Boostlingo, a provider of SAAS-based interpreting technology solutions for global language access, announced its addition to the Zoom App Marketplace. Zoom Meetings that requires foreign language support will be able to add professional interpreters directly into their Zoom Meetings experience. Professional remote interpreters accustomed to using the Boostlingo platform can now be added on-demand into the Zoom environment. The Boostlingo platform supports a network of 8000+ certified interpreters and 300 spoken word languages and multiple sign languages. Boostlingo will enable you to:
Configure Zoom services for your Zoom accounts – Zoom‘s configuration policies allow you to create Zoom access for your clients.
Allow your client accounts to register their Zoom instance with Boost – Your client’s Zoom administrators can authenticate their account with Boostlingo, and all of your client’s supported users will be automatically enabled.
Boostlingo supports Zoom authentication – Boostlingo can support authentication at both the organizational level and at the individual user level.
Add VRI interpreters On Demand – Once the configuration is done, interpreters receive interpretation requests like they normally do and when answered on the web, they will be automatically joined into a Zoom session. Use your own interpreter team members or enable the Boostlingo Professional Interpreter Network (BPIN) to take the call for you.
Full back-end reporting – Boostlingo captures all the same important call data that a regular Boostlingo interpreting session collects.
SciBite, an Elsevier semantic technology company, announced the launch of SciBiteSearch, a scientific search and analytics platform that offers interrogation and analysis capabilities across unstructured and structured data, from public and proprietary sources. SciBiteSearch provides scientists with access to domain specific ontology and AI-powered search capabilities.
SciBiteSearch uses knowledge graphs to augment searches and deliver not only items relevant to the query but the structure and relationship between them. The addition of AI enables natural language understanding. SciBiteSearch can integrate data across a range of use cases including:
Unify multiple data sources into a single solution, designed for departments wanting their own tailored search tool. For example, combining public biomedical literature, clinical trials, and grants with proprietary data.
Incorporate full-text biomedical literature from publishers to better address researchers’ discovery needs. For example, users can load subscribed licensed data from partner publishers or content brokers.
Enable users to get accurate search results without the need to understand the complexities of Named Entity Recognition (NER), its underlying data structures, or the functions required to surface.
SciBiteSearch creates sophisticated query and assertion indices created using SciBite’s tools and ontologies. A streaming load API, connectors, and parsers for different sources and content types let it load and process content to make it searchable.
Lucid, provider of visual collaboration software, announced its virtual whiteboard, Lucidspark, is now available as an iOS app for tablet devices. Lucidspark is a place for distributed teams to brainstorm and collaborate together in real time. The launch of the Lucidspark tablet app will provide users with greater flexibility and accessibility across devices, helping teams to seamlessly align and more quickly move into action. With the Lucidspark app, users can access all the features of the browser experience, including:
Track individual contributions with assigned Collaborator Colors
Facilitate large and small group sessions with an infinite canvas and Breakout Boards
Automatically synthesize generated ideas into action plans with Gather and Sort
Share feedback through comments, mentions, and in-product chat
Brainstorm ideas in real time or asynchronously in a shared visual workspace
Leverage integrations with Jira, Microsoft Teams, and Slack to align teams across existing workflows
AI-powered learning platform, Docebo Inc. announced the launch of a multi-product learning technology suite. Previously, Docebo has focused on solving the problem of how organizations deliver training with its learning management system (LMS). With the launch of Docebo Learning Suite, Docebo will go beyond content delivery and address challenges across the entire learning lifecycle, from content creation and management to measuring learning impact and key business drivers. The launch of Docebo Learning Suite coincides with the launch of Docebo Shape, a content creation product built on AI. Developed internally, Docebo Shape enables businesses to bring more internal experts into their elearning content strategy by leveraging AI to create engaging learning content in minutes. Including Docebo Shape, the core products that come together to transform the company’s offering into a cohesive learning suite include:
Docebo Learn LMS, a Learning Management System that has been used by more than 2,000 customers;
Docebo Shape, a content creation product that uses AI to create elearning content in minutes;
Docebo Content, a library of thousands of off-the-shelf, mobile-ready learning courses, and;
Docebo Learning Impact, a data-driven tool that allows users to measure the effectiveness of their learning programs on their people and improve ROI.
In this issue we have recommended reading on creating a modern data workspace, enterprise search & AI, enterprise AI trends, no-code / low-code companies, Medium’s latest pivot, Facebook’s new publishing platform plan, and Wikipedia getting the big guys to pay.
Our content technology news weekly will be out Wednesday as usual.
Decoding the no-code / low-code startup universe and its players
No-code and low-code companies are sprouting up everywhere and whatever your initial impression has been, it’s time to consider their increasing utility and role in even complex application development environments. No-code / low-code can democratize and speed development by bringing business analysts and software developers closer together. Pietro Invernizzi and Ben Tossell have put together a very helpful resource looking at 145 companies with lots of detail and access to an Airtable spreadsheet. (Click the image for a version you can read)
Prukalpa Sankar generously and delightfully describes what she and her team learned from multiple attempts at creating a “modern data workspace”. Some of you will be familiar with the problems and lessons, but the approaches, tools used, and specific examples, will still be instructive.
