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Category: Computing & data (Page 63 of 80)

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.

Amazon Web Services unveils space business segment

Amazon Web Services (AWS) announced it is introducing a new business segment dedicated to accelerating innovation in the global aerospace and satellite industry. The Aerospace and Satellite Solutions business segment will bring AWS services and solutions to the space enterprise, and work with customers and partners around the world to: reimagine space system architectures, transform space enterprises, launch new services that process space data on Earth and in orbit, and provide cloud solutions to support government missions and companies advancing space around the world. Retired Air Force Major General Clint Crosier, former director of Space Force Planning at the U.S. Space Force, is the leader of this new business segment.

AWS Ground Station helps customers communicate with satellites, and to downlink, process, and distribute satellite data within minutes of capture. AWS Ground Station, a fully managed service that provides satellite owners and operators global access to their space workloads, offers a hint of what these innovative solutions can look like. Enabling customers to downlink data and provide satellite commands across multiple regions with speed and agility—and at a low cost—means satellite operators don’t have to own and manage duplicative ground station infrastructure. AWS Ground Station is already being used by NASA’s Jet Propulsion Lab (JPL) and other customers.

https://blog.aboutamazon.com/

Serviceaide introduces Luma Knowledge

Serviceaide, Inc., a provider of intelligent, enterprise service management solutions, announced the launch of Luma Knowledge, a self-learning, knowledge-centered product that optimizes access, creation and reuse of enterprise knowledge to service and support needs of users and customers. The maker of the AI-powered Luma Virtual Agent, Serviceaide is leveraging AI technologies like natural language processing and machine learning in digital interactions, knowledge and automation to bring advanced capabilities and business value to service and support functions across the enterprise. Features and capabilities:

  • The Luma Knowledge hub provides a common tool to actively correlate and access information federated across the enterprise.
  • Luma Knowledge offers a common semantic pathway to all enterprise knowledge.
  • Natural Language Processing auto extracts topics and pulls text from complex documents to auto-create FAQs. 
  • A dynamic guided search capability, based on available knowledge, helps users access the right information even when they don’t know exactly what to ask for, and don’t know what is in the knowledge base.
  • Automated learning leverages machine learning to auto-tune retrievals and identify missing content or other related issues.
  • Knowledge Sharing – Federating across multiple knowledge bases, semantic searches and guiding requests deliver accurate knowledge
  • Knowledge Discovery – Proactively discovering knowledge both inside an organization and from external sources
  • Knowledge Improvement – Continuous monitoring of knowledge and feedback to provide recommendations for needed knowledge, correcting knowledge and searches, and retiring unused knowledge

https://serviceaide.com

Databricks introduces Delta Engine and acquires Redash

Databricks announced the availability of Delta Engine and the acquisition of Redash. These new capabilities make it faster and easier for data teams to use its Unified Data Analytics platform for data science, machine learning, and a broad range of data analytics use cases. Delta Engine is a high-performance query engine on cloud data lakes and Redash is an open-source dashboarding and visualization service for data scientists and analysts to do data exploration.

Delta Engine is tailored for use with Delta Lake, the open-source structured transaction layer for data lakes. Organizations can now build curated data lakes that include structured and semi-structured data and run all their analytics on high quality, fresh data in the cloud. Databricks acquired Redash, the company behind the successful Redash open source project, to provide easy-to-use dashboarding and visualization capabilities on these curated data lakes. With Redash, data scientists and SQL analysts can eliminate the complexity of moving data into other systems for analysis.

The open source Redash project was created to help data teams make sense of their data. Data scientists and SQL analysts can easily gather a wide variety of data sources, including operational databases, data lakes, and Delta Lake, into thematic dashboards. The results can be visualized in a wide variety of formats like charts, cohorts, and funnels, and are easily shareable across an organization or with external users. Redash can be used with Databricks today using a free connector, and Redash will be fully integrated into Databricks’ Unified Data Analytics Platform and the Databricks workspace in the coming months and take advantage of capabilities like Delta Engine.

https://databricks.com/

iManage Delivers AI and Knowledge Management to Document Management Users

iManage announced the availability of iManage RAVN Knowledge Unlocked. With Knowledge Unlocked, iManage has productized Knowledge Management and RAVN AI, making them accessible to a broader market through packaged solutions that are easy to deploy and use, and integrated with their document and email management product, iManage Work 10. iManage enables law firms, legal departments, and professional services organizations of any size to use AI with Work 10 plug-ins that minimize the need for dedicated Knowledge Management (KM) staff, AI expertise, or outside services. IT-implemented and user-driven, Knowledge Unlocked enables knowledge workers to capture and reuse important data locked in data repositories, mine best practices, and identify knowledge and experts across their organizations to get to the information they need, when they need it.

Knowledge Unlocked brings together various KM and AI capabilities – including classification, search, and machine learning – in an integrated package, taking what would previously have been individual products and combining them to solve specific KM problems with greater efficiency. The solution extends the document retrieval-oriented search of Work 10 to knowledge search that enables organizations to surface relevant matters, clauses, people or expertise that could be of value to the user.

