Expert.ai today launched a new user Community designed to serve the AI natural language understanding (NLU) and natural language processing (NLP) software ecosystem using the expert.ai NL technology, products and API. By sharing thought leadership, best practices, training material, and more, the Community is a space for developers, data scientists, knowledge engineers, computational linguists, AI enthusiasts and experts to learn more about the NL capabilities from the AI tools provided by expert.ai. Members can leverage the Community to gain new insights and knowledge, get advice from technical experts to overcome NL challenges and expand skills, interact with peers to ask support and share acquired expertise. To learn more or join the expert.ai Natural Language Community, visit
Category: Computing & data (Page 56 of 92)
Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.
Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.
Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.
ThoughtSpot, provider of enterprise search & AI-driven analytics, announced a new investment from Snowflake Ventures, the ventures arm of Snowflake. This investment reflects the continued partnership and success joint customers are able to achieve with Thoughtspot’s AI-driven analytics platform powered by Snowflake’s Data Cloud. Organizations that have adopted the Data Cloud in combination with search and AI-driven analytics move beyond traditional static dashboards and improve how they leverage data. With Snowflake and ThoughtSpot, companies are able to empower every employee with granular insights that create bespoke, personalized experiences. Joint customers will benefit from:
- Accelerated product innovation. ThoughtSpot’s search and AI-driven analytics platform will continue to integrate and leverage the latest Snowflake platform features that enable joint customers to further democratize the use of data and unlock meaningful business insights.
- Increased ROI from cloud migrations. With ThoughtSpot and Snowflake, companies can quickly get their data into the cloud, identify and move analytics use cases into production, and scale these to any employee in their business.
- Continued joint go to market. ThoughtSpot and Snowflake will work together to help companies experience the combination of their solutions through jointly held virtual events, workshops, and a free trial of ThoughtSpot.
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TELUS International announced the completion of its previously announced acquisition of a 100% interest in Lionbridge AI, following the clearance of the acquisition by the Committee on Foreign Investment in the United States (CFIUS). Lionbridge AI is a global provider of scalable data annotation services for text, images, videos, and audio. The company sources multilingual training data in more than 300 languages and dialects to build premium, ground truth data for some of the world’s largest technology companies in social media, search, retail and mobile. Lionbridge AI has also developed a proprietary data annotation platform that is used in combination with a crowdsourced community of one million professional annotators, qualified linguists and in-country language speakers across six continents.
At their Ignite conference Microsoft introduced Microsoft Mesh, a new mixed-reality platform powered by Azure that allows people in different physical locations to join collaborative and shared holographic experiences on many kinds of devices. Microsoft Mesh will also enable geographically distributed teams to have more collaborative meetings, conduct virtual design sessions, assist others, learn together and host virtual social meetups. People will initially be able to express themselves as avatars in these shared virtual experiences and over time use holoportation to project themselves as their most lifelike, photorealistic selves, the company said.
With Microsoft Mesh-enabled applications, designers or engineers who work with 3D physical models — anything from bicycles to high-end furniture to jet engines to new sports stadiums — could appear as themselves in a shared virtual space to collaborate and iterate on holographic models, regardless of their physical location.
At Ignite, Microsoft also announced two apps built on the Microsoft Mesh platform. Those include a preview of the Microsoft Mesh app for HoloLens, which allows team members to remotely collaborate and is available for download. Customers can also request access to a new version of Mesh-enabled AltspaceVR, which will allow companies to hold meetings and work gatherings in virtual reality with enterprise-grade security features including secure sign-ins, session management and privacy compliance.
https://news.microsoft.com/innovation-stories/microsoft-mesh/
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Cloudera, an enterprise data cloud company, announced the availability of the Cloudera Data Platform (CDP) Operational Database on both Amazon Web Services (AWS) and Microsoft Azure. CDP Operational Database is a fully managed cloud-native operational database with scale, performance, and reliability. Optimized to be deployed anywhere, on any cloud platform, CDP Operational Database aligns with the cloud infrastructure strategy best suited for the business.
CDP Operational Database works across public and private cloud environments, including on-premises. It enables application developers to deliver prototypes in under an hour on their choice of cloud, with the power to easily scale to petabytes of data. Application developers can deliver mission-critical applications with speed because CDP Operational Database auto-scales, auto-heals and auto-tunes based on workload needs. CDP Operational Database is now generally available on AWS and Azure.
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DataStax announced the general availability of Astra serverless, an open, multi-cloud serverless database-as-a-service (DBaaS). DataStax’s Astra will deliver pay-as-you-go data together with multi-cloud and open source. DataStax Astra builds upon the Apache Cassandra open source database and introduces a modern, microservices-based architecture that separates compute from storage, enabling database resources to scale up and down on demand to match application requirements and traffic independent of compute resources.
While serverless compute has been around for a while, serverless data has lagged due to the technical challenges around separating compute and storage. Scaling a database typically requires the addition of more server nodes in order to handle more demand or to store more data, which, in turn, requires that the entire data set is “rebalanced” across the nodes to keep the ratio of storage and computing capability equal. With the introduction of Astra serverless, developers will only pay for what they use, no matter how many database clusters they create and deploy. This flexibility brings faster application development and streamlined operations by letting developers and IT create as many databases as they need for development, testing, staging, or any other purpose.
MongoDB, Inc. and Google Cloud announced an expanded five-year partnership that will extend their existing go-to-market relationship and provide a deeper integration of Google Cloud products with MongoDB’s global cloud database, MongoDB Atlas. As a fully-managed service directly integrated with the Google Cloud Console and Marketplace, MongoDB Atlas gives joint customers integrated billing and support. Customers get a single bill for all Google Cloud services as well as MongoDB Atlas, and can use their Google Cloud spending commitments toward Atlas. The service is now available as a “pay as you go” offering on the Google Cloud Marketplace.
With this expanded partnership, MongoDB is enabling developers to integrate Atlas with Google Cloud products, including Pub/Sub, BigQuery, Dataproc, Dataflow, Cloud Run, App Engine, Cloud Functions, Google Kubernetes Engine (GKE), and Tensorflow. Additionally, Google Cloud’s mainframe modernization solutions now support MongoDB Atlas and help customers convert legacy COBOL code on mainframes into modern Java-based applications built on MongoDB. Together, G4 and MongoDB Atlas accelerate the modernization and migration process for organizations moving their business-critical workloads to the cloud.
dotData, provider of data science automation and operationalization for the enterprise, announced dotData Cloud, AI-automation software platform and services designed to provide business intelligence (BI) teams with the ability to automate AI/ML development. The solution was developed specifically to support growing enterprise organizations with small or no data science teams who want to launch or accelerate their data science practice. dotData Cloud is currently available as an all-inclusive bundle that includes technology and support to assist organizations in developing and deploying their first model, with a 45-day, risk-free, no-money guarantee.
dotData’s AI-powered feature engineering automatically discovers, evaluates and features by transforming hundreds of tables with complex relationships and billions of rows into a single feature table, automating the most manual data science projects that are fundamental to developing predictive analytics solutions. It also democratizes data science by enabling BI developers and data engineers to make enterprise data science scalable and sustainable. dotData is also designed to operationalize AI/ML models by producing both feature and ML scoring pipelines in production, which IT teams can then quickly integrate with business workflows. With the dotData GUI, AI/ML development becomes a five-minute operation, requiring neither significant data science experience nor SQL/Python/R coding.
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