The Gilbane Advisor

Curated for content, computing, and digital experience professionals

Year: 2023 (Page 14 of 23)

Sinequa enhances platform for scientific search and clinical trial data

May 11, 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. 

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

Adobe and Google integrating Firefly and Bard

May 10, 2023 /

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

MindsDB and Nixtla enhance time-series forecasting

May 10, 2023 /

MindsDB, an open-source applied machine learning platform, announced full integration with Nixtla, an open-source ecosystem that offers time-series forecasting.

Time-series forecasting refers to making scientific predictions based on historical, time-stamped data. It allows data scientists to employ models to predict a future value or classification at a particular point in time, such as forecasting power demand, call volumes, inventory requirements, or supply and demand.

Nixtla offers libraries specifically for time-series forecasting. One of the libraries, StatsForecast, which provides statistical and econometric models, will now function seamlessly within the MindsDB ecosystem. This integration will allow developers using MindsDB to build AI-powered forecasting capabilities and anomaly detection solutions in the database without writing extensive code. MindsDB turns a team of 1,000 developers into 1,000 AI developers with little to no training.

The Nixtla integration includes accurate model implementations, probabilistic forecasting and confidence intervals, support for exogenous variables and static covariates, anomaly detection and time series forecasting. Nixtla’s StatsForecast is optimized for high performance and scalability and uses classical methods, such as ARIMA, rather than deep learning models. This platform means models can be trained quickly and generalized well, making short-time series forecasting easier for developers.

https://mindsdb.com ■‍ https://www.nixtla.io/

TransPerfect launches GlobalLink Connect app for Contentstack’s DXP

May 8, 2023 /

TransPerfect, a provider of language and technology solutions for global business, announced that its new GlobalLink Connect app is now available on the Contentstack Marketplace, part of Contentstack’s Composable Digital Experience Platform (DXP). Contentstack Marketplace’s apps allow users to extend the capability of Contentstack’s content management solution and customize its functionalities by easily integrating third-party platforms. The GlobalLink Connect for Contentstack app enables customers to:

  1. Select single or multiple entries for translation using the Translation Wizard dashboard
  2. Track the status of any project in real time with the new entry sidebar widget
  3. Manage and control content translation projects with the new configuration screen
  4. Configure translation for any content type using the new field configuration widget

GlobalLink is TransPerfect’s modular suite of tools specifically designed to manage the complex demands of creating, deploying, and maintaining multilingual content, drastically reducing the time and effort required throughout the localization process.

https://www.transperfect.com/about/press/transperfect-launches-globallink-connect-app-contentstacks-composable-digital

Algolia launches AI-powered Algolia NeuralSearch

May 2, 2023 /

Algolia launched Algolia NeuralSearch, their next-generation vector and keyword search in a single API. Algolia NeuralSearch understands natural language and delivers results in milliseconds. Algolia NeuralSearch uses Large Language Models (LLM) and goes further with Algolia’s Neural Hashing for hyper-scale, and constantly learns from user interactions.

Algolia NeuralSearch analyzes the relationships between words and concepts, generating vector representations that capture their meaning. Because vector-based understanding and retrieval is combined with Algolia’s full-text keyword engine, it works for exact matching too. Algolia NeuralSearch addresses the limitation in neural search to scale with their Neural Hashing, which compresses search vectors.

Algolia incorporates AI across three primary functions: query understanding, query retrieval, and ranking of results.

  • Query understanding – Algolia’s advanced natural language understanding (NLU) and AI-driven vector search provide free-form natural language expression understanding and AI-powered query categorization that prepares and structures a query for analysis. Adaptive Learning based on user feedback fine-tunes intent understanding.
  • Retrieval – The retrieval process merges the Neural Hashing results in parallel with keywords using the same index for easy retrieval and ranking.
  • Ranking – The best results are pushed to the top by Algolia’s AI-powered Re-ranking, which takes into account the many signals attached to the search query.

https://www.algolia.com/products/neuralsearch/

Gilbane Advisor 4-26-23 — Software², martech futures

April 26, 2023 /

This week we feature articles from Minqi Jiang, and Scott Brinker.