Knowledge Unlocked is available in three editions – Essentials, Professional, and Enterprise – each with an increasing level of capability and sophistication. The tiers have been designed so that organizations don’t have to go through expensive system replacement to get to the next level in AI – they can continue to build upon Knowledge Unlocked.

https://imanage.com/

MariaDB releases MariaDB Community Server 10.5

MariaDB Corporation announced the general availability of MariaDB Community Server 10.5, a major release that brings high-performance analytics to the open source database. In a push to mainstream analytics and to make it as popular as MariaDB’s transactional engine, the company added a new, native columnar storage engine to the community database server and a new, native MariaDB Python Connector and Microsoft Power BI integration. All new analytical capabilities in MariaDB Community Server 10.5 are available for free with unrestricted use to broaden adoption of hybrid transactional and analytical processing, and modern analytical approaches.

MariaDB Server is compatible with the widely used MySQL database protocol and therefore supports native integrations with BI and data analysis tools and frameworks. This compatibility also enables access to data in any MariaDB storage engine, including ColumnStore. In addition, MariaDB released two new, native connectors to make data analysis with MariaDB easier and faster. MariaDB Community Server 10.5 including ColumnStore is available immediately for free direct download on the MariaDB website now and through Docker Hub by the end of June. MariaDB Connector/Python and MariaDB Power BI adapter can be downloaded from mariadb.com. For customers interested in MariaDB for demanding production environments with built-in high availability and massively parallel processing (MPP), please contact MariaDB for early access to MariaDB Enterprise Server 10.5.

https://mariadb.com

Adobe Sensei Product Recommendations integrate with Magento Page Builder

Adobe announced Product Recommendations for Magento Commerce has been integrated with Magento’s content creation tool, Page Builder, extending the embedded Magento Admin experience to streamline workflows. Magento merchants can now drag and drop Sensei-powered recommendation units on any position within content that’s being authored in Page Builder.

Adobe released Product Recommendations powered by Adobe Sensei, their AI and machine learning technology, to Magento Commerce customers globally in April. This feature allows merchants to deploy automated and intelligent recommendations across storefronts to help their customers discover new, relevant products throughout their shopping journey. Adobe plans additional Product Recommendations capabilities to bridge the gap between intelligent merchandizing and content management.

Key benefits of the Page Builder integration include:

  • Drag and drop functionality makes it simple to place product recommendations in any position within the content being edited via Page Builder.
  • Merchants can now easily add recommendation units to multiple content types including pages, blocks, dynamic blocks and individual fields.
    • Merchants can now target recommendations to specific customers by assigning dynamic blocks to various consumer segments.
    • With Page Builder, merchants can deploy specific recommendations to individual product pages instead of across all product pages.
    • Merchants can customize recommendation units within Page Builder to match their brand, including adding borders, colors, and custom headings.

Magento Commerce merchants that have implemented Product Recommendations can take advantage of the Page Builder integration today by updating their modules. Product Recommendations is exclusively available for Magento Commerce merchants.

https://magento.com/

Graph database

A graph database uses graph structures with nodes, edges, and properties to represent and store data. By definition, a graph database is any storage system that provides index-free adjacency. This means that every element contains a direct pointer to its adjacent element and no index lookups are necessary. General graph databases that can store any graph are distinct from specialized graph databases such as triplestores and network databases.

Semantic Web Company and Ontotext partner to advance enterprise knowledge graphs

Ontotext (OT) and Semantic Web Company (SWC) announced a strategic partnership to meet the requirements of enterprise architects such as deployment, monitoring, resilience, and interoperability with other enterprise IT systems and security. Users will be able to work with a feature-rich toolset to manage a graph composed of billions of edges that is hosted in data centers around the world. The companies have implemented an integration of the PoolParty Semantic SuiteTM v.8 with the GraphDB and Ontotext Platform, which offers benefits for numerous use cases:

  • GraphDB powering PoolParty: Most of the knowledge graph management tools out there bundle open-source solutions that are good at managing thousands of concepts, whereas PoolParty bundled with GraphDB manages millions of concepts and entities—without extra deployment overheads.
  • PoolParty linked to high-availability GraphDB cluster: GraphDB can now be used as an external store for PoolParty, which offers a combination of performance, scalability and resilience. This is particularly relevant for organizations intent on developing tailor-made knowledge graph platforms integrated into their existing data and content management infrastructure.
  • Dynamic text analysis using big knowledge graphs: PoolParty can be used to edit big knowledge graphs in order to tune the behavior of Ontotext’s text analysis pipelines, which employ vast amounts of domain knowledge to boost precision. This way the power and comprehensiveness of generic off-the-shelf natural language processing (NLP) pipelines can be custom-tailored to an enterprise.
  • GraphQL benefits for PoolParty: Application developers can now access the knowledge graph via GraphQL to build end-user applications or integrate knowledge graph services with the functionality of existing systems. Ontotext Platform uses semantic business objects, defined by subject matter experts and business analysts, to generate GraphQL interfaces and transform them into SPARQL.

https://www.ontotext.com/, https://www.poolparty.biz

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