Lack of transparency in AI is in general an unsolved problem even though there is obviously huge value in its application across domains. Martin White has some thoughts and advice on what this means for enterprise search.
Enterprise search presents a special challenge when it comes to AI transparency. Most other enterprise processes are close to linear in execution, so the impact of AI on performance can be relatively easily assessed and monitored. In the case of search, every query is a new workflow as it is dependent on the knowledge of the individual and the intent behind their search.
Lots of activity in the independent writing/publishing platform space recently: the Substack Pro controversy, Twitter‘s acquisition of Revue, Facebook’s announcement of a new platform for independent writers, and Medium’s latest pivot. None of these companies has figured out a sustainable business model, and none provide writers a safe long-term way to control their brand and content. They can in some cases be supplemental marketing and delivery channels if you own and control your content and publishing capability however. 🙂
Casey Newton reports on the changes at Medium…
Medium’s original journalism was meant to give shape and prestige to an essentially random collection of writing, gated behind a soft paywall that costs readers $5 a month or $50 a year. Eleven owned publications covered food, design, business, politics, and other subjects… But in the end, frustrated that Medium staff journalists’ stories weren’t converting more free readers to paid ones, Williams moved to wind down the experiment…
The Gilbane Advisor is curated by Frank Gilbane for content technology, computing, and digital experience professionals. The focus is on strategic technologies. We publish more or less twice a month except for August and December. We also publish curated content technology news weekly We do not sell or share personal data.
Arthur, the machine learning model monitoring company, released a suite of new tools and features for monitoring natural language processing models. Natural language processing is one of the most widely adopted machine learning technologies in the enterprise. But organizations often struggle to find the right tools to monitor these models.
The Arthur platform now offers advanced performance monitoring for NLP models, including tracking data drift, bias detection, and prediction-level model explainability. Monitoring NLP models for data drift involves comparing the statistical similarity of new input documents to the documents used to train the model. The Arthur platform automatically alerts you when your input documents or output text starts drifting beyond pre-configured thresholds.
Arthur now also offers bias detection capabilities for NLP models, allowing data science teams to uncover differences in accuracy and other performance measures across different subgroups to identify and fix unfair model bias. The platform also offers performance-bias analysis for tabular models. The Arthur team has also released a new set of explainability tools for NLP models, providing token-level insights for language models. Organizations can now understand which specific words within a document contributed most to a given prediction, even for black-box models.
Acquia announced updates to the Acquia Open Digital Experience Platform (DXP) to help marketers and developers architect a composable enterprise. These include the launch of Acquia Experience Platform, including Acquia CMS, a content management system (CMS) built on Drupal, and enhancements to Acquia Drupal Cloud and Acquia Marketing Cloud. New to Drupal Cloud, the Acquia Experience Platform includes Acquia CMS, Site Studio and Cloud IDE. All run on the Acquia Cloud Platform, a Kubernetes-native, autoscaling cloud platform for digital experiences:
Acquia CMS: a brand new CMS that includes capabilities from the Drupal community in a simple, out-of-the-box experience.
Acquia Site Studio: a no-code tool available within an enterprise CMS, allowing anyone to build websites without the need for technical expertise.
Acquia Cloud IDE: development environment for Drupal to expedite development timelines and reduce barriers to entry for Drupal development.
Acquia Marketing Cloud updates:
Unified analytics: Acquia Personalization now leverages the same analytics platform as Acquia CDP.
New machine learning models: New fuzzy clustering capabilities allow customers to be segmented into multiple machine learning clusters.
Reporting enhancements: New campaign performance reporting provides insights into the results from campaigns using CDP data.
Compliance workflows: A new consumer data erasure request UI and API make it more efficient to honor GDPR and CCPA deletion requests and confirm that deletion requests were handled properly.
DataStax announced a collaboration with IBM to deliver DataStax Enterprise, a scale-out NoSQL database built on the open source Apache Cassandra. DataStax Enterprise with IBM is now available to help enterprises build and manage modern data applications in hybrid and multi-cloud environments. DataStax Enterprise is an open, multi-cloud stack for modern data applications, a multi-model database incorporating transactions, search, analytics, and graph workloads all on the same platform. Building on the existing IBM Cloud Databases for DataStax product, DataStax Enterprise with IBM is designed to provide IBM customers with a hybrid cloud solution set that can be deployed on private clouds or on multiple public clouds to support applications requiring open source Apache Cassandra-based technology. DataStax Enterprise with IBM is designed to provide enterprises with:
The elimination of data sprawl with an operational data platform that helps enable organizations to move away from legacy systems
A lightning-fast data layer that can keep pace with AI and machine learning priorities
Extensibility to build an ideal tool and future-ready deployments
Global sales and support from IBM for worldwide customer deployments