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Why "Augmented Intelligence" is Trending

by Phoebe Allen on July 6, 2018

What is Augmented Intelligence and why has it become a business buzzword?

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2018 finds many sectors making a vernacular shift away from Artificial Intelligence (AI), but not merely to allay people’s growing trepidation surrounding the term. Humans remain necessary for AI to be effective. Unsupervised machine learning is still prohibitively complex and expensive, and supervised machine learning can only go so far. AI has other limitations; Natural Language Generation (NLG) technologies are not being employed to write novels or legislation, but rather to summarize complex data sets or churn-out rote descriptions for websites. At present, AI largely revolves around its capacity to assist human intelligence rather than replace it. As such, the spreading prevalence of the term “Augmented Intelligence” makes sense.

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Topics: augmented intelligence, Natural Language Processing, Natural Language Generation, Machine Learning, Artificial Intelligence

Intuition and the Limits of Natural Language Generation

by Phoebe Allen on June 8, 2018

Natural Language Generation lacks the insight that participation provides

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Natural Language Generation (NLG) is a software process that converts complex systems (data) into text (prose) that is comprehensible to humans. NLG is a relatively new use for Artificial Intelligence (AI) that, since its advent, has helped accelerate operations across multiple sectors by quickly translating and summarizing datasets that would otherwise take thousands of working hours to interpret.

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Topics: augmented intelligence, Natural Language Processing, Natural Language Generation, Machine Learning, Artificial Intelligence

Relationships Define Natural Language Processing

by Leonard Hancock on March 13, 2017

Vectors, ontologies, embeddings and sentiment analysis: how relationships between words are the foundation of NLP
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Human language follows unexpected patterns. Varied forms of syntax and metaphor, together with context and repetition, make classification challenging for both humans and machines. Manual classification of unstructured linguistic data by human curators can be valuable, but without technological assistance, is time consuming and potentially rife with errors. When such “natural language” data is left untouched it is less usable. Enterprises are faced with the challenge of transforming huge amounts of this raw data into actionable intelligence.

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Topics: Natural Language Processing, AI, Machine Learning, Ontologies, Sentiment Analysis

A Breakdown of Key Concepts Shaping Business Information Technology

by Kari Walgran on September 23, 2016

Artificial Intelligence. Machine Learning. Natural Language Processing.

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Artificial intelligence. Machine learning. Natural language processing. Once the stuff of science fiction, these high-tech unions of human intelligence and computing capabilities, of algorithms and efficiencies, have already transformed business information technology, and they are poised for even greater growth in the future.

With drastic changes in information processing compounding the ever-growing volumes of information being produced, it is critical for digital strategists to develop a working knowledge of key concepts and terminology.

Read on for a glossary of key terms, along with links to further reading and resources.

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Topics: Natural Language Processing, Machine Learning, Artifical Intelligence, Business Information Technology

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