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Category: Semantic technologies (Page 7 of 72)

Our coverage of semantic technologies goes back to the early 90s when search engines focused on searching structured data in databases were looking to provide support for searching unstructured or semi-structured data. This early Gilbane Report, Document Query Languages – Why is it so Hard to Ask a Simple Question?, analyses the challenge back then.

Semantic technology is a broad topic that includes all natural language processing, as well as the semantic web, linked data processing, and knowledge graphs.


Franz releases AllegroGraph 7.2

Franz Inc., announced AllegroGraph 7.2, which provides organizations with Data Fabric tools, including Graph Neural Networks, Graph Virtualization, Apache Spark graph analytics, and streaming graph pipelines to help data analytics professionals derive business value out of Knowledge Graphs. With AllegroGraph 7.2, users can create Graph Neural Networks (GNNs) and take advantage of an AI approach for Knowledge Graph enrichment via text processing for news classification, question and answer, search result organization, event prediction.

AllegroGraph 7.2 allows users to virtualize data as part of their AllegroGraph Knowledge Graph solution so the data remains in the source system and is linked and queried with other data stored directly in AllegroGraph. Any data source with a supported JDBC driver can be integrated into an AllegroGraph Knowledge Graph.

With AllegroGraph 7.2 and Apache Kafka, users can create a decision engine that produces real-time event streams based on computations that trigger specific actions. AllegroGraph accepts incoming events, executes instant queries and analytics on the new data and then stores events and results. Users can export data out of the Knowledge Graph and then perform graph analytics with Apache Spark. Users gain machine learning and SQL database solutions as well as GraphX and GraphFrames.

https://allegrograph.com/allegrograph-v7-2-now-available-gnn-virtual-graphs-spark-and-kafka/

Alation acquires Lyngo Analytics

Alation Inc., a provider of enterprise data intelligence solutions, announced the acquisition of Lyngo Analytics, a Los Altos, Calif.-based data insights company. The acquisition will elevate the business user experience within the data catalog, scale data intelligence, and help organizations drive data culture. Lyngo Analytics CEO and co-founder Jennifer Wu and CTO and co-founder Joachim Rahmfeld will join the company.

Lyngo Analytics uses a natural language interface to empower users to discover data and insights by asking questions using simple, familiar business terms. Alation an intelligent and user-friendly machine-learning data catalog. By integrating Lyngo Analytics’ artificial intelligence (AI) and machine-learning (ML) technology into its platform, Alation deepens its support for the non-technical user, converting natural language questions into SQL. Business users can acquire and develop data-driven insights from across an enterprise’s broad range of data sources. This means even data consumers without SQL expertise can ask questions in natural language and find data and insights without the support of data analysts.

https://www.alation.com/press-releases/alation-acquires-artifical-intelligence-vendor-lyngo-analytics/

CCC adds SciBite Semantic Search capability within RightFind Navigate

Copyright Clearance Center (CCC) announced the availability of Semantic Search within RightFind Navigate through a partnership with SciBite, a semantic technology organization. CCC also announced several features to RightFind Enterprise. 

Through semantic enrichment in RightFind Enterprise, now extended to RightFind Navigate, users can locate relevant data beyond just the specific words used, letting them find more relevant data associated with similar words and phrases. Established controlled vocabularies, such as SciBite’s VOCabs, which apply an explicit, unique meaning and description to scientific terms, provide comprehensive coverage of relevant terminology and the foundation necessary for an effective literature monitoring strategy. RightFind Navigate enables researchers to find relevant content easily through contextualized discovery that is based on machine learning and smart data. RightFind Navigate unifies searching across multiple licensed content sources, publicly available data, and internal proprietary content.

Features added to RightFind Enterprise include:

  • See available reuse rights in personal and shared libraries to minimize infringement risk without interrupting workflows
  • Order multiple articles in personal or shared libraries with one click
  • View the average rating from colleagues for an article in shared libraries, including the number of reviews
  • Easily view a large number of supplemental material files in one convenient list.

https://www.copyright.com/ccc-launches-semantic-search-capability-within-rightfind-navigate-through-partnership-with-scibite/

John Snow Labs announces free no-code natural language processing tools

John Snow Labs, a Healthcare AI and NLP company and developer of the Spark NLP library, announced that it will enable free access to its enterprise-grade Annotation Lab and NLP Server software for all users. The Annotation Lab, a data labeling and AI/ML solution for teams, enables users to annotate documents, images, and videos. The software automatically trains models using active learning and transfer learning. The project-based workflow helps users leverage real-time analytics on productivity, dataset bias, and inter-annotator agreement.

