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Wednesday, July 12, 2017
IBM Revamps Unit Around Watson Artificial Intelligence, Microsoft Creates New AI Lab

IBM and Microsoft are embracing Artificial Intelligence to enhance their services and develop learning systems. IBM is revamping its Global Technology Services division while Microsoft is setting up a new research lab.

The new new AI-capability in IBM's Global Technology Services division will help IBM's customers minimize disruptions such as server outages or switching malfunctions by predicting problems before they occur and automatically taking corrective action.

The product offering is powered by IBM's Watson cognitive computing platform and could help the company to maintain its market share in IT network infrastructure management.

Analysts of networking systems could now be automatically alerted to a slowdown and presented with options to choose from to get the network running smoothly again. IBM's system also has the ability to understand IT helpdesk queries using natural language.

IBM trained its Watson-based IT infrastructure platform by feeding it data from more than 10 million past incidents. The system is now handling more than 800,000 incidents a month.

The AI-based analytics run on IBM's cloud computing platform, but the underlying data is retained by the customer on whatever network architecture they currently use.

IBM is facing competition from rivals including Microsoft, Cisco Systems and Alphabet's Google, who have also begun emphasizing artificial intelligence and automation in products.

Microsoft has announced a reorganization of its global salesforce, in part to focus on selling AI-enabled products and services. The company is setting up a new research lab focused on artificial intelligence with the goal of creating more general-purpose learning systems.

The "Microsoft Research AI" lab will be based at the company's headquarters in Redmond, Washington, and involve more than 100 scientists from across various sub-fields of artificial intelligence research, including perception, learning, reasoning and natural language processing.

The goal is to combine these disciplines to work toward more general artificial intelligence, meaning a single system that can tackle a wide-range of tasks and problems.

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