June 2, 2016

IoT Seen Driving AI Adoption

George Leopold

While hardware vendors view it as another vehicle for selling more chips and servers that would allow enterprises to move processing power closer to data, the torrent of sensor and other information the Internet of Things (IoT) is expected to generate also is driving adoption of artificial intelligence technology, concludes a new survey of software developers.

Evans Data Corp., the market intelligence specialist based on Santa Cruz, Calif., released a survey of developers this week that placed IoT at the top of a list of technologies propelling AI adoption. The findings are somewhat surprising given the amount of development related to big data technologies. The developer survey nevertheless found that IoT topped the list of AI drivers that included machine learning, neural networks, deep learning and pattern recognition technologies.

“All the related disciplines that are commonly lumped together as artificial intelligence are being stimulated by the burgeoning growth of Internet of Things.” Evans Data CEO Janel Garvin noted in a statement releasing the survey findings. “These technologies are being incorporated very rapidly into the design and development process across a host of industries, and types of applications, but it’s IoT that is the strongest driver.”

Of all the technologies driving AI adoption, the market researcher added, IoT development was the only category eliciting a double-digit response as a target technology of choice.

Meanwhile, the Evans survey found that “fact extraction and reasoning,” image recognition, machine translation and prescriptive—as opposed to predictive—analytics were among the most frequently cited focus areas for developers working on machine learning applications.

Along with IoT adoption, the Evans survey of developers also tracks big data, database and platform adoption.

While the market researcher did not release details on individual companies, major vendors like IBM (NYSE: IBM) have been promoting cognitive computing platforms like Watson as primed for the coming era of connected networks of sensors and devices. For example, IBM is promoting its cognitive computing IoT as capable of handling the growing amounts of unstructured data the IoT is expected to generate.

Chris O’Conner, general manager of IBM’s IoT products, told a recent conference the company’s focus includes secure platform development to be used to organize and process IoT data. Using its Watson-based IoT platform as the receiving end for sensor data, work now focuses on developing applications that provide the capability to “create the lifecycle that’s so important for that IoT [sensor] device…. That device needs to be maintained, and the applications give you the ability to maintain that asset through its entire lifecycles,” O’Conner said.

Others cognitive computing specialists also are jumping into the IoT fray. For example, Digital Reasoning, an IBM Watson competitor that has helped the Defense Department track terrorists online, is expected to release an AI platform next week that would process users’ unstructured data at higher speeds and provide context. The company, which also has collaborated with financial markets to spot insider traders, touts its new system as leveraging cognitive computing to generate new sources of revenue.

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