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Can Global Semantic Context Improve Neural Language Models? from @Apple's Machine Learning Journal

Can Global Semantic Context Improve Neural Language Models? from @Apple's Machine Learning Journal | Language Tech Market News | Scoop.it

From Apple's Machine Learning Journal Vol. 1, Issue 11 ∙ September 2018
by Frameworks Natural Language Processing Team
Entering text on your iPhone, discovering news articles you might enjoy, finding out answers to questions you may have, and many other language-related tasks depend upon robust natural language processing (NLP) models. Word embeddings are a category of NLP models that mathematically map words to numerical vectors. This capability makes it fairly straightforward to find numerically similar vectors or vector clusters, then reverse the mapping to get relevant linguistic information. Such models are at the heart of familiar apps like News, search, Siri, keyboards, and Maps.

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@Gamalon Aims to Help Interpret Customer Messages by Learning Ideas, Not Just Language

@Gamalon Aims to Help Interpret Customer Messages by Learning Ideas, Not Just Language | Language Tech Market News | Scoop.it

Gamalon’s (US) so-called “idea learning” platform is all about serving companies with “accurate, editable, and explainable” processing capabilities for inbound customer messages and other forms of unstructured data. The company said that its platform can now process natural language and then explain the ideas. “We’re creating an AI model by essentially just talking to it — and Gamalon is figuring out what ideas, and the structure of those ideas, are present, and then automatically creating a model that can then be used on new utterances and messages." 

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Announcing AVA: A Finely Labeled Video Dataset for Human Action Understanding

Announcing AVA: A Finely Labeled Video Dataset for Human Action Understanding | Language Tech Market News | Scoop.it
In order to facilitate further research into human action recognition, we have released AVA, coined from “atomic visual actions”, a new dataset that provides multiple action labels for each person in extended video sequences. AVA consists of URLs for publicly available videos from YouTube, annotated with a set of 80 atomic actions (e.g. “walk”, “kick (an object)”, “shake hands”) that are spatial-temporally localized, resulting in 57.6k video segments, 96k labeled humans performing actions, and a total of 210k action labels.
LT-Innovate's insight:

Facebook for one is truing to use images to teach robots words for things. Next may come words for actions.

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Semantics-driven Photonics Portal for the UK

Semantics-driven Photonics Portal for the UK | Language Tech Market News | Scoop.it

This is a knowledge-driven portal that makes use of semantic web technologies to draw together everyhting about UK photonics research capabilities.

phw@lt-innovate.eu's insight:

Good example of a vertical domain that can leverage semantic tech to collect and organise a useable knowledge base.

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@PwC Partners @Cortical.io in Semantic #NLU Applications

PwC Germany and European tech company Cortical.io have signed a joint business relationship agreement whereby PwC becomes partner of Cortical.io and develops natural language understanding solutions using Cortical.io’s technology.
Cortical.io has developed a unique natural language understanding technology that its says solves many challenges related to big text data. The novel, meaning-based algorithm is based on Cortical.io’s patented Semantic Folding methodology.

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Web 3.0 Manifesto on Semantic Technologies in Products and Services

The semantic wave embraces four stages of internet growth. Web 1.0, was about connecting information and getting on the net. Web 2.0 is about connecting people — putting the “I” in user interface, and the “we” into webs of social participation. The next stage, Web 3.0, is starting now. It is about representing meanings, connecting knowledge, and putting these to work in ways that make our experience of internet more relevant, useful, and enjoyable. Web 4.0 will come later. It is about connecting intelligences in a ubiquitous web where both people and things reason and communicate together.

LT-Innovate's insight:

A paying report that sounds déjà vu., especially when there's no overt reference to AI in the marketing blurb.  

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Springer Nature SciGraph Provides Semantic Support for Open Science

Springer Nature is giving a boost to researchers with the launch of its new Springer Nature SciGraph. The new Linked Open Data (LOD) platform aggregates data sources from Springer Nature and cooperating partners, making it easier to analyze information related to Springer Nature publications. 

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