Digital experience company Acquia announced enhancements to its digital asset management platform, Acquia DAM (Widen), including an artificial intelligence (AI) chatbot to assist in creative workflows. The capability enhances creative collaboration across content and creative teams with an always-ready sounding board and idea generator.
AI Assistant is integrated into the comments functionality of the Acquia DAM review and proofing tool, Workflow. Using it, anyone reviewing a content proof can ask the AI assistant a question in a conversational way and get a response in seconds to help spur creativity. Examples include getting copy suggestions to improve the written aspect of a project, requesting design suggestions, getting suggestions for visuals such as images or videos, receiving suggestions based on audience segmentation such as interests or behavior, or analyzing competitors’ content to help ensure differentiation.
Acquia also released new integrations for Acquia DAM to streamline collaboration across content and marketing teams and extend the value of their content across their martech stacks. These include: Canva, Jira, Dropbox, Marq, and Salesforce.
Elastic announced the launch of the Elasticsearch Relevance Engine (ESRE), with built-in vector search and transformer models, which is designed to bring AI innovation to proprietary enterprise data. ESRE enables companies create secure deployments to take advantage of all their proprietary structured and unstructured data.
Elastic has made investments in foundational AI capabilities to democratize AI and machine learning for developers with a Unified APIs for vector search, BM25f search and hybrid search, plus a transformer model small enough to fit on a laptop’s memory.
Using a relevance engine, like ESRE, allows companies to take advantage of all of their structured and unstructured data to build custom generative AI (GAI) apps, without having to worry about the size and cost of running large language models. The ability to “bring your own” transformer model and integrate with third-party transformer models allows organizations to create secure deployments that leverage GAI on their specific business data. With ESRE, the companies and community of users that have invested in Elastic solutions can advance AI initiatives right now without a lot of additional resources.
Adobe unveiled Generative Fill in Photoshop, bringing Adobe Firefly generative AI capabilities directly into design workflows. The new Firefly-powered Generative Fill giving users a new way to work by easily adding, extending or removing content from images non-destructively using simple text prompts. This beta release of Photoshop is Adobe’s first Creative Cloud application to deeply integrate Firefly. Adobe plans to incorporate Firefly across Creative Cloud, Document Cloud, Experience Cloud and Adobe Express.
Generative Fill automatically matches perspective, lighting and style of images to enable users achieve results while reducing tedious tasks. Generative Fill expands creative expression and productivity and enhances creative confidence of creators with the use of natural language and concepts to generate digital content.
Photoshop’s Generative Fill feature is available in the desktop beta app today and will be generally available in the second half of 2023. Generative Fill is also available today as a module within the Firefly beta app for users interested in testing the new capabilities on the web.
Docugami, a document engineering company that transforms how businesses create and execute critical business documents, announced an initial integration of LlamaIndex with Docugami, via the Llama Hub.
The LlamaIndex framework provides a flexible interface between a user’s information and Large Language Models (LLMs). Coupling LlamaIndex with Docugami’s ability to generate a Document XML Knowledge Graph representation of long-form Business Documents opens opportunities for LlamaIndex developers to build LLM applications that connect users to their own Business Documents, without being limited by document size or context window restrictions.
General purpose LLMs alone cannot deliver the accuracy needed for business, financial, legal, and scientific settings because they are trained on the public internet, which introduces a wide range of irrelevant and low-quality source materials. By contrast, Docugami is trained exclusively for business scenarios, for greater accuracy and reliability.
Systems aiming to understand the content of documents, such as retrieval and question-answering, will benefit from Docugami’s semantic Document XML Knowledge Graph Representation. Our unique approach to document chunking allows for better understanding and processing of your documents
Expert.ai announced availability of the expert.ai Platform for Life Sciences. With the expert.ai Platform for Life Sciences, teams can access advanced natural language understanding capabilities, learning methodologies, 3rd-party large language models like BioBert and Bio-GPT as well as customizable pre-built knowledge models to build custom solutions.
