IBM advances Watson's ability to understand business language

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IBM advances Watson's ability to understand business language

For example, a new advanced sentiment analysis feature is defined to identify and analyse idioms

Wednesday March 11, 2020 3:08 PM, IANS

Bengaluru: Tech giant IBM on Wednesday said it is adding several new features to its Artificial Intelligence (AI) platform Watson which are designed to help organisations begin identifying, understanding and analysing some of the most challenging aspects of the English language with more clarity, for greater insights.

The new technologies represent the first commercialisation of key Natural Language Processing (NLP) capabilities to come from IBM Research's Project Debater -- an AI system capable of debating humans on complex topics.

For example, a new advanced sentiment analysis feature is defined to identify and analyse idioms and colloquialisms for the first time.

Phrases, like 'hardly helpful,' or 'hot under the collar,' have been challenging for AI systems because they are difficult for algorithms to spot.

With advanced sentiment analysis, businesses can begin analysing such language data with Watson application programming interface (APIs) for a more holistic understanding of their operations.

Further, IBM is bringing technology from IBM Research for understanding business documents such as PDF's and contracts, to also add to their AI models.

"Language is a tool for expressing thought and opinion, as much as it is a tool for information," Rob Thomas, General Manager, IBM Data and AI, said in a statement.

IBM also announcing that it plans to integrate Project Debater technologies into Watson throughout the year, with a focus on advancing clients' ability to exploit natural language.

"This is why we're harvesting technology from Project Debater and integrating it into Watson - to enable businesses to capture, analyze, and understand more from human language and start to transform how they utilise intellectual capital that's codified in data," Thomas said.

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