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Trados announces Trados Studio 2024

Trados, the translation platform by RWS, announced the upcoming release of Trados Studio 2024, their computer-assisted translation tool. Studio 2024 includes new features that improve accessibility, democratize access to generative AI, and increase management capabilities:

  • Perform a project roundtrip (create, manage, translate, deliver) with screen readers and leverage native dictation in the online editor.
  • Access smart AI capabilities, such as our new ‘Trados Copilot – AI Assistant’ app exclusive to Trados Studio 2024, seamless support for Machine Translation Quality Estimation (MTQE) data and Smart Help – intelligent support as you work.
  • Benefit from full support for local, server and cloud-based projects in the new Manager view, better integration with cloud capabilities and the ability to leverage cloud resources during batch processing in local Studio projects.

Additional enhancements:

  • The workflow editor has the option to edit outcomes in human workflow tasks. This functionality simplifies the user experience for administrators making it easier for them to manage workflows, particularly when handling task transitions (which help users decide which ‘route’ they want their workflows to follow).
  • The customer portal is designed to streamline the translation project management process, providing a simple and efficient interface for requestors to create, track and retrieve their projects.

https://slator.com/trados-enhances-platform-with-new-accessibility-ai-and-management-features/

WordPress VIP introduces VIP API Mesh to enable composable digital experiences

WordPress VIP introduced VIP API Mesh, a new part of the WordPress VIP platform which simplifies the integration of backend systems. It handles the complex connections between WordPress VIP and other platforms, allowing front-end developers to retrieve all necessary data with a single GraphQL call.

The API Mesh simplifies data integration with a single API improves performance with caching, supports data transformation, and is accessible to both technical and non-technical users.

  • Single API: Regardless where data resides, the API Mesh manages pulling from various backends.
  • Performance acceleration: With built-in caching and indexing, queries go faster, improving user experience..
  • Data composition and transformation: Enables data transformation per your schema across multiple systems.
  • Prebuilt connectors, GraphQL, and REST: The API Mesh comes with dozens of prebuilt connectors, and can pull data from systems that don’t support GraphQL.
  • Read/write/execute: The API Mesh isn’t limited to pulling data from a backend. Just as easily update backend data across systems or invoke actions like triggering a marketing automation workflow on the backend.
  • No-code/low-code tools for content practitioners: The VIP API Mesh integrates with the WordPress Block Editor (Gutenberg), allowing non-technical staff to incorporate data from any API connected to the API Mesh into their content.

https://wpvip.com/2024/04/25/vip-api-mesh-composable-digital-experiences/

Snowflake launches Arctic, an open enterprise-grade LLM

Snowflake announced Snowflake Arctic, a large language model (LLM) an open, enterprise-grade LLM. It is optimized for complex enterprise workloads. In addition, Snowflake is releasing Arctic’s weights under an Apache 2.0 license and details of the research leading to how it was trained. The Snowflake Arctic LLM is a part of the Snowflake Arctic model family, a family of models built by Snowflake that also include practical text-embedding models for retrieval use cases.

Snowflake Arctic comes with an Apache 2.0 license that permits ungated personal, research, and commercial use. Snowflake also provides code templates, alongside flexible inference and training options so users can get started with deploying and customizing Arctic using their preferred frameworks. These will include NVIDIA NIM with NVIDIA TensorRT-LLM, vLLM, and Hugging Face. For immediate use, Arctic is available for serverless inference in Snowflake Cortex, Snowflake’s service that offers machine learning and AI solutions in the Data Cloud. It will also be available on Amazon Web Services(AWS), alongside other model gardens and catalogs, which will include Hugging Face, Lamini, Microsoft Azure, NVIDIA API catalog, Perplexity, and Together AI. In addition to the Arctic LLM, the Snowflake Arctic family of models also includes the recently announced Arctic embed. 

https://www.snowflake.com/news/snowflake-launches-arctic-the-most-open-enterprise-grade-large-language-model

AtScale introduces Developer Community Edition for semantic modeling

AtScale, a provider of semantic layer solutions for analytics and Generative AI, today announced the public preview of the AtScale Developer Community Edition. This free downloadable version of AtScale’s semantic layer platform allows users to build and share semantic models to democratize analytics. The Developer Community Edition serves as a Universal Semantic Hub, allowing semantic models to be distributed to various AI/BI tools, promoting a connected data environment. Features include:

  • Semantic Modeling Language – An object-oriented modeling language called the semantic modeling language (SML) was introduced to express complex business concepts. SML facilitates the sharing and reusing of composable and versionable semantic objects, supporting an analytics mesh, or hub-and-spoke governance style for users.
  • Business-Friendly Interface – Users can comprehend and analyze data without needing to know complex query languages or database knowledge.
  • Public Semantic Model GitHub Repository – AtScale Developer Community Edition adds a public GitHub repository for pre-built, reusable semantic models, helping users and the community to share, learn, and innovate together, making the benefits of analytics widely accessible. Industry-specific semantic models are readily available for use with any BI tool, offering value to companies seeking to leverage data modeling in their operations.

https://www.atscale.com/press/atscale-developer-community-edition-for-semantic-modeling/

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/

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