Through a hybrid AI approach combining natural language tools, enterprise language models and machine learning, the expert.ai Platform for Life Sciences shifts the way unstructured medical and scientific data is monitored, understood, analyzed and collated. Teams can access knowledge and insights trapped in medical articles, reports, press releases, clinical research, customer/patient interactions, consent forms, etc. as well as up-to-date knowledge available based on standards like MeSH, UMLS Conditions & Interventions and IUPAR. Pharmaceutical and Life Sciences teams can:
- Confirm scientific claims against trusted public and private knowledge sources;
- Extract connections between biomedical entities in literature for in-depth causality analysis to support researchers;
- Monitor clinical trials and social media sources filtered by any combination of indication, drug, mechanism of action, sponsor, or geography to gain insight for clinical trials;
- Accelerate the quality control process of clinical and preclinical reports analysis using sensitive and proprietary data sources prior to their submission to regulatory bodies.
Ontotext announced the release of Target Discovery, an AI-powered platform that speeds the process of discovering new safe and efficient drug candidates. Target Discovery combines knowledge from public and proprietary data, AI-derived data from scientific publications, patents and clinical trials. It also features analytics for target identification and selection that medical or scientific experts without technical skills. Knowledge graph technology can lower the cost and shorten the time for semantic data integration. It also brings in a new level of insights on top of highly connected data and provides normalized quality data for supporting AI analysis. Benefits include:
- Target Discovery stays up-to-date with the newest discoveries by automatically extracting knowledge from more than 80 million documents, including patents and clinical trials.
- Target Discovery combines all required data, whether public or proprietary, AI-derived or structured in one place. Information is updated regularly and includes a selections from AlphaFold, Open Targets, EMBL.
- One can quickly gain an overview of a disease or target with customizable visual analytics and dashboards over any type of data and source.
- Hidden relationships can be easily uncovered in a network of over 5 billion facts with advanced graph algorithms.
- Transparent insight provenance and evidence.
RWS, a provider of technology-enabled language, content and intellectual property services, announced the launch of its next major release of Tridion, RWS’s intelligent multilingual content management system. The platform combines web content, structured content and headless delivery in a single solution, for organizations with heavy content demands.
The new platform helps clients to better orchestrate the creation, management, translation and delivery of content to any digital touchpoint across the customer journey. It means that customers, employees and partners can expect a consistent experience, in their own language, on any device or channel. Includes:
- Headless Delivery – fine-grained access to content components and semantic modeling of headless content.
- Content Discovery – now also natively provides additional content services such as intelligent content recommendations.
- Content Security – further modernized features for access management, authentication and audit trails.
- User Experience and Workflow –simplified and aligned with daily user tasks with a direct impact on productivity for both web content and long-form structured content.
- Content Globalization – further streamlined translation workflows integrated with RWS’s translation technology.
Tridion Docs 15, Tridion Sites 10, an updated version of Tridion Dynamic Experience Delivery (DXD) and new embedded version of Fonto for structured content authoring, will be available in July 2023.
AI-powered search provider Sinequa has announced domain-specific enhancements to its intelligent search platform for Scientific Search and Clinical Trial Data. Its search platform now utilizes new Neural Search and ChatGPT capabilities for faster, more effective discovery and decisions in drug development and clinical research. Sinequa will present these capabilities at the 2023 Bio-IT World Conference, May 16-18, at the Boston Convention and Exhibition Center, during conference sessions and at booth #803 in Auditorium Hall C.
Combining the capabilities of Sinequa Neural Search – multiple deep learning and large language models for natural language understanding (NLU) – with the latest ChatGPT models through Azure OpenAI Service, Sinequa enables accurate, fast, traceable semantic search, insight generation, and summarization. Users can query and converse with a secure corpus of data, including proprietary life science systems, enterprise collaboration systems, and external data sources, to answer complex and nuanced questions. Comprehensive search results with high relevance and the ability to generate concise summaries enhance R&D intelligence, optimize clinical trials, and streamline regulatory workflows.