Curated for content, computing, and digital experience professionals

Category: Computing & data (Page 26 of 88)

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.

Acquia updates Acquia DAM

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.

https://acquia.com/products/acquia-dam

Elastic unveils the Elasticsearch Relevance Engine

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.

https://www.elastic.co/enterprise-search/generative-ai

Adobe unveils Generative Fill for Photoshop

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.

https://firefly.adobe.com

Docugami announces integration with LlamaIndex

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

https://www.docugami.com/blog/llamaindex

Expert.ai launches AI platform for Life Sciences

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.

https://www.expert.ai/

Ontotext releases Target Discovery

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.

https://www.ontotext.com/solutions/ontotexts-target-discovery/

Sinequa enhances platform for scientific search and clinical trial data

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. 

https://www.sinequa.com/enterprise-search-for-industries/healthcare-life-science/

Adobe and Google integrating Firefly and Bard

Adobe and Google are partnering to bring Firefly to Bard, Google’s experimental conversational AI service, with the ability to continue the creative journey further in Adobe Express. With the new Bard by Google integration, users at all skill levels will be able to describe their vision to Bard in their own words to create Firefly generated images directly in Bard and then modify and use them to create designs via Express.

Because Firefly has the CAI’s Content Credentials on by default, every image created in Bard using Firefly will have transparency built in. The CAI’s Content Credentials are a free, open-source tool that serve as a digital “nutrition label.” Content Credentials can show information such as name, date, the tools used to create an image and any edits made to that image. They remain associated with content wherever it is used, published or stored, enabling proper attribution and helping consumers make informed decisions about digital content.

Firefly’s first model is trained on Adobe Stock images, openly licensed content and public domain content where copyright has expired. Enterprise businesses will be able to train Firefly with their own creative collateral in order to generate content in the company’s brand language.

https://www.adobe.com/sensei/generative-ai/firefly.html

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