Category: Computing & data (Page 60 of 92)

Expert.ai announced the availability of commercial options for its NL API. Powered by expert.ai technology, which mimics the human ability to understand language and complex textual information, the expert.ai NL API provides advanced linguistic analysis out of the box, so developers and data scientists can reduce development costs and increase productivity while optimizing their natural language processing (NLP) applications. The introduction of the commercial offering builds upon the previously released freemium model to give users the ability to expand their usage of the expert.ai NL API and scale their apps, either standalone or embedded into an enterprise’s existing AI processes, by supporting larger volumes of data.

Expert.ai NL API features include linguistic analysis tools, embedded taxonomies for classification, and sentiment analysis. By resolving complexity associated with language, it streamlines the development of apps that rely on and process natural language content and unstructured data (contracts, internal database, news articles, academic papers, customer service emails, insurance policies, medical reports etc.) that typically is either not analyzed because it is inefficient or is analyzed manually which is expensive.

https://www.expert.ai/products/nl-api/, https://policies.expert.ai/nlapi/pricing/

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Microsoft announced that DeBERTa now surpasses humans on the SuperGLUE benchmark. SuperGLUE is a challenging benchmarks for evaluating NLU models. The benchmark consists of a wide range of NLU tasks, including question answering, natural language inference, co-reference resolution, word sense disambiguation, and others. Top research teams around the world have been developing large-scale pretrained language models (PLMs) that have driven performance improvement on the SuperGLUE benchmark. Microsoft recently updated the DeBERTa model by training a larger version that consists of 48 Transformer layers with 1.5 billion parameters. The performance boost makes the single DeBERTa model surpass the human performance on SuperGLUE for the first time in terms of macro-average score (89.9 versus 89.8), and the ensemble DeBERTa model sits atop the SuperGLUE benchmark rankings, outperforming the human baseline by a decent margin (90.3 versus 89.8). The model also sits at the top of the GLUE benchmark rankings with a macro-average score of 90.8.

Microsoft will release the 1.5-billion-parameter DeBERTa model and the source code to the public. In addition, DeBERTa is being integrated into the next version of the Microsoft Turing natural language representation model (Turing NLRv4). Our Turing models converge all language innovation across Microsoft, and they are then trained at large scale to support products like Bing, Office, Dynamics, and Azure Cognitive Services.

https://www.microsoft.com/en-us/research/blog/microsoft-deberta-surpasses-human-performance-on-the-superglue-benchmark/

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Hitachi Solutions, Ltd. announced the release of “Business Efficiency Solution by Natural Language Processing (NLP) AI.” It combines Hitachi and Allganize’s expertise in Artificial Intelligence (AI) to provide business automation solutions, such as Robotic Process Automation (RPA), NLP and cognitive agents. Allganize’s AI technology is able to extract structured knowledge from millions of documents and other content sources. Hitachi’s “Katsubun Intellectual Information Mining” provides a set of tools and techniques to identify specific ways to improve business operations. The solution features:

• Katsubun Intellectual Information Mining analyzes clients’ operational processes and enables them to identify bottlenecks for process improvement.
• Alli AnswerBot streamlines customer service and automates business processes.
• Cognitive Search enriches and extracts structured knowledge from unstructured data sources to make content more searchable.
• Named Entity Recognition (NER) locates and classifies named entities such as brand names, people, product names, purchase order and account information from unstructured data sources.
• Review Analysis automatically converts opinions such as user feedback and reviews into measurable data for analysis.
• Text Classification assigns custom predefined categories to free-text for managing content.
• Sentiment Analysis, emotional AI that categorizes text by emotional state such as happy, angry or sad.

https://www.hitachi-solutions.co.jp/allganize/, https://allganize.ai

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