As part of an effort to incorporate conversational interfaces within its Spark collaboration application portfolio, Cisco today announced its intention to acquire MindMeld for $127 million in cash. MindMeld has been driving the development of conversation interfaces based on a natural language engine powered by machine learning algorithms. Jason Goecke, Cisco vice president and general […]
As part of an effort to incorporate conversational interfaces within its Spark collaboration application portfolio, Cisco today announced its intention to acquire MindMeld for $127 million in cash.
MindMeld has been driving the development of conversation interfaces based on a natural language engine powered by machine learning algorithms. Jason Goecke, Cisco vice president and general manager responsible for collaboration applications, says Cisco will initially work to embed support for those conversational interfaces as a complement to the existing graphical interface. But over time, Cisco expects conversational interfaces to be the dominant interface end users will employ to access collaboration applications.
“Conversational interfaces over time will become the base expectation,” says Goecke.
Goecke says Cisco plans to both develop natural language capabilities in Spark in addition to continuing to work with IBM on integrating Cisco Spark with the IBM Watson cognitive computing platform.
MindMeld CEO Tim Tuttle says conversational interfaces driven by artificial intelligence are feasible now because of inexpensive compute resources in the cloud that make it possible to access massive amounts of data. That data is then used to train the AI models developed on top of machine learning algorithms that have been around for years.
“We’re now able to approach human-like accuracy,” says Tuttle.
Despite those advances, Tuttle says organizations shouldn’t expect to see AI system replacing the need for humans any time soon. While there will clearly be some economic impact, most of the usage of AI in the enterprise will be focused on specialized use cases for some time to come, if for no other reason than the amount of time and effort required to train and continuously update an AI application.
At the same time, Tuttle notes there is no going back now. Organizations of all sizes should be planning to not only interact more with AI-enabled applications, but also starting to give more thought to how those applications will fundamentally transform the way everyone in the organization performs their tasks.
Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.
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