Curated for content, computing, and digital experience professionals

Category: Computing & data (Page 13 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.

Contentful announces new products and capabilities

Contentful, a composable content platform, has incorporated a variety of generative AI-driven capabilities into the Contentful product and ecosystem and is introducing a number of capabilities that support better ways for digital teams to work together to harness the business value of content. Highlights include:

The Contentful Platform. Enhanced enterprise governance and security, including an expanded EU data residency footprint, can help address an organization’s data protection and compliance needs. The AI Content Type Generator, announced previously, streamlines the content model creation process so developers can accelerate time to market.

Contentful Studio. The new Experience Builder capability will provide a visual canvas whereby teams can create consistent, on-brand experiences using design system components and a structured content foundation. New AI enhancements include the AI Image Generator to create and manipulate images, and the improved AI Content Generator to quickly create content, translations, and SEO keywords.

The Contentful Ecosystem. New partnerships and enhanced integrations from AWS, Salesforce, SAP, Twilio Segment, commercetools, BigCommerce, Cloudinary, and WPP. Contentful AI advancements from ecosystem partners include the new AI Content Detector from Writer. SurferSEO delivers AI-driven SEO capabilities.

https://contentful.com/whats-new

Brightspot launches its next generation CMS solution 

Brightspot, a provider of content management solutions, announced a new version of its flagship product: Brightspot CMS version 4.7. New capabilities include:

Brightspot’s flexible Design System comes with hundreds of pre-built templates, styles, behaviors and interactions for Brightspot users to get started with. They can also choose to modify, extend or customize these pre-built assets with or without code, so your digital experiences fit your brand and can be easily changed over time.

The integration with OpenAI provides suggestions for headlines and full body text for articles and blog posts to make content creation easier, while enhanced search features allow users to make changes to content directly from the search view. With personalized content monitoring to stay updated on changes to specific content pieces and use in-platform production guides for step-by-step guidance on modules so you can navigate the CMS confidently.

Integrations with Shopify, Microsoft OneDrive, Google Drive, and SharePoint enable you to transform externally-created content into Brightspot CMS content types. AI-driven auto tagging and taxonomy capabilities reduce the manual burden of content categorization.

Brightspot CMS 4.7 introduces alerts that promptly notify of broken links, missing metadata, content inconsistencies and more, helping you proactively tackle potential issues.

https://www.brightspot.com/brightspot-cms/brightspot-4-7

WordLift introduces Content Generation Tool

WordLift announced a WordLift Content Generation Tool, technology for content generation that seamlessly integrates the capabilities of Large Language Models (LLMs) and incorporates a compound network of Knowledge Graphs (KG).

At the heart of WordLift is the Knowledge Graph. It’s a dynamic, interconnected web of information. It’s mapping every piece of information, fact, and relationship. It creates a rich tapestry that breathes life into your content. It isn’t only data; it’s a living, evolving entity that understands context, relationships, and nuances. By leveraging these graphs built using WordLift, we guide the LLMs, ensuring they remain on the right path, enriching content with depth and relevance, enabling a more reliable and accurate way of exploiting LLMs.

Key features and technologies: 

  • Structured Data Integration, making content more readable and recognizable for search engines like Google.
  • Knowledge Graph Creation, with the help of AI, allows search engines to comprehend the structure of your content.
  • Content Recommendation System can suggest products to users and integrate clickable cards, widgets, and shopping cart banners.
  • Generative AI-powered content creation to scale content production through AI within the company’s guidelines and TOV.
  • Integration with Data Studio facilitates the creation of shareable, comprehensive reports.

https://wordlift.io

Atlan launches Tag Management, enabling bi-directional tag sync

Atlan, an active metadata platform, has launched Tag Management, accelerating the shift of data governance to the left. 

As the modern data stack continues to evolve, data teams are faced with the challenge of ensuring the right people have the right access to the right data. Data teams need to ensure that they can confidently identify sensitive data across their data stack and protect it with the right access controls, while serving trusted data to data consumers.

Atlan’s Tag Management is a new way for data teams to manage data access across the modern data stack. Tags are important metadata that can be assigned to data assets to monitor sensitive data for compliance, discovery, and protection use cases.

