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IBM launches Watson tools for Multiple Sectors

YORKTOWN HEIGHTS, NY

YORKTOWN HEIGHTS, NY – JANUARY 13: A general view of IBM’s ‘Watson’ computing system at a press conference to discuss the upcoming Man V. Machine “Jeopardy!” competition at the IBM T.J. Watson Research Center on January 13, 2011 in Yorktown Heights, New York. (Photo by Ben Hider/Getty Images)

IBM plans to outline its pre-packaged Watson tools for various industries like that of agriculture, customer service, human resources, manufacturing, and marketing by implementing the growing trend in both Artificial Intelligence and Machine Learning where the technology providers are enabled for easier access in implementing the options without the help of data scientists.
Here IBM Watson pack will be at various levels of release that take best practices and training knowledge from various IBM engagements where its platform for Agriculture is generally available and now they are integrated its weather data as well as the Internet of to establish endpoints in agriculture and images in implementing “predictive view of a farm.”

IBM’s Pre-training Watson for Industries and Functional Areas:
• IBM released a customer service Watson pack in collaboration with Deluxe Corp where this customer service app aims to bring relevant information about a caller in real-time for the service agents with minimum training.

• In the Human Resources sector, the Watson tools will study and identify the background of top performing employees from various backgrounds and also aims to find similar traits among other applicants.

• Watson Supply Chain Insights is readily available to aim at weather data, traffic reports and enhance regulatory changes to enterprises to improvise the supply chain mechanism.

• Watson Toolsets that is based on IoT analytics are being used for manufacturing industrial equipment with a focus on product inspection, productivity, skills gaps, and material costs as well as downtime and defects.

• IBM IoT builds insights that will examine data from commercial properties to minimize energy costs and gauge occupancy trends.

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