The enterprise solution also supports strong user management and role-based access, fully versioned and auditable completions, customizable workflows and tags, the ability to use custom models and embeddings, and integration with other tools using an API. Users can install the Annotation Lab within their own software infrastructure, including in air-gap networks, avoiding the need to share any data. There are no limits on the number of deployments, users, and customers. The NLP Server grants users access to thousands of pretrained out-of-the-box NLP models, enabling their use with no coding or data science experience necessary. Users can simply install the server as a single Docker container or on a cloud compute instance and access APIs.

https://www.johnsnowlabs.com/john-snow-labs-announces-free-enterprise-grade-no-code-natural-language-processing-tools-annotation-lab-and-nlp-server/

InMoment completes acquisition of Lexalytics

InMoment, a provider of Experience Improvement (XI) solutions, announced it has completed the acquisition of Lexalytics, a provider of cloud and on-premise natural language processing (NLP), and machine learning (ML) that transform structured data, text, and unstructured data from any source, into actionable intelligence. Lexalytics brings two decades of structured and unstructured data experience and cloud and on-premise text analytics solutions that go beyond surveys to include social, call center, voice, reviews, support tickets, chat logs, and many additional data channels.

This combination brings flexibility to organizations that require private, public, or hybrid cloud text analytics infrastructures, and unlocks new market opportunities with native text analytics across 24 languages and a large set of industry data sets. Together, InMoment solutions can be implemented in a variety of industries for social media monitoring, people analytics and voice of the employee, reputation management and voice of the customer, and regulatory compliance programs. Lexalytics employees, including its founder Jeff Catlin, will continue in their roles and will be key to accelerating InMoment’s structured and unstructured analytics leadership and initiatives.

https://inmoment.comhttps://www.lexalytics.com

OpenAI improves OpenAI Codex

OpenAI announced an improved version of OpenAI Codex, an AI system that translates natural language to code, and are releasing it through our API in private beta starting today. Codex is the model that powers GitHub Copilot, which we built and launched in partnership with GitHub a month ago. Proficient in more than a dozen programming languages, Codex can now interpret simple commands in natural language and execute them on the user’s behalf—making it possible to build a natural language interface to existing applications. We are now inviting businesses and developers to build on top of OpenAI Codex through our API.

OpenAI Codex is a descendant of GPT-3; its training data contains both natural language and billions of lines of source code from publicly available sources, including code in public GitHub repositories. OpenAI Codex is most capable in Python, but it is also proficient in over a dozen languages including JavaScript, Go, Perl, PHP, Ruby, Swift and TypeScript, and even Shell.

GPT-3’s main skill is generating natural language in response to a natural language prompt, meaning the only way it affects the world is through the mind of the reader. OpenAI Codex has much of the natural language understanding of GPT-3, but it produces working code—meaning you can issue commands in English to any piece of software with an API. We’re now making OpenAI Codex available in private beta via our API, and we are aiming to scale up as quickly as we can safely. During the initial period, OpenAI Codex will be offered for free.

https://openai.com/blog/openai-codex/

Lilt launches Quick Translate Machine Translation solution

Lilt, a language service and technology provider, announced the launch of Quick Translate, a product that provides access to high-quality machine translation in a secure environment. Quick Translate is part of the Lilt Platform and enables users to quickly translate content using a customized, human-in-the-loop trained neural machine translation engine. Use of publicly available, cloud-based solutions can entail dropping content directly into a non-secure machine translation engine, jeopardizing content security. With Quick Translate, users can enter source text or upload bundles of documents in a secure environment within the Lilt Platform. Lilt is Cyber Essentials and SOC-2 certified.

Trained by human linguists and human feedback, this engine continuously improves and learns, enabling it to generate higher quality translations. Quick Translate combines customized engines with Translation Memories, delivering content from a neural machine translation engine that has been trained on each customer’s unique content and translation preferences. Quick Translate provides an interface that is easy for non-technical and non-specialized stakeholders to use. Quick Translate enables individual users to easily batch translate multiple documents of the same source language (or languages) at once, providing quick access to time-sensitive information. 

https://lilt.com

LumenVox launches new speech recognition engine with transcription

LumenVox, a provider of speech and voice technology, announced its next-generation Automatic Speech Recognition (ASR) engine with transcription. The new engine, built on a foundation of artificial intelligence (AI) and deep machine learning (ML), helps deliver more accurate speech-enabled customer experiences.

The new LumenVox ASR engine uses a Deep Neural Network (DNN) architecture and its speech recognition processing capabilities. The new ASR engine accelerates the ability to add new languages and dialects and provides a modern toolset to expand the language model to serve a more diverse base of users. LumenVox enables customers to:

  • Future-proof speech technology: LumenVox’s single language model enables customers to quickly add new languages and non-native speaking accents.
  • Migrate legacy speech applications: Through the LumenVox Speech Tuner, customers can migrate most of their grammars and confidence values from legacy applications to the LumenVox ASR.
  • Deliver a seamless customer experience: By converting speech-to-text in real-time, the LumenVox ASR engine delivers high availability and accurate transcription with little or no latency.
  • Deploy in any environment: LumenVox provides customers with complete flexibility to deploy their speech applications in any environment: on-premise, multi-cloud, or a hybrid model.

https://www.lumenvox.com

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