Curated for content, computing, and digital experience professionals

Day: February 7, 2023

MadCap Software adds cloud-based authoring to MadCap Central

MadCap Software, Inc., a provider of multi-channel content authoring software, released a new version of their content experience management (CxM) platform, MadCap Central. Designed for teams and enterprises, the latest version adds content authoring capabilities in the cloud. Now authorized users can contribute to content development, publishing, project management, collaboration, translation, hosting and analytics using the cloud-based MadCap Central platform without the need to add subscriptions to the MadCap Flare desktop application. Single-source publishing means the same content can be repurposed to deliver modern documentation websites, print brochures, online Help, knowledge bases, support sites, training and development content.

MadCap Flare and Central extend micro content functionality with the ability to design and display micro content as curated knowledge containers or panels on any topic or in search results. The flexible knowledge panels can be used to improve the user experience (UX). The containers can also be used to help bridge the gap between technical documentation and sales and marketing by highlighting new products, updated features, and promotions and turning technical information into a variable lead and revenue generation engine. MadCap Central also adds enterprise single sign-on (SSO) for improved user management, password management, and security compliance.

Weaviate releases generative search module

Weaviate announced the release of a generative search module for OpenAI’s GPT-3, and other generative AI models (Cohere, LaMDA) to follow. The module allows Weaviate users and customers to integrate with those models and eliminates hurdles that currently limit the utility of such models in business use cases.

Generative models have so far been limited by a centralized and generic knowledge base that leaves them unable to answer business-specific questions. Weaviate’s generative module removes this limitation by allowing users to specify that the model work from users’ own Weaviate vector database. The solution combines language abilities like those of ChatGPT with a vector database that is relevant, secure, updated in real time, and less prone to hallucination.

Weaviate’s open-source generative AI module is now available to download. The new model also integrates with the company’s SaaS and hybrid SaaS products for use by clients with service-level agreements.

The Weaviate vector-search engine is a “third wave” database technology. Data is processed by a machine learning model first, and AI models help process, store, and search through it. As a result, Weaviate is not limited to natural language; Weaviate can also search images, audio, video, or even genetic information. announces new features to hybrid natural language platform, experts in artificial intelligence (AI) for language understanding and language operations, released new features for its Natural Language (NL) platform enhancing natural language processing (NLP) workflow support. Employing a hybrid approach that combines NL techniques – including machine learning and knowledge-based, symbolic AI – the platform leverages unstructured data, like text in documents, applications and tools, to enable organizations across vertical domains to create new business models and optimize processes.

  • The new release enables the use of Kubernetes (K8s) to store core data on-premise, implement specific security measures or comply with specific regulatory requirements.
  • The release allows integration of 3rd-party external knowledge sources including Unified Medical Language System (UMLS) like MeSH, ICD9 and ICD10 and specific resources like the ones provided by WAND Inc., a source for domain specific taxonomies.
  • Developers can now interact with APIs using visual documentation, making it easy for back-end implementation and client-side consumption. Development teams can now visualize and interact with the API resources using a familiar Swagger interface.
  • Navigation of Knowledge Graphs (KGs): Resulting in customized navigation of knowledge models to identify the strength of related concepts and connections.

© 2024 The Gilbane Advisor

Theme by Anders NorenUp ↑