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Category: Computing & data (Page 43 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.

DataStax eases migrations from Apache Cassandra to DataStax Astra

March 31, 2021 /

DataStax announced the general availability of a new Zero-Downtime Cloud Migration tool that enables organizations to seamlessly migrate live data from self-managed Apache Cassandra instances to the company’s fully managed serverless Cassandra offering, DataStax Astra with no downtime. The Apache Cassandra open source database is often used for workloads that need to deliver massive amounts of data to users around the world with high reliability. As such, many Cassandra production applications are business critical, always on, and downtime is not an option. With DataStax’s new migration tool, enterprises can easily migrate live production Cassandra or DataStax Enterprise workloads to the DataStax Astra database-as-a-service (DBaaS) to quickly take advantage of the cost savings and other benefits of fully-managed, serverless Cassandra. The DataStax Zero-Downtime Migration tool is available for zero cost, and it comes with every DataStax Astra subscription. For more information on the fastest way to get up and running on Astra without any downtime, see

https://www.datastax.com/blog/four-steps-migrate-live-data-apache-cassandra-astra-zero-downtime

ThoughtSpot acquires SeekWell

March 31, 2021 /

ThoughtSpot, provider of search & AI-driven analytics, announced it has entered into a definitive agreement to acquire SeekWell. With SeekWell, customers will be able to operationalize their analytics and use SQL to push cloud data insights directly to business applications. As the companies integrate their offerings, the combination of ThoughtSpot and SeekWell will let users use natural language search to pull data from cloud data warehouses, modify it with productivity applications like Google Spreadsheets, then automatically and sync it back to business applications like Salesforce. With SeekWell and ThoughtSpot, customers can find insights easier, and close data loops by pushing insights directly back to applications and scaling data-driven decision making in the process.

SeekWell capabilities are available from ThoughtSpot starting today. As SeekWell becomes fully integrated into ThoughtSpot, this entire process will be powered by natural language search. No SQL will be required; instead, customers can use search to find data in the cloud, enable modification via productivity apps, and sync it with business apps. ThoughtSpot will also invest in building new business app integrations, expanding the number of end destinations for SeekWell.

https://www.thoughtspot.com ▪︎ https://seekwell.io

SciBite launches AI-driven semantic search platform

March 31, 2021 /

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.

http://scibite.com/scibitesearch

Arthur releases NLP model monitoring solution

March 29, 2021 /

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.

https://www.arthur.ai

DataStax and IBM collaborate on NoSQL database

March 23, 2021 /

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

https://www.ibm.com/products/datastax-enterprise

ABBYY launches no-Code platform Vantage 2 and AI Marketplace

March 23, 2021 /

ABBYY launched Vantage 2, a low-code/no-code platform that delivers cognitive skills for RPA robots, automation systems, chatbots, and mobile solutions, enabling organizations to gain insights from documents and content. The company also launched ABBYY Marketplace, a marketplace where organizations can discover, try, and purchase reusable AI skills to accelerate their automation initiatives, while partners can build and publish skills to automate all types of content-centric processes.

ABBYY Vantage 2 lets citizen developers to have more control within intelligent automation initiatives, enabling business users to digitize operations faster without complete reliance on IT: with Vantage, they can derive insights from documents on a large scale. The re-architectured platform is built on microservices and packaged into containers orchestrated by Kubernetes. Cognigy, EXL, Kryon, Micro Focus, NICE, Pegasystems, PwC, and RoboRana are already integrating Vantage 2 with their platforms. Out-of-the-box connectors developed by ABBYY are available for Alteryx, Blue Prism, and UiPath.

The new ABBYY Marketplace provides an extensive online collection of reusable technology assets including cognitive skills for classification of documents and data extraction, ready-to-go process flows, and pre-built connectors. The Marketplace offers pre-trained skills for all types of documents like invoices, purchase orders, receipts, loan documents, insurance claims, bills of lading, and more.

www.abbyy.com/solutions/digital-intelligence

Optimizely acquires customer data platform Zaius

March 22, 2021 /

Optimizely announced it has acquired Zaius, a customer data platform (CDP), bringing the context of the customer to the experience creation and optimization process of digital experiences. With the addition of Zaius organizations can:

  • Harmonize: Zaius adds 50 pre-built connector apps, including Shopify, Snowflake and Zendesk, to Optimizely’s Digital Experience Platform (DXP), powering the ability to create a unified view of customers via one-click integrations and automated identity resolution with consent management.
  • Understand: Zaius’s segmentation engine coupled with Optimizely’s behavioral data (from experiments) and transactional insights (from its content and commerce platform) provides a new level of insight aided by artificial intelligence (AI) and machine learning (ML)-driven predictions.
  • Act: Zaius includes more than 125 pre-configured orchestration recipes that allow marketers to take the optimal action immediately based on the full context of digital performance now visible across the entire process from creation to optimization.

Optimizely’s DXP focuses on the creation and optimization of digital experiences. With Zaius’s CDP – including its capabilities for AI and ML – the platform can unlock more value by providing visibility and guidance through the lens of the customer.

https://www.optimizely.com ▪︎ https://www.zaius.com

DataRobot 7.0 enhances enterprise AI platform

March 16, 2021 /

DataRobot unveiled upgrades to every product in its enterprise AI platform to optimize the value seen through AI deployments and enable better business outcomes with AI. Enhancements include:

  • MLOps remote model challengers, which allow organizations to challenge any production model – no matter where it is running and regardless of the framework or language in which it was built. By analyzing how challenger models perform versus the current champion model on the exact same production data, companies can easily determine which model is best for them now or at any point in history.
  • Choose your own forecast baseline, which lets companies compare the output of their forecasting models with predictions from DataRobot’s Automated Time Series product.
  • Visual AI image augmentation, available through DataRobot AutoML, which creates new training images from a company’s dataset by intelligently replicating and transforming the original images. Organizations can improve the accuracy of their image models while reducing the need to manually capture and label new images.
  • Enhanced prediction preparation. DataRobot’s visual data prep capabilities allow organizations to prepare their data for model training. Customers can use visual data prep to more easily score new data from models already deployed. DataRobot’s Data Prep tools work within platform, enabling companies to secure scored data and prediction explanations from any deployed model for transparency and trusted AI. For addition features see

https://www.datarobot.com/platform/new/datarobot-7-0/

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