Category Archives: Natural Language Processing

Recent Advances in Google Translate

Posted on December 20, 2020 by decisionmanagementcommunity

Google Translate was introduced in 2016 and it enabled great improvements to the quality of translation for over 100 languages since then. In this post Google Research describes how recent advances in machine learning drive improvements to automated translation. Link

Posted in Artificial Intelligence, Languages, Machine Learning, Natural Language Processing | Leave a comment

GPT-3, the latest evolution in language technology – What is the big deal?

Posted on September 28, 2020 by decisionmanagementcommunity

Over the summer 2020, the latest language model from OpenAI, called GPT-3, created a lot of buzz around the internet. Both within the AI community and outside people shared links to numerous examples on what GPT-3 could do, ranging from … Continue reading →

Posted in Artificial Intelligence, Human-Machine Interaction, Knowledge Representation, Languages, Natural Language Processing | Leave a comment

Giving GPT-3 a Turing Test

Posted on July 22, 2020 by decisionmanagementcommunity

GPT-3 is a general language model, trained on a large amount of uncategorized text from the internet. It isn’t specific to a conversational format, and it isn’t trained to answer any specific type of question. The only thing it does … Continue reading →

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Climbing Towards Natural Language Understanding

Posted on July 12, 2020 by decisionmanagementcommunity

This paper “Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data” won the “Best Theme Award” at the ACL2020 AI conference.  “… in contrast to some current hype, meaning cannot be learned from form alone. This … Continue reading →

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The latest NLP revolution

Posted on June 17, 2020 by decisionmanagementcommunity

Read an interview with Noam Shazeer who helped spark the latest NLP revolution. “He developed the multi-headed self-attention mechanism described in “Attention Is All You Need,” the 2017 paper that introduced the transformer network. That architecture became the foundation of … Continue reading →

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Extracting Data from Templatic Documents

Posted on June 12, 2020 by decisionmanagementcommunity

In this article Google researches describe a novel approach using representation learning for tackling the problem of extracting structured information from templatic documents, such as receipts, bills, or insurance quotes. They “propose an extraction system that uses knowledge of the … Continue reading →

Posted in Human-Machine Interaction, Machine Learning, Natural Language Processing | Leave a comment

More Efficient NLP Model Pre-training

Posted on March 10, 2020 by decisionmanagementcommunity

“Recent advances in language pre-training have led to substantial gains in the field of natural language processing, with state-of-the-art models such as BERT, RoBERTa, XLNet, ALBERT, and T5, among many others. These methods, though they differ in design, share the same idea of leveraging … Continue reading →

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“Do you love me?”​ How can a computer deal with real sentences?

Posted on January 22, 2020 by decisionmanagementcommunity

Prof. Roger Shank just published an article with this title. He writes: “My career was in Natural Language Processing which is only one part of AI. I spent my life trying to figure out ways that computers could understand sentences … Continue reading →

Posted in Artificial Intelligence, Natural Language Processing | 1 Comment

Breakthrough in Google Search

Posted on October 28, 2019 by decisionmanagementcommunity

On Oct. 25 Pandu Nayak, Google Fellow and Vice President of Search, published an article “Understanding Searches Better Than Ever Before“.  “Search is about understanding language. The latest advancements from our research team in the science of language understanding–made possible … Continue reading →

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Knowledge Specification and Querying

Posted on July 25, 2019 by jacobfeldman

Our colleagues from the Rules and Reasoning community have just reported interesting results. They built a system that achieves 100% accuracy on an extensive test suite of movie-related questions, e.g. “Who appears in a Steven Spielberg directed film?”. Their approach … Continue reading →

Posted in Natural Language Processing, Reasoning, Semantic Web | Leave a comment