Curated for content, computing, and digital experience professionals

Category: Computing & data (Page 4 of 74)

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.

Uniform announces CMS capabilities for Visual Workspace

Uniform announced the addition of new CMS capabilities to its Uniform Visual Workspace, to expand the basic concept of a CMS from a single-source content repository to unified, multi-source one. This enables brands to leverage content from any source without writing any integration logic, setting up unreliable data synchronization processes, or moving content into yet another repository. In the Visual Workspace, mapping fields from different content sources is done without developer involvement. Localization, versioning and asset management are now part of the Visual Workspace.

For brands who already have one or more CMSs in place, this creates an opportunity to work with a single content model that spans those systems, along with any other content sources they use – be they legacy, monolithic, composable, or bespoke. With generative AI integrated throughout the Visual Workspace, new content can be created almost instantly. Uniform provides guardrails that ensure generative AI is creating accurate, on-brand content, using the language models you choose.

https://www.uniform.dev

ActionIQ announces CXAI to integrate GenAI data & GenAI content

ActionIQ, an Enterprise Customer Data Platform, announced the launch of CXAI, a suite of AI-enabled solutions purpose-built for customer experience (CX), marketing, and data teams. The first CXAI release introduces two modules, CXAI Data and CXAI Content. Together, these capabilities are meant to help marketers deliver personalized creative content to individual audience members.

CXAI Data

  • GenAI Audiences. An audience co-pilot for marketers, bringing a natural language interface to GenAI for marketers to build audiences, analyze performance, and uncover insights. Marketers can design the audiences and experiences they want, in their own language, without requiring SQL or data expertise.
  • AI Decisioning & Analytics. A new decisioning engine for personalizing customer experiences. AI Decisioning makes recommendations and optimizes for the best audience, products, offers, lookalikes, channel preference, and more. AI Decisioning can use out-of-the-box models, custom models, or in-house models.

CXAI Content. Today, we are announcing an exciting new partnership with Typeface, a generative AI platform for enterprise content creation. With ActionIQ CXAI Content and Typeface Multimodal Content Hub integration, marketers and designers create customized, on-brand content that aligns with ActionIQ’s audiences, and can be activated across any channel.

https://www.actioniq.com/newsroom/actioniq-announces-cx-ai-genai/

Pega introduces Pega GenAI Knowledge Buddy

Pegasystems Inc., announced Pega GenAI Knowledge Buddy, a generative AI assistant to enable customers and employees to get specific answers synthesized by generative AI from content scattered across knowledge bases.

With Knowledge Buddy, customers and employees can ask questions through conversational interfaces and get specific, accurate, audited, and concise responses – with transparent attribution to source content. Users can also ask Knowledge Buddy to generate new content, such as emails or documents, based on their existing libraries. Additionally, security features give organizations control over user access rights as well as transparency to understand how and from where the technology pulls information. Content authors will be able to add, update, or delete knowledge, with all actions managed and audited by Pega’s workflow automation. 

Organizations will be able to configure unique Buddies for different use cases – such as answering marketing, operations, sales, or service questions – and quickly integrate them into any internal system or digital channel.

Pega Knowledge Buddy also connects to knowledge libraries within Pega Knowledge Management, which allows organizations to build, manage, and optimize content by assisting content authors and managers during the curation process and enables content versioning and lifecycle management.

https://www.pega.com/products/genai-knowledge-buddy

DataStax launches Data API to simplify GenAI application development

DataStax, a company that powers generative AI (GenAI) applications with relevant, scalable data, announced the general availability of its Data API, a one-stop API for GenAI, that provides all the data and a complete stack for production GenAI and retrieval augmented generation (RAG) applications with high relevancy and low latency. Also debuting today is a completely updated developer experience for DataStax Astra DB, a vector database for building production-level AI applications. 

The new vector Data API and experience makes Apache Cassandra available to JavaScript, Python, or full-stack application developers in a more intuitive experience for AI development. It is specifically designed for ease of use, offering higher relevancy, throughput, and fast response times, by using the JVector search engine. It introduces an intuitive dashboard, efficient data loading and exploration tools, and seamless integration with AI and machine learning (ML) frameworks. 

Developers can use the Data API for an out-of-the-box AI ecosystem that simplifies integrations with GenAI ecosystem leaders like LangChain, LLamaIndex, OpenAI, Vercel, Google Vertex AI, Amazon Bedrock, GitHub Copilot, Azure, and all major platforms while supporting security and compliance standards. Any developer can now support advanced RAG techniques such as FLARE and ReAct that must synthesize multiple responses.

https://www.datastax.com/blog/general-availability-data-api-for-enhanced-developer-experience

Ontotext’s GraphDB available on the Microsoft Azure Marketplace

Ontotext, a semantic knowledge graph provider, today announced that its flagship product, GraphDB, is now available on the Microsoft Azure Marketplace. Now, enterprises can streamline the global deployment of graph databases, facilitating the migration of on-premises data to Azure and other prominent public cloud platforms. Customers can take advantage of the Azure cloud platform, with streamlined deployment and management to ensure compliance with rigorous industry and privacy regulations. 

