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Category: Computing & data (Page 1 of 76)

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.

Adobe adds Firefly to Adobe Express App

Adobe announced that the all-new Adobe Express mobile app is available to all users, bringing features powered by Adobe Firefly generative AI directly into the hands of content creators. The new Adobe Express mobile app brings Adobe’s photo, design, video and generative AI capabilities into an all-in-one content editor, giving everyone the ability to produce high quality content on web and mobile.

Marketers can create explainer and promotional videos to launch new products or design on-brand social campaigns for multiple social channels. Small business owners can design logos and standout business cards, create digital flyers for online sales, edit photos and videos and schedule and publish content for their TikTok and Instagram channels directly in the app. Creative professionals can bring assets they design in Adobe Illustrator and Adobe Photoshop into Adobe Express and quickly create social posts for their clients’ e-commerce business.

The new Adobe Express mobile app is now available for free worldwide in many languages and on most Android and iOS devices. Android users can download the new Adobe Express mobile app from the Google Play store and iOS users can download it from The App Store. New users can register for an Adobe Express account.

https://news.adobe.com/news/news-details/2024/All-New-Adobe-Express-Mobile-App-with-Firefly-AI-Now-Available-to-Millions-Empowering-them-to-Create-Standout-Content-On-the-Go/default.aspx

NebulaGraph Enterprise v5.0 offers native GQL support

As a member of Linked Data Benchmark Council, Vesoft (NebulaGraph) participates in the formulation and promotion of GQL standards and announced its GQL native support in NebulaGraph Enterprise v5.0.

ISO/IEC released the international standard of Graph Query Language (GQL) on April 12th, 2024. This publication establishes the foundations for property graphs, covering their creation, maintenance, and control, along with the data they comprise. It also standardizes the data management language for outlining and modifying the structure of these graphs and their collections.

GQL standards help to ensure data portability and manipulation across GQL implementations, and compatibility with programming languages and database tools. It will foster a dynamic graph database ecosystem and lower the entry barrier for this technology, enabling more enterprises to effectively utilize graph databases for complex relational data.

Rather than just being compatible or adapted to GQL, NebulaGraph Enterprise v5.0 has been redesigned to support GQL at the overall architecture level: it is built on and designed for GQL for data compatibility and interoperability, thereby amplifying the business value of graph databases across various scenarios. Native support for GQL means that enterprises can directly benefit from enhanced interoperability, improved stability, enhanced security, and more cost-efficient maintenance.

https://www.nebula-graph.io/posts/nebulagraph_enterprise_5.0_gql_supporthttps://www.iso.org/standard/76120.html

ThoughtSpot renames and adds features to ThoughtSpot Everywhere

ThoughtSpot, an AI-powered analytics company, today announced a series of initiatives for developers and product builders to help their customers, partners, and employees with generative AI and embedded natural language search, including a new pricing edition, a Vercel Marketplace listing, support channels, and new courses and certifications. 

ThoughtSpot has renamed the embedded solution, previously known as ThoughtSpot Everywhere to ThoughtSpot Embedded, reflecting ThoughtSpot’s vision to make analytics invisible – seamlessly embedded into every data application and user workflow – and its business outcomes visible. New features and offerings include: 

  • Developer Edition. The new Developer Edition offers developers exploring ThoughtSpot in free trial an opportunity to try ThoughtSpot Embedded capabilities with their specific use case for free for 12 months.  
  • Vercel Marketplace Integration. The new app listing for ThoughtSpot enables developers to quickly embed ThoughtSpot’s AI-powered analytics into their apps via the Vercel Marketplace.
  • Discord Channel. Developers can ask ThoughtSpot Embedded subject matter experts technical questions and receive guidance in our Discord community.
  • New ThoughtSpot Embedded Courses and Certifications. ThoughtSpot University is releasing a new paid certification for ThoughtSpot Embedded, the ThoughtSpot Embedded Developer. The new certification is for developers looking to attain formal recognition of their skills and knowledge in AI-Powered Analytics with ThoughtSpot Embedded.

https://www.thoughtspot.com/press-releases/thoughtspot-makes-embedding-ai-powered-analytics-easy-and-ubiquitous-for-everyone

Expert.ai launches Insight Engine for Life Sciences

Expert.ai, specialists in providing AI-powered language solutions to enterprises, today announced the launch of the expert.ai Insight Engine for Life Sciences.

For the world of drug research and development, data is both a challenge to be managed and an opportunity. The ability to effectively and quickly mine scientific and biomedical content for developing new drugs and to design and operate clinical trials is critical. The complexity of the diverse data sources that researchers depend on makes integrating, standardizing and analyzing them both challenging. Commercial licensing and data access restrictions, as well as the lack of granularity and different taxonomies used by common search tools complicate the process.

