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Automattic invests in open decentralized comms ecosystem Matrix

May 21, 2020 /

Automattic, the open source force behind WordPress, WooCommerce, Longreads, Simplenote and Tumblr, has made a $4.6M strategic investment into New Vector — the creators of an open, decentralized communications standard called Matrix. New Vector also developed a Slack rival (Riot) which runs on Matrix. Matrix is an open source project that publishes the Matrix open standard for secure, decentralised, real-time communication, and its Apache licensed  reference implementations.

New Vector’s decentralized tech powers instant messaging for a number of government users, including France — which forked Riot to launch a messaging app last year (Tchap) — and Germany, which just announced its armed forces will be adopting Matrix as the backbone for all internal comms; as well as for KDE, Mozilla, RedHat and Wikimedia, and others.

https://vector.im, https://matrix.org, h/t: Techcrunch

 

Luminoso announces enhancements to open data semantic network

May 20, 2020 /

Luminoso, who turn unstructured text data into business-critical insights, announced the newest features of ConceptNet, an open data semantic network whose development is led by Luminoso Chief Science Officer Robyn Speer. ConceptNet originated from MIT Media Lab’s Open Mind Common Sense project more than two decades ago, and the semantic network is now used in AI applications around the world. ConceptNet is cited in more than 700 AI papers in Google Scholar, and its API is queried over 500,000 times per day from more than 1,000 unique IPs. Luminoso has incorporated ConceptNet into its proprietary natural language understanding technology, QuickLearn 2.0. ConceptNet 5.8 features:

Continuous deployment: ConceptNet is now set up with continuous integration using Jenkins and deployment using AWS Terraform, which will make it faster to deploy new versions of the semantic network and easier for others to set up mirrors of the API.

Additional curation of crowd-sourced data: ConceptNet’s developers have filtered entries from Wiktionary that were introducing hateful terminology to ConceptNet without its context. This is part of their ongoing effort to prevent human biases and prejudices from being built into language models. ConceptNet 5.8 has also updated its Wiktionary parser so that it can handle updated versions of the French and German-language Wiktionary projects.

HTTPS support: Developers can now reach ConceptNet’s website and API over HTTPS, improving data transfer security for applications using ConceptNet.

http://blog.conceptnet.io/posts/2020/conceptnet-58/, https://luminoso.com/how-it-works

Microsoft open sources Fluid Framework – announces Fluid Workspaces and Fluid Components for Office 365

May 20, 2020 /

Microsoft introduced the first way for end users to experience the Fluid Framework in Microsoft 365 with the upcoming availability in preview of Fluid Workspaces and Fluid Components. Fluid Workspaces and Components work like the web to bring the right level of context and connection as well as seamlessly capture follow-ups in-line and edit action items with an entire team. Fluid Components and Fluid Workspaces will become available in more places over time. This initial public preview includes basic text, tables, lists, agendas and action items. These Fluid components will be available for creation in Outlook for the web and Office.com. Microsoft also announced the Fluid Framework will be made open source and hosted as a repository available on GitHub in the next month, allowing developers and creators to use infrastructure from Fluid Framework in their own applications. Coupled with the release of additional developer documentation and tooling, developers can work alongside Microsoft to create and evolve Fluid Framework as it is developed. Developers can take advantage of JavaScript APIs that give them access to collaborative, shared data structures which can be used to power collaborative experiences. They also can create Fluid components — elements that can be reused within Microsoft 365 and across applications.

https://www.microsoft.com/en-us/microsoft-365/blog/2020/05/19/microsoft-teams-fluid-framework-new-microsoft-365/

Information Model
Gilbane Advisor 6-9-21 — stacks & aggregation, JavaScript for data, news

Hugging Face dives into machine translation with release of 1,000 models

May 19, 2020 /

Hugging Face is taking its first step into machine translation this week with the release of more than 1,000 models. Researchers trained models using unsupervised learning and the Open Parallel Corpus (OPUS). OPUS is a project undertaken by the University of Helsinki and global partners to gather and open-source a wide variety of language data sets, particularly for low resource languages. Low resource languages are those with less training data than more commonly used languages like English.