Ontotext GraphDB accelerates knowledge graph builds, and provides users with a platform for enterprise-wide data integration and discovery. GraphDB was developed for companies with decentralized data challenges and that require data driven analytics in order to drive insights for crucial business needs. GraphDB on Azure enables their joint customers to:

  • Remove data silos and speed up time to insights/time to market with a linking engine for enterprise data management.
  • Unify data sources for impactful data sharing, collaboration and semantic data discovery that delivers ROI on information architecture spend.
  • Empower standardized data exchange, discovery, integration, and reuse to provide 360 views of their business.

https://www.ontotext.com/company/news/ontotexts-graphdb-solution-is-now-available-on-the-microsoft-azure-marketplace/

Pinecone announces Pinecone Serverless

Vector database company Pinecone announced Pinecone Serverless, with a unique architecture and a serverless experience, to deliver cost reductions and eliminate infrastructure hassles, allowing companies to bring better GenAI applications to market faster. Companies can improve the quality of their GenAI applications and have a choice of LLMs just by making more data (or “knowledge”) available to the LLM. Pinecone Serverless includes:

  • Separation of reads, writes, and storage reduces costs for all types and sizes of workloads.
  • Architecture with vector clustering on top of blob storage provides low-latency, fresh vector search over practically unlimited data sizes at a low cost.
  • Indexing and retrieval algorithms built from scratch to enable fast and memory-efficient vector search from blob storage without sacrificing retrieval quality.
  • Multi-tenant compute layer provides efficient retrieval for thousands of users, on demand. This enables a serverless experience in which developers don’t need to provision, manage, or think about infrastructure, as well as usage-based billing that lets companies pay only for what they use.

Pinecone Serverless is launching with integrations to Anthropic, Anyscale, Cohere, Confluent, Langchain, Pulumi, and Vercel. Pinecone Serverless is available in public preview today in AWS cloud regions, and will be available thereafter on Azure and GCP.

https://www.pinecone.io/blog/serverless/

Typeface announces integration within Microsoft Dynamics 365

Typeface, a generative AI platform for enterprise content creation, and Microsoft today announced an AI-powered experience within Microsoft Dynamics 365 Customer Insights, a customer data platform and journey orchestration solution, aimed at transforming how marketers work by reducing the complexities of end-to-end campaign management and enhancing marketer productivity and ROI. 

To use this AI-powered experience in Dynamics 365 Customer Insights, marketing teams can simply type their desired campaign outcome in their own words or upload an existing brief. Copilot then responds by generating a central project board that recommends and connects everything needed for the campaign, including audience data, journey orchestration, and channels – all in the flow of work. While creating their campaign, marketers will have access to Typeface, so they can generate and curate on-brand content directly within Dynamics 365 Customer Insights. For Dynamics 365 Customer Insights customers, an early access public preview, will be released in the first quarter of 2024.

https://www.typeface.ai/blog/typeface-announces-integration-within-microsoft-dynamics-365-customer-insights-to-help-redefine-marketer-experiences

OpenAI introduces ChatGPT Team 

From the OpenAI blog…

We’re launching a new ChatGPT plan for teams of all sizes, which provides a secure, collaborative workspace to get the most out of ChatGPT at work…

ChatGPT Team offers access to our advanced models like GPT-4 and DALL·E 3, and tools like Advanced Data Analysis. It additionally includes a dedicated collaborative workspace for your team and admin tools for team management. As with ChatGPT Enterprise, you own and control your business data—we do not train on your business data or conversations, and our models don’t learn from your usage. More details on our data privacy practices can be found on our privacy page and Trust Portal. ChatGPT Team includes:

  • Access to GPT-4 with 32K context window
  • Tools like DALL·E 3, GPT-4 with Vision, Browsing, Advanced Data Analysis—with higher message caps
  • No training on your business data or conversations
  • Secure workspace for your team
  • Create and share custom GPTs with your workspace
  • Admin console for workspace and team management
  • Early access to new features and improvements

We recently announced GPTs—custom versions of ChatGPT that you can create for a specific purpose with instructions, expanded knowledge, and custom capabilities. These can be especially useful for businesses and teams. With GPTs, you can customize ChatGPT to your team’s specific needs and workflows (no code required) and publish them securely to your team’s workspace. GPTs can help with a wide range of tasks, such as assisting in project management, team onboarding, generating code, performing data analysis, securely taking action in your existing systems and tools, or creating collateral to match your brand tone and voice. Today, we announced the GPT Store where you can find useful and popular GPTs from your workspace.

ChatGPT Team costs $25/month per user when billed annually, or $30/month per user when billed monthly. You can explore the details or get started now by upgrading in your ChatGPT settings.

https://openai.com/blog/introducing-chatgpt-team

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