many exciting things happening in healthcare, but our focus remains on making the technology accessible to everyone. The only way we can do this is by making it easier for people to use in every part of the world.” For further information, visit www.nvidia.com