Models trained with OPUS data now make up the majority of models provided by Hugging Face and the University of Helsinki’s Language Technology and Research Group the largest contributing organization. Before this week, Hugging Face was best known for enabling easy access to state-of-the-art language models and language generation models, like Google’s BERT, which can predict the next characters, words, or sentences that will appear in text. The Hugging Face Transformers library for Python includes pretrained versions of advanced and state-of-the-art NLP models like versions of Google AI’s BERT and XLNet, Facebook AI’s RoBERTa, and OpenAI’s GPT-2.

https://huggingface.co h/t: VentureBeat

Progress updates Sitefinity 13 digital experience platform

May 19, 2020 /

Progress announced the release of Progress Sitefinity 13 Digital Experience Platform (DXP). The new release includes: 

  • A new productivity environment to manage digital assets and classify content in a consistent and resource-efficient manner
  • The ability to control the look and feel of the presentation layer while delivering content to a myriad of channels. This is possible through the new page layout service that decouples content from presentation when distributed to external channels.
  • Personalization based on custom tags such as title, campaign source or other attributes as well as consistent, personalized experiences for returning visitors, regardless of the initial touch point.
  • Customer journey and online touchpoint monitoring based on machine learning, enabling marketers to receive proactive touchpoint alerts in order to spot new opportunities and improve the ROI of marketing campaigns.
  • Data-driven analytics to measure the performance of content with a comprehensive view of all personalization initiatives as well as the ability to export data directly to Google Data Studio for expanded data analysis options.

https://www.progress.com/sitefinity-cms

SDL announces integration of translation management with Veeva Vault RIM

May 19, 2020 /

SDL announced it has advanced its partnership level with Veeva Systems (“Veeva”), supporting the product life cycle for pharmaceutical and Life Sciences companies. SDL Translation Management System (TMS) is integrated with the Veeva Vault RIM Suite, a cloud-based Regulatory Information Management (RIM) system. In the biopharmaceutical sector, companies must react quickly to complex regulatory updates across multiple regions. The combination of SDL’s network of in-house certified medical translators with SDL’s translation management technology provides an integrated set of translation capabilities within Veeva Vault RIM. This integration enables Veeva Vault RIM customers to automate multilingual tasks relating to regulatory document submissions, engagement with health authorities and product registration. SDL joined Veeva Systems’ Technology Partner Program in 2018. https://www.sdl.com

Amazon releases Kendra to solve enterprise search with AI and machine learning

May 11, 2020 /

Amazon Web Services announced the general availability of Amazon Kendra, an enterprise search service. Amazon Kendra uses machine learning to enable organizations to index all of their internal data sources, make that data searchable, and allow users to get precise answers to natural language queries. When users ask a question, Amazon Kendra uses finely tuned machine learning algorithms to understand the context and return the most relevant results, whether that be a precise answer or an entire document. For example, businesses can use Amazon Kendra to search internal documents spread across portals and wikis, research organizations can create a searchable archive of experiments and notes, and contact centers can use Amazon Kendra to find the right answer to customer questions across the complete library of support documentation. Amazon Kendra requires no machine learning expertise and can be set up completely within the AWS Management Console. Amazon Kendra provides a wide range of native cloud and on-premises connectors to popular data sources such as SharePoint, OneDrive, Salesforce, ServiceNow, Amazon Simple Storage Service, and relational databases.

https://aws.amazon.com/kendra/ ht: Techcrunch

Adobe and ServiceNow announce global availability of integration

May 5, 2020 /

Adobe and ServiceNow announced the availability of its partnership integration connecting data from Adobe Experience Platform and ServiceNow’s Customer Service Management workflow product to enable more seamless, connected customer experiences. Connecting Adobe Experience Platform, its Customer Experience Management (CXM) platform, and ServiceNow’s Customer Service Management product provides brands with a more complete view of the customer. Through this integration, Adobe and ServiceNow joint customers can:

  • Establish Context to Drive Brand Loyalty
    Enterprises are often challenged by navigating internal silos of data pertaining to interactions with their customers. This integration creates data workflows that removes those barriers and connects marketing and customer service organizations.
  • Gain Deeper Insights for Personalization
    Great experiences are built on the understanding of a customer’s journey. Customers can streamline work between teams by aggregating data during the “evaluate” and “purchase” touchpoints, and capture service interactions to ultimately build rich, real-time customer profiles.
  • Improve Customer Experiences
    A seamless customer experience allows for anticipating needs before they arise. With ServiceNow, organizations will understand which products or services the customer owns and uses, allowing organizations to drive towards greater personalization.

www.adobe.com, www.servicenow.com

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