NLP vs. NLU and the growing ability of machines to understand

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Humans want to speak to machines the same way they speak to each other -- in natural language, not the language... You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered. You have exceeded the maximum character limit.



Hewlett Packard Enterprise Enriches HPE IDOL Machine Learning Engine with Natural Language Processing - insideBIGDATA

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Hewlett Packard Enterprise (NYSE:HPE) announced a new release of its flagship unstructured data analytics engine, HPE IDOL, featuring advanced Natural Language Question Answering. The new version of HPE IDOL leverages advanced machine learning functionality to improve the effectiveness and contextual accuracy of human interactions with computers. Among the biggest challenges facing organizations trying to leverage Big Data is providing answers to users' questions in a natural, effective manner without cumbersome user interfaces or extensive training. Interactive voice assistants and online chatbots have recently simplified this process for consumers, however developers have had a difficult time adapting this approach to enterprise-class tasks due to the complexity and context of the questions, trustworthiness of the source, specificity of the information needed and accuracy of the answer. HPE Natural Language Question Answering deciphers the intent of a question and provides an answer or initates an action drawing from an organization's own structured and unstructured data assets in addition to available public data sources to provide actionable, trusted answers and business critical responses.


Trends And Developments Fuel NLP Market

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The large volumes of structured, as well as unstructured data generated at an unprecedented rate, has taken the industry by storm. Growing prevalence of Big Data in the IT sector has fueled the need for newer tools powered by Artificial Intelligence (AI) and Natural Language Processing (NLP).


Machine Learning: The Real Business Intelligence

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Business intelligence (BI) tools first appeared on the enterprise technology scene several decades ago, at birth clumsy and difficult to use but ultimately improving the flow of data through organizations from their operational systems to decision support. Data warehousing cut the time it took to access data, but even at their full maturity, BI systems could do little more than produce data and reports in a traditional organized way. But with the advancement of artificial intelligence and--more importantly--machine learning, true business intelligence is actually on its way to the enterprise. Such self-learning software will run on servers, be built into bots, drive decision-making systems, be embedded into cars or aircraft, and become the beating heart of mobile devices. Increased data-processing power, the availability of big data, the Internet of Things, and improvements in algorithms are converging to power this actual business intelligence.