For data teams that have tag-based access control built into their Snowflake Data Cloud, Atlan can now become the control plane for access control management. Once a data producer tags a data asset in Atlan or Snowflake, data teams can rest assured that the data asset is protected across the data ecosystem. 

https://atlan.com

Expert.ai launches Enterprise Language Model for Insurance (ELMI)

Expert.ai unveiled its “Enterprise Language Model for Insurance” – ELMI, a domain trained language model, to help insurers reach their process automation and digital transformation goals with the highest accuracy. By simplifying and powering the interaction with language data within the expert.ai Platform for Insurance, Insurers can access solutions that scale and take advantage of deep insurance domain expertise combined with the best and most cost-effective attributes of Large Language Models (LLMs) to automate core processes.

Through the expert.ai Platform for Insurance, ELMI supports key capabilities, including:

  • Generative Summarization: generate accurate summaries, condensing vast amounts of claim or policy information into concise insights, saving time and accelerating straight through processing or human review activities.
  • Zero Shot Extraction: extract crucial insurance data from structured/unstructured, handwritten/typed, good quality/bad quality sources with accuracy and automatically normalize output formats and add medical annotations such as ICD 9/10 medical codes.
  • Generative Q&A: answer questions quickly so underwriters and claims handlers can extract meaningful insights from proprietary case files by asking questions using natural language queries.
  • Cloud-agnostic: Offering the flexibility to deploy on any cloud infrastructure or on-premises, ELMI deployments easily meet insurer’s varying requirements.

https://www.expert.ai/expert-ai-launches-enterprise-language-model-for-insurance-elmi/

MongoDB announces new Atlas Vector Search capabilities

MongoDB announced new capabilities, performance improvements, and a data-streaming integration for MongoDB Atlas Vector Search.

Developers can more easily aggregate and filter data, improving semantic information retrieval and reducing hallucinations in AI-powered applications. With new performance improvements for MongoDB Atlas Vector Search, the time it takes to build indexes is reduced to help accelerate application development. Additionally, MongoDB Atlas Vector Search is now integrated with fully managed data streams from Confluent Cloud to make it easier to use real-time data from a variety of sources to power AI applications.

MongoDB Atlas Vector Search provides the functionality of a vector database integrated as part of a unified developer data platform, allowing teams to store and process vector embeddings alongside virtually any type of data to more quickly and easily build generative AI applications.

https://www.mongodb.com/press/new-mongodb-atlas-vector-search-capabilities-help-developers-build-and-scale-ai-applications

Amazon and Anthropic announce strategic collaboration to advance generative AI

Amazon and Anthropic announced a strategic collaboration that will bring together their respective technology and expertise in safer generative artificial intelligence (AI) to accelerate the development of Anthropic’s future foundation models and make them widely accessible to AWS customers. As part of the expanded collaboration:

  • Anthropic will use AWS Trainium and Inferentia chips to build, train, and deploy its future foundation models, benefitting from the price, performance, scale, and security of AWS.
  • AWS will become Anthropic’s primary cloud provider for mission critical workloads, including safety research and future foundation model development. Anthropic plans to run the majority of its workloads on AWS.
  • Anthropic makes a long-term commitment to provide AWS customers around the world with access to future generations of its foundation models via Amazon Bedrock. In addition, Anthropic will provide AWS customers with early access to unique features for model customization and fine-tuning capabilities.
  • Amazon will invest up to $4 billion in Anthropic and have a minority ownership position in the company.
  • Amazon developers and engineers will be able to build with Anthropic models via Amazon Bedrock so they can incorporate generative AI capabilities into their work.

https://press.aboutamazon.com/2023/9/amazon-and-anthropic-announce-strategic-collaboration-to-advance-generative-aihttps://www.anthropic.com

StreamText updates Automatic Speech Recognition Caption platform

StreamText, enterprise caption platform, announced the latest release of Automatic Speech Recognition (ASR) technology powered by artificial intelligence (AI). With the ability to create captions directly from an audio source, StreamText ASR features term glossaries to help finetune captioning AI for specific events and increase overall accuracy. The platform offers direct integrations with meeting software such as Zoom and Adobe Connect. It also supports over 50 source languages, including variants of English, French, and Spanish. While the quality of human captioning is often more accurate than AI counterparts, it may not always apply to all captioning needs. In these cases, StreamText ASR is a solution. ASR is useful in university settings, classrooms, government administration, and broadcast media.

https://streamtext.net/automatic-captions/

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