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.
Expert.ai, 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 expert.ai 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.
Zeta Alpha, a neural search and discovery platform, announced they have integrated with OpenAI’s GPT with its semantic neural search engine, to provide more reliable and explainable AI generated answers to enterprise search queries. This capability gives workers the ability to leverage GPT to access knowledge hidden in troves of internal company data.
Generative AI models like GPT tend to ‘hallucinate,’ or give answers that seem plausible, but are not factually correct. This prevents organizations from adopting AI tools for enterprise search and knowledge management. The combination of Zeta Alpha’s intelligent neural search engine and advances in GPT-3 reduce this problem by applying natural language understanding. Other enhancements include:
- InPars v2, a GPT-powered neural search model that enables fast tuning on synthetic in-domain data without the cost of creating terminology lists and taxonomies.
- Zeta Alpha enables users to ask a question and get contextually relevant results, automatically saving text to a spreadsheet or note for further analysis, and mapping back to the location where the document is saved for future access.
- Visualizing the information landscape in a semantic map and interpreting it with summaries by GPT can guide knowledge workers in the right direction to answer important strategic questions.
Section, a cloud-native hosting platform, announced it is making it easier to deploy and scale a Mastodon server; in just a few clicks, developers can use Section’s global platform to ensure a responsive user experience. With the open-source Mastodon software seeing explosive growth in interest and adoption, communities find themselves looking for solutions that can help run self-hosted social networks for a geographically dispersed base of users. Section’s platform automates the management of workloads like Mastodon using easily adjusted, rules-based parameters, making it suited to easily distribute and scale these Mastodon instances globally. Simultaneously, the company has announced support for Persistent Volume storage, better enabling distributed deployment of Mastodon and other complex workloads.
Digital Science has completed the acquisition of metaphacts, which has become the newest member of the Digital Science family. Based in Germany, metaphacts is a knowledge graph and decision intelligence software company. Its main product metaphactory is a platform that supports customers in accelerating their adoption of knowledge graphs and driving knowledge democratization. metaphacts operates in the pharmaceutical, engineering, manufacturing, finance, insurance, retail and energy markets, and will be working most closely with Digital Science portfolio product Dimensions.
This acquisition will see metaphacts and Digital Science build new, joint knowledge democratization solutions, facilitating the interface between humans and machines, and helping transform raw data into human and machine-interpretable, actionable insights to power business decisions. metaphactory’s semantic knowledge modelling approach will be applied to the Dimensions linked information dataset to expose new, meaningful knowledge through metaphactory’s semantic search and graph exploration capabilities.
Customers can leverage this curated, packaged data solution and enrich and gain additional context for their proprietary knowledge. Additional integrations with complementary products from the Digital Science portfolio, such as OntoChem’s text analysis and data mining products, are also available.
https://metaphacts.com ■ https://www.digital-science.com
Snowflake announced it has signed a definitive agreement for Snowflake to acquire SnowConvert, a suite of tools for efficiently migrating databases to the Data Cloud, from Mobilize.Net.
A key challenge with platform migrations is the code conversion required to ensure that all legacy database functionality can be moved to the cloud with minimal time and effort. The SnowConvert toolkit has long been a preferred solution for migrating customer workloads to Snowflake, using sophisticated automation techniques that reduce the need for manual coding and help ensure migration projects are successful.
After converting more than 1.5 billion lines of code1 with SnowConvert, the toolkit has proven to significantly reduce migration effort and improve the speed of migrating legacy databases to Snowflake through the built-in analysis capabilities at a data-type and procedure level, as well as matching to Snowflake native types. In addition to legacy database conversions, SnowConvert also converts workloads written in Scala and Python, making it easy to transfer that code to Snowflake’s Snowpark developer environment.
Closing of the acquisition is subject to the receipt of required regulatory approvals and other customary closing conditions. SnowConvert will expand Snowflake’s professional services footprint in Costa Rica, Colombia, and Bellevue, Washington.
https://www.snowflake.com/ ■ https://www.mobilize.net
One AI, a platform that enables developers to add language AI to products and services, announced it has entered into a collaboration with Amazon Web Services (AWS). The relationship allows One AI to offer its Software-as-a-Service (SaaS) language AI solutions in the AWS Marketplace, which makes it easy for customers to find, test, buy and deploy software on AWS.
One AI’s advanced natural language processing (NLP) platform allows developers to analyze and process large amounts of text, audio and video data through an application programming interface (API) for a range of use cases, including analyzing and understanding email threads for customer sentiment or reactions, extracting important points in a conversation, examining and breaking down all data from call centers, and determining positive and negative feedback on various subjects from social media posts and product reviews.
Businesses and developers can create their own Language Skills or choose from a library that includes capabilities such as advanced data extraction, transcription, summarization, sentiment analysis, emotion recognition, and action item detection. The library of Language Skills allows businesses and developers to tailor the solution to their specific needs and use-cases.
https://www.oneai.com ■ https://aws.amazon.com/marketplace/pp/prodview-div4d7ckhwkqe
Lexalytics, an InMoment company and provider of AI-based, natural language processing (NLP) technology, announced it has improved accuracy and expanded NLP capabilities for 11 non-English languages. Now global brands and businesses can analyze unstructured data natively and benefit from full-featured text analytics to better understand their customers and make more informed decisions across 31 total languages.
While some companies offer a range of NLP features in languages other than English, few cover the sheer number that Lexalytics supports. Many rely on machine translation before processing which can decrease the accuracy of the analysis. Because Lexalytics processes text data in its native language, it can take into account specific nuances and complexities of that language, and better understand the meaning and context of the text.
Lexalytics has expanded feature coverage to include entities, themes, summarization, sentiment (at the document and item level), categorization, and part-of-speech tagging for the following 11 languages: Arabic, Danish, Finnish, Hebrew, Norwegian, Polish, Russian, Swedish, Thai, Turkish and Vietnamese. Lexalytics continues to offer full-featured support for an additional 20 languages. These expanded language capabilities are available for customers of Lexalytics’ Salience, Semantria API, and Spotlight application, as well as InMoment’s XI Platform.