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Digital transformation tools move AI and deep learning forward

This blog post is part of our Essential Guide: Everything to know about overcoming digital transformation challenges

While today’s popular digital transformation tools have expanded the possibilities presented by analytics, social, IoT, and mobile, there’s also an underlying factor that can’t be ignored. Businesses can only transform fast enough if their underlying infrastructure is built to keep up.

So how are vendors helping provide the digital transformation tools that organizations require in order to move into the modern digital age? Apparently, data, information and analytics is an important part of the puzzle. “Data is to this century what oil was to the last—a catalyst of innovation and a revolutionary leader of change,” said Michael Greene, Intel’s VP of System Technologies and Optimization during his JavaOne 2017 keynote. “This is a total transformation across technology, moving from a compute-centric to a data-centric world.” For Intel, when it comes to digital transformation tools, it all comes down to speed, scale, and smarts.

“Performance is everything in a world where the difference between days and months can mean the success or failure of a business,” said Greene as he announced the new Intel Xeon scalable processors that are designed to work across a wide range of digital transformation tools involving 5G, cloud, networking, storage, and analytics. Key benefits include supporting more VMs, much faster cryptographic hashing, double the AI power, and a 3X increase Big Data optimization with Hadoop and Spark. Greene described this as the largest generational gain in performance in the last decade, along with the fact that there are features in the Java SE 9 release that are designed to take advantage of this fresh generation of infrastructure.

Scaling to address digital transformation challenges

And the performance of low level infrastructure like processing units, along with the ability for environments like Java SE 9 to take advantage of this infrastructure, because the vast amounts of data modern enterprises are generating is placing a great deal of stress on existing digital transformation tools. “From large data centers to the billions of device sensors on the edge, the data generated are growing at an exponential rate creating a couple of challenges,” said Greene. “First, data must be stored and accessed quickly if you want to turn valuable data into business insights. Second, massive transaction volumes require a much more flexible and scalable application architecture.”

But despite the daunting challenges the gargantuan amount of data modern enterprise systems create poses, there are advocates out there ready to assure the public that modern digital transformation tools are ready to tackle even the most difficult problems.“We are running about one hundred thousand Java Apps and one million instances,” said King Sum Chow, Chief Scientist at Ali Baba Systems Software. In Chow’s JavaOne 2017 keynote speech, he assured all of us that building distributed Java Services on top of the Java SE isn’t that hard. In fact, Java has proven itself as a reliable platform for creating and deploying Java based microservices that can operate and scale independently. But the Java platform doesn’t exist within a vacuum. Chow reiterated Greene’s sentiment that fast and reliable hardware is also an important piece of the puzzle when building digital transformation tools. “The better the hardware performance, the more creative we can be in delivering better and faster services. We are also interested in learning how to use the system memory in our applications.”

Digital transformation tools and AI

So what is the final result when fast and reliable hardware makes it possible for digital transformation tools to consume massive amounts of data? Apparently, all digital transformation roadmaps eventually lead to deep learning and artificial intelligence plays. “AI will be the tool that harnesses and converts a flood of data into powerful insights and smarter decisions,” said Greene. “Increasingly, these insights will be made not only by people but by machines themselves. Society’s being transformed on a spectacular scale. Machines that sense, reason, and act can accelerate solutions to large scale deployments.”

Regardless of which technology partners enterprises rely on to supply their infrastructure, these three factors of achieving greater speed, scale, and smarts are certain to play a role in moving digital transformation into the next generation. And as digital transformation tools evolve to match the increasingly capable hardware that drives them, new opportunities for consuming, interpreting and learning from the various data points applications generate will continue to emerge and subsequently change the digital landscape forever.

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