Curated for content, computing, and digital experience professionals

Month: January 2024 (Page 2 of 3)

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.

Gilbane Advisor 1-17-24 — Knowledge editing, Bayesian inference

This week we feature articles from Dhanshree Shripad Shenwai, and Stephanie Shen. 

Additional reading comes from Kyle Wiggers, Caleb Sponheim, Ben Waber & Nathanael J. Fast, and Raphaël Millière & Cameron Buckner.

News comes from Typeface, OpenAI, Argo Translation, and Digimarc.

All previous issues are available at

Opinion / Analysis

A comprehensive study of knowledge editing for large language models

We’re still learning how knowledge graphs and large language models might be combined to reap the benefits of their individual capabilities. Knowledge graph embeddings in LLMs are one approach, but are typically not easily modified (as they are on their own) without re-training. Dhanshree Shripad Shenwai summarizes an interesting new paper on knowledge editing activity in general, and specifically on a new approach to knowledge editing in language models that doesn’t require re-training. (3 min)


Bayesian Inference: A unified framework for perception, reasoning, and decision-making

Stephanie Shen provides an accessible and useful description of what Bayes’ Theorem is and how it works in English (minus the math), and explains why its applicability is much broader than appreciated. A good refresher for those of us not steeped in it, and a good intro for decision-makers. (14 min)

More Reading

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Content technology news

Typeface announces integration within Microsoft Dynamics 365

Dynamics 365 Customer Insights customers get access to Typeface’s brand and audience-personalized AI seamlessly within their environments.

OpenAI introduces ChatGPT Team

OpenAI introduces ChatGPT Team — ChatGPT Team offers access to GPT-4 and DALL·E 3, tools like Advanced Data Analysis, a dedicated collaborative workspace, and admin tools.

Argo Translation launches CMSConnect

Support for multiple CMS, PIM, DAM, and CRM platforms expands their ability to help businesses make content available in numerous languages.

Digimarc offers free digital watermark embedding and detection tools to device and chip manufacturers and content creation platforms

The Secure, Automated, Fair, and Efficient (SAFE) digital watermark tools are designed to protect digital content owners and consumers.

All content technology news

The Gilbane Advisor is authored by Frank Gilbane and is ad-free, cost-free, and curated for content, computing, web, data, and digital experience technology and information professionals. We publish recommended articles and content technology news weekly. We do not sell or share personal data.

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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.

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.

Altova announces MobileTogether 9.0

Altova announced the release of MobileTogether 8.1, its low-code app development platform for building enterprise solutions and native apps for iOS, Android, and Windows. This release introduces full support for MQTT, allowing developers to build MQTT-enabled apps for communication among smart devices.

MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol used for communication by smart devices. MQTT is a critical component of real-time monitoring and control of devices and processes in a wide variety of industries including automotive, manufacturing, transportation, and healthcare. MQTT enabled apps are invaluable for realizing the potential of smart devices in industrial automation as well as smart home and smart office scenarios.

MobileTogether 9.0 introduces complete support for building MQTT enabled apps with new actions, page events, and variables for interacting with an MQTT network as a publisher, a subscriber, or both. Also new in MobileTogether 9.0:

  • Support for table row dragging
  • Support for table row swiping
  • Native support for MySQL and MariaDB
  • Support for drawing barcodes and QR codes
  • Chart generation on clients
  • Page source tree editing during simulation
  • Dark and light themes for MobileTogether Designer
  • Solution aliases on the server
  • Support for multiple row groups per table
  • New button looks

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.

MadCap Software acquires Xyleme to expand suite of intelligent content management products 

MadCap Software, Inc., announced the acquisition of Xyleme, Inc. With the addition of Xyleme to their product portfolio, organizations will have a single source of enterprise-class solutions for their content needs—from delivering product and user documentation to onboarding customers and their workforce.  

MadCap Software solutions allow for creating, managing and publishing modern technical documentation, such as support and Help portals, knowledge bases, instructional and procedure manuals, from a single source for any format, including online, mobile and print. MadCap, customers rely on the cloud-based MadCap Central content management platform, MadCap IXIA CCMS component content management system, and MadCap Flare technical authoring software for how corporate documentation is delivered.

Xyleme offers an intelligent learning content management system (LCMS) to control and manage an enterprise’s mission-critical content. Xyleme’s platform supports the development, management, multi-format publishing, and syndication of content for complex use cases, such as employee or customer onboarding, skills development, product and skills certification, customer training, and channel and partner enablement. Because Xyleme’s platform deliver content to all applications within the learning ecosystem—learning management system (LMS), learning experience platform (LXP), adaptive learning, mobile app, etc, it serves as a single source of truth for content and critical data.

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.

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