IBM, the benchmark in artificial intelligence for businesses, is announcing new IBM Watson technologies designed to help organizations begin to identify, understand and analyze some of the biggest challenges of human language more clearly for better insights.
The new technologies represent the first commercialization of essential Natural Language Processing (NLP) capabilities present in IBM Research's Project Debater research project, an Artificial Intelligence (AI) system capable of debating with humans on complex topics , including advanced sentiment analysis, summarization, and advanced topic grouping capabilities.
In this way, companies can begin to analyze this language data with Watson APIs to gain a more holistic understanding of their operations. In addition, IBM is bringing technology from its research division, IBM Research, to understand business documents, such as PDFs and contracts, to add to its AI models as well.
"Language is a tool for expressing thoughts and opinions as well as a tool for obtaining information," comments Rob Thomas, General Manager of IBM Data and AI. "That's why we're taking technology from Project Debater and integrating it with Watson – to enable companies to capture, analyze and understand more of the human language and begin to transform the way they use the intellectual capital that is encoded in the data."
Analysis - Advanced Sentiment Analysis
IBM has improved sentiment analysis to be able to better identify and understand complicated word constructions, such as phrases and idioms, and so-called sentiment shifters, which are combinations of words that together take on a new meaning, such as the English expression " hardly helpful", in which 'hard' does not mean 'hard' but rather 'little'. This technology will be integrated into Watson Natural Language Understanding in English and by the end of the year in Portuguese. In addition, the company is announcing a new classification technology that will enable customers to create AI templates to more easily classify clauses in business documents such as purchasing contracts. Based on Project Debater's deep learning rating technology, new features can learn from a few hundred samples to make new ratings quickly and easily. The technology is expected to be added to Watson Discovery later this year.
Briefs — Summarization (summary)
This technology extracts textual data from various sources to provide users with a summary of what is being said and written about a specific topic. An early version of Summarization was used in The GRAMMYS this year to analyze more than 18 million articles, blogs and biographies to produce insights into hundreds of GRAMMY artists and celebrities. The data was used in the red carpet live stream, photos and videos on demand at www.grammy.com to provide fans with a broader context on the night's main topics. The technology is expected to be added to IBM Watson Natural Language Understanding by the end of the year.
Clustering — Advanced Topic Clustering
Based on insights gained from Project Debater, new topic grouping techniques will allow users to "group" incoming data to create meaningful "topics" of related information for analysis. The technique, which is expected to be integrated into Watson Discovery later this year, will also allow experts to customize and tweak topics to reflect the language of specific companies or industries, such as insurance, healthcare and manufacturing.
IBM is a reference in NLP, developing technologies that allow computer systems to learn, analyze and understand human language – including feelings, dialects, intonations, among others, with greater precision and speed. Through Watson, IBM brought to market its NLP technology – much of which was born in the research division, IBM Research. Products such as: Watson Discovery, for understanding documents; the IBM Watson Assistant, for virtual assistants; and Watson Natural Language Understanding for advanced sentiment analysis all have NLP.
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