The AI (artificial intelligence) underpinning IBM Watson has undergone several recent advancements in understanding colloquial and business terms in order to improve its analysis, briefing and clustering abilities.
The advancements have resulted in Advanced Sentiment Analysis, Summarisation and Advanced Topic Clustering.
Advanced Sentiment Analysis allows for Watson to understand idioms such as “hardly helpful” or “let’s rip up this plan”, as well as adapting technology from IBM Research to understand business documents like PDF files and procurement contracts contracts.
Meanwhile, Summarisation is able to look at textual data to generate summaries and Advanced Topic Clustering can cluster incoming data to create relevant topics, which can then be analysed.
All three technologies will be added to commercial applications of Watson technology throughout 2020, with Advanced Sentiment Analysis to be added to Watson Natural Language Understanding later this month and Summarisation to be added later this year.
Meanwhile, Advanced Topic Clustering and Advanced Sentiment Analysis’ business document analysis functionality will be added to Watson Discovery later this year.
"Language is a tool for expressing thought and opinion, as much as it is a tool for information,” said Rob Thomas, general manager of Data and AI at IBM. “This is why we’re harvesting technology from Project Debater and integrating it into Watson – to enable businesses to capture, analyse, and understand more from human language and start to transform how they utilise intellectual capital codified in data."
These advancements stem from the natural language processing (NLP) capabilities of IBM Research’s Project Debater, with the company claiming it’s the only AI system able to debate humans on complex issues.