Unlocking the 'Black Box' of Big Data: Why Artificial Intelligence will Soon be Your Organisation's Most Important Technology

By Vishal Dhupar, MD, NVIDIA

Big data is not an emerging tech trend: it’s already here. Every web click, transaction and connected device is pumping information into our systems. Staggeringly, 90 percent of all the data that exists today was created in the last two years. And data generation is only going to accelerate.

So how do we take the next step, from gathering data to analysing it and deriving meaning to inform decision making? From retail, healthcare and telecommunications to banking, manufacturing and self-driving cars, the scale on which organisations are producing data is simply too massive for manual processing to be an option.

Artificial intelligence, and in particular the branch of AI called deep learning, is answering this challenge. The ‘deep’ in deep learning refers to the way deep learning systems build layers of nodes or neurons, called artificial neural networks, to solve problems. These networks are roughly comparable to the structure of the
human brain.

In conventional computing, a programmer writes lines of code which tell the computer how to solve a problem. Deep learning is a completely new computing model which enables computers to solve problems by trial and error, in much the same way human children learn. Effectively, a computer using deep learning is writing its own software. It’s an extremely powerful approach because, unlike conventional programming, it allows computers to solve problems we don’t know the answers to by finding patterns in data.

In combination with graphics processing units (GPUs), which deliver the extreme processing power required by this approach, deep learning offers a way to turn the ‘black box’ of big data into solutions that will
transform enterprise.

For example, 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.

NVIDIA’s role in this deep learning revolution is pivotal. Not only does our core hardware technology, the GPU, accelerate deep learning so that results can be produced within a useful timeframe, but we have invested significantly in software tools that make deep learning accessible for business.

Several years ago we committed ourselves as a company to investing in deep learning. Now that commitment is bearing fruit, 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, startup and business communities to ensure that all the major frameworks, libraries and applications on which deep learning relies are extremely compatible with the GPU.

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 hyper scale computing in the accelerated datacentre.

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.

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