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Machine Learning’s Future: Fortune 500 Buys In, Manufacturing Sees The Light

By   /  April 7, 2014  /  No Comments

STServerby Jennifer Zaino

Martin Hack, CEO and co-founder of machine learning company Skytree, has a prediction to make: “In the next three to five years we will see a machine learning system in every Fortune 500 company.” In fact, he says, it’s already happening, and not just among the high-tech companies in that ranking but also among the “bread and butter” enterprises.

“They know they need advanced analytics to get ahead in the game or stay competitive,” Hack says. For that, he says, they need machine learning algorithms for analyzing their Big Data sets, and they need to be able to deploy them quickly and easily — even if those who will be doing the deployments are coming from at best a background of basic analytics and business intelligence.

“There just aren’t enough data scientists to go around,” he says. It’s very tough to fill those roles in most companies, he says, “so like it or not, we have to make it much, much easier for people to digest and use this.”

The C-suite see the need for leveraging machine learning to advanced analytics in order to guide their next steps more clearly than ever, Hack believes, which is driving rapid adoption. That – along with the company’s emphasis on making the technology accessible to business users, as discussed here – has worked in Skytree’s favor, which announced last week that it has grown booked revenues by over 300 percent on an annual basis since the company officially launched in 2012.

Skytree, whose Skytree Server suite of machine learning software has been certified to work with Hortonworks, MapR Technologies, and Cloudera Hadoop distributions si that enterprises could run the technology without moving their data, last week also became certified on Cloudera 5, the latest version of Cloudera’s unified analytic data management platform. “Hadoop is becoming more and more mission-critical,” says Hack. “Hadoop seems to be the de facto standard in the industry for Big Data infrastructure, and it’s a natural thing for us to ride atop that.,,, Most customers, if haven’t [begun using Hadoop] last year, they probably are planning for it this year, and they can turn machine learning on on top of that if they want to.”

Where The Action’s At

Financial services is a key Fortune 500 vertical for the technology, Hack says, but a big opportunity going forward is in the manufacturing sector. “It’s probably the most most underserved industry now in relation to advanced analytics and Big Data,” he says. But it can become a more competitive industry as it becomes a more data-driven one, with opportunities to become more effective in areas such as supply chain management and market responsiveness, Hack thinks.

“The more predictive you can be about your product, its lifecycle, market demand, and the manufacturing process, the bigger your chance to compete in the marketplace,” he says. “We are certain doing so will lower costs. “

Meanwhile, Skytree continues to create new methods and algorithms to beomce part of its platform, as it also reacts to what Hack sees as three major trends. The first of these, he says, is automation and artificial intelligence coming back full circle in being part of the machine learning stack, furthering the cause of letting even non-data savvy workers become users of these tools. “Automation is a big game-changer going forward,” he says. “It’s already part of the product but we will have more emphasis on that” aimed at delivering ease of use sometime in this quarter.

Deep learning is another trend Skytree has its eyes on to become part of its platform, but it’s taking this one cautiously. “It sounds exciting but the business applications still have to be ironed out. We’re working on this, too,” he says.

Finally, the next step is around reinforcement learning, which he says is an exciting field to drive machine learning forward. It’s got heavy, if not sole, implications around robotics, enabling the continuous and automated predictions of what must happen next, without a network feedback model. “That lets us almost to infinity create more self awareness, and constantly predict the next step without ever checking back if it’s the right step,” he says. “Google is heavily involved in this but there are pretty interesting business applications.”  Skytree’s work here is in its early phases, but Hack says it has seen some pretty good results.”

About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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