Advanced AI technologies provide the capability to mine and aggregate scientific content, synthesize knowledge, extract relevant information & reveal hidden correlations, helping researchers quickly access and analyze a vast amount of relevant information coming from biomedical and scientific literature, including full texts, speeding up the discovery and development of new drugs and therapies. Expert.ai Insight Engine for Life Sciences supports multiple use cases, including competitive intelligence, clinical trial design optimization, intellectual property protection, and research intelligence.

https://www.expert.ai/expert-ai-launches-insight-engine-for-life-sciences/

Progress releases Sitefinity 15.1

Progress, a provider of infrastructure software, announced new capabilities and enhancements in the latest release of Progress Sitefinity. Building on existing AI support throughout the platform, Sitefinity 15.1 introduces AI-powered conversion propensity scoring, AI-powered content classification for faster content editing and improved customer data modeling, enabling higher ROI and productivity. Additionally, new support for ASP.NET Core in .NET 8 provides flexibility to engineering teams, enabling them to develop and deploy using any platform.

  • New AI Propensity Scoring for Conversions: Progress Sitefinity Insight customer data platform (CDP) automatically identifies high/medium/low segments for each conversion, helping to refine audience segmentation and activate users. New Sitefinity Insight features also include streamlined rules management for persona and lead scores, ​additional and enriched data export options, automatic tracking of outbound clicks and improvements to the chatbot-based Insightful Assistant.
  • AI-Assisted Content Classification: Integrated with the rich text editor and available for static content types, dynamic modules and media items, this new tool delivers AI suggestions for classification built upon existing taxonomy and can help hone content performance by increasing discoverability, reusability and relevance.
  • Page Editing Experience Enhancements: The exposed widget toolbox embedded in the new page editor improves page editing and accelerates publishing.

https://investors.progress.com/news-releases/news-release-details/progress-announces-advanced-ai-capabilities-accelerate-delivery

Google enhances Google Workspace

Snippets from the Google Workspace blog…

Today we’re announcing the next wave of enhancements to Google Workspace, starting with Google Vids, our new AI-powered video creation app for work. Vids will sit alongside our other productivity tools like Docs, Sheets, and Slides. Vids is being released to Workspace Labs in June.

We’re also announcing two commercial offers that allow you to bring AI-powered meetings and messaging, as well as AI-powered security, to everyone in your organization, each for $10 per user, per month. In addition, Gemini is coming to Google Chat in preview, giving you an AI-powered teammate to summarize conversations, answer questions, and more. And finally, we’re making it easy for organizations to extend the power of their data and custom AI models by using Vertex AI with Workspace as a platform, enabling next-generation workflows that are built right into Docs, Gmail, and other Workspace apps.

By using Model Garden on Vertex AI, you can choose the right model for your needs from more than 130 options, and the Workspace add-on framework can allow you to bring that custom agent into the productivity apps you use everyday in Workspace, streamlining workflows, and enhancing team collaboration.

https://workspace.google.com/blog/product-announcements/new-generative-ai-and-security-innovations

MongoDB expands collaboration with Google Cloud

MongoDB, Inc. announced an expanded collaboration with Google Cloud to make it easier and more cost-effective to build, scale, and deploy generative AI applications using MongoDB Atlas Vector Search and Vertex AI from Google Cloud, along with additional support for data processing with BigQuery. The companies are also collaborating on new industry solutions for retail and manufacturing, with deeper product integrations and solutions to provide a seamless development environment for creating shopping experiences and data-driven applications for smart factories. For workloads that use highly sensitive data, MongoDB Enterprise Advanced (EA) is now available on Google Distributed Cloud (GDC).

  • MongoDB Atlas Search Nodes on Google Cloud provide dedicated infrastructure for generative AI and relevance-based search workloads that use MongoDB Atlas Vector Search and MongoDB Atlas Search.
  • A dedicated Vertex AI extension makes it easier to work with large language models (LLMs) without having to transform data or manage data pipelines between MongoDB Atlas and Google Cloud.
  • Integration of Spark stored procedures with BigQuery improves automation, optimization, and reuse of data processing workflows between BigQuery and MongoDB Atlas for analytics, BI, and end-user applications.

https://www.mongodb.com/press/mongo-db-expands-collaboration-with-google-cloud-at-google-next

DataStax acquires Langflow

DataStax announced it has entered into a definitive agreement to acquire AI startup, Logspace, the creators of Langflow, an open source visual framework for building retrieval-augmented generation (RAG) applications.

Langflow makes it easier and faster for any developer, experienced or new, to build Generative AI applications using Python-based composable building blocks and pre-built components, which can be combined in numerous ways. With its easy-to-use, drag-and-drop visual environment and rapid iteration of data flows, Langflow makes it simpler for any developer to build LangChain-based RAG applications and deploy in one-click. 

Developers benefit from a rich ecosystem that builds, shares, and reuses components with each other in the Langflow Store–a place to publish and search for components built by the community. With this, they can quickly test, reuse, and share flows to iterate on RAG applications with fine-grained control to dramatically speed up deployment and reduce hallucinations. 

The combination of Langflow and DataStax creates a one-stop Generative AI application stack offering flexible deployment options, including integration with DataStax Astra DB, alongside a rich ecosystem of Python libraries, and integration with partners like LangChain. The Langflow team will operate independently, focusing on project innovation and community collaboration.

https://www.datastax.com/blog/datastax-acquires-langflow-to-accelerate-generative-ai-app-developmenthttps://www.langflow.org

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