Additional reading comes from David Weinberger, Mike Masnick, David Pierce, and Kevin Schaul, Szu Yu Chen & Nitasha Tiku.

News comes from Weaviate, Xyleme, Bloomreach, and Replica Analytics.

Time for our own version of spring break. The next issue will be published on May 17.

All previous issues are available at https://gilbane.com/gilbane-advisor-index/

Opinion / Analysis

Software²: A new generation of AIs that become increasingly general by producing their own training data

“… exploration, as typically studied in reinforcement learning (RL) and supervised learning (SL)—where it appears as some variation of active learning—is primarily designed with a static, predefined dataset or simulator in mind … unsuitable for learning in open-ended domains like the real world, where the set of relevant tasks is unbounded and cannot be modeled as a static, predefined data generator.”

Minqi Jiang and colleagues look ahead to continuous, open-ended, generalized exploration, to get beyond this limitation. (14min)

https://thegradient.pub/software2-a-new-generation-of-ais-that-become-increasingly-general-by-producing-their-own-training-data/

Exploring the 2nd order effects of generative AI in marketing and martech

Scott Brinker is also looking ahead to what’s coming, beyond the immediately obvious, for marketing technology. (10 min)

https://chiefmartec.com/2023/04/exploring-the-2nd-order-effects-of-generative-ai-in-marketing-and-martech/

More Reading

All Gilbane Advisor issues

Content technology news

Xyleme adds Elevate module to CCMS/LCMS platform

The new product adds dashboard analytics, APIs, and rich integration capabilities to the existing component content management system (CCMS)
https://xyleme.com

Weaviate raises $50 million for vector database

The vector database technology addresses the problem of generating, storing, and searching embedding vectors and their corresponding objects.
https://weaviate.io

Bloomreach integrates ChatGPT with CMS

The ChatGPT Text Generator with Bloomreach Content CMS is designed to support the creation and integration of text into e-commerce web pages.
https://www.bloomreach.com/

Replica Analytics unveils Replica Synthesis 3.0

The latest version of trusted synthetic data generation software comes with a new intuitive user interface.
https://replica-analytics.com/

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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Xyleme adds Elevate module to CCMS/LCMS platform

April 24, 2023 /

Xyleme, a provider of enterprise Component Content Management Systems (CCMS), announced the launch of Elevate, the newest module in their platform. The new product will add dashboard analytics, APIs, and rich integration capabilities to the existing CCMS, providing users with advanced functionality to enhance their learning and development programs.

Elevate is designed to provide users with a more streamlined and efficient platform-wide user experience, making it easier to access and manage key platform capabilities. The dashboarding features provide users with a customizable interface that displays key metrics and insights, allowing for better decision making and management of learning content. The enhanced API capabilities allow for integration with other systems, such as HR and talent management platforms, providing a more comprehensive and connected experience. Elevate will also provide a hub for innovation, with a labs area designed to showcase emerging content intelligence features and integrations. Xyleme Elevate is available now, and the base edition is included with every platform instance.

https://xyleme.com

Weaviate raises $50 million for vector database

April 21, 2023 /

Weaviate, developer of the AI-native Weaviate vector database, announced a $50M round of funding led by Index Ventures with participation from Battery Ventures. Weaviate’s existing investors include NEA, Cortical Ventures, Zetta Venture Partners, and ING Ventures. The capital will be used to expand the Weaviate team and accelerate the development of its open source database and new Weaviate Cloud Service for the AI application development markets use of embedding vectors, which are AI-generated representations of documents, images, customers, products, and other objects.

The Weaviate database simplifies vector data management for AI developers. An essential AI-native infrastructure component, it addresses the problem of generating, storing, and searching embedding vectors and their corresponding objects. AI-native vector database capabilities include:

  • Extensible, built-in machine learning (ML) modules – Just load and search; Weaviate does the ML heavy lifting – any data type, any model, any use case.
  • Rich vector search – Supports a variety of ML searches with the added benefit of being able to search vectors and the source objects from which the vectors were generated.
  • High performance – Sub-second search, scales to billions of objects, runs non-stop.

https://weaviate.io

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