Microsoft Corp. and SAS announced an extensive technology and go-to-market strategic partnership. The two companies will enable customers to run their SAS workloads in the cloud, and will migrate SAS’ analytical products and industry solutions onto Microsoft Azure as the preferred cloud provider for the SAS Cloud. SAS’ industry solutions and expertise will also bring value to Microsoft’s customers across health care, financial services and many other industries. This will include optimizing SAS Viya, the latest release of the company’s cloud-native offering, for Azure as well as integrating SAS’ deep portfolio of industry solutions into the Azure Marketplace. Additionally, Microsoft and SAS will explore opportunities to integrate SAS analytics capabilities, including industry-specific models, within Azure and Dynamics 365 and build new market-ready joint solutions for customers that are natively integrated with SAS services across multiple vertical industries. Microsoft and SAS are already supporting customers with solutions that help them capitalize on the vast amount of data being generated by the Internet of Things by combining Microsoft’s Azure IoT platform with SAS’ edge-to-cloud IoT analytics and AI capabilities. Additional SAS products and solutions will begin rolling out later this year.
Category: Content technology news (Page 129 of 624)
Curated information technology news for content technology, computing, and digital experience professionals. News items are edited to remove hype, unhelpful jargon, iffy statements, and quotes, to create a short summary — mostly limited to 200 words — of the important facts with a link back to a useful source for more information. News items are published using the date of the original source here and in our weekly email newsletter.
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GIGXR, Inc., a provider of extended reality (XR) learning systems for instructor-led teaching and training, announced the availability of its GIG Immersive Learning System for the Fall 2020 Northern Hemisphere academic year. The cloud-based System was created to enhance learning outcomes while simplifying complex, real-life teaching and training scenarios in medical and nursing schools, higher education, healthcare and hospitals. The GIG Immersive Learning System is available for demos and pre-order now, and includes three core components:
- Remote and Socially Distanced Learning: Enables teaching and training with students in a distributed classroom through extended reality. Students can be co-located, remote or safely socially distanced, and participate in sessions anywhere using 3D mixed reality immersive devices and mobile phones, tablets or laptops for a 2.5D experience.
- Mixed Reality Applications: GIGXR’s products HoloPatient and HoloHuman run on Microsoft’s HoloLens 2, placing the 3D digital world in a collaborative physical space for safe development of clinical skills and exploration into human pathologies and anatomies.
- Immersive Learning Platform: Cloud-based infrastructure that supports GIGXR’s mixed reality applications and remote learning capabilities with additional features such as visual login, instructor content creation, holographic content management, session planning, roles and rights, license management, security, privacy, and long-term data management.
Doctor Evidence (DRE) has updated their newly launched DOC Analytics (“Digital Outcome Conversion”) platform with network meta-analysis (NMA) capabilities. DOC Analytics provides immediate quantitative insights into the universe of medical information using artificial intelligence/machine learning (AI/ML) and natural language processing (NLP). With the addition of indirect treatment comparison and landscape analysis using NMA, DOC Analytics is a critical, daily-use tool for strategic functions in life sciences companies. DOC Analytics allows users to conduct analyses comprised of real-time results from clinical trials, real-world evidence (RWE), published literature, and any custom imported data to yield insightful direct meta-analysis, network-meta analysis, cohort analysis, or bespoke statistical outputs. Analyses are informed by AI/ML and can be made fit-to-purpose with filters for demographics, comorbidities, sub-populations, inclusion/exclusion selections, and other relevant parameters.
Cloudera announced the the premiere of Cloudera Data Platform Private Cloud (CDP Private Cloud). CDP Private Cloud is built for hybrid cloud, seamlessly connecting on-premises environments to public clouds with consistent, built-in security and governance. CDP Private Cloud, built on Red Hat OpenShift, is an enterprise data cloud that separates compute and storage for greater agility, ease of use, and more efficient use of private and public cloud infrastructure. Together, Red Hat OpenShift and CDP Private Cloud help create an essential hybrid, multi-cloud data architecture, enabling teams to rapidly onboard mission-critical applications and run them anywhere, without disrupting existing ones. Companies can now collect, enrich, report, serve and model enterprise data for any business use case in any cloud. CDP Private Cloud is in tech preview for select customers and is expected to be generally available later this summer.
OpenAI API announce they were releasing an API for accessing new AI models developed by OpenAI. Unlike most AI systems which are designed for one use-case, the API today provides a general-purpose “text in, text out” interface, allowing users to try it on virtually any English language task. You can now request access in order to integrate the API into your product, develop an entirely new application, or help us explore the strengths and limits of this technology. Given any text prompt, the API will return a text completion, attempting to match the pattern you gave it. You can “program” it by showing it just a few examples of what you’d like it to do; its success generally varies depending on how complex the task is. The API also allows you to hone performance on specific tasks by training on a dataset (small or large) of examples you provide, or by learning from human feedback provided by users or labelers. The API is designed to be both simple for anyone to use but also flexible enough to make machine learning teams more productive. In fact, many OpenAI teams are now using the API so that they can focus on machine learning research rather than distributed systems problems. Today the API runs models with weights from the GPT-3 family with many speed and throughput improvements.
The field’s pace of progress means that there are frequently surprising new applications of AI, both positive and negative. We will terminate API access for obviously harmful use-cases, such as harassment, spam, radicalization, or astroturfing. But we also know we can’t anticipate all of the possible consequences of this technology, so we are launching today in a private beta rather than general availability, building tools to help users better control the content our API returns, and researching safety-relevant aspects of language technology (such as analyzing, mitigating, and intervening on harmful bias). We’ll share what we learn so that our users and the broader community can build more human-positive AI systems.
Grammarly released a new feature exclusively for Grammarly Business customers: customizable company style guides. With a company style guide, Grammarly Business can deliver customized, real-time writing suggestions to employees and be confident that customers exploring the company blog, browsing your website, or chatting with your support team, they’ll always feel like they’re interacting with the same company. Training employees to write consistently in the company style requires a large — and ongoing — time investment. On top of that, employees may be writing in dozens of different interfaces and tools. Trying to ensure compliance with a manual review process is rarely scalable or sustainable. Over time, individual deviations from company style add up, creating confusion for customers, eroding trust, and negatively impacting your brand and bottom line.
https://www.grammarly.com/blog/grammarly-business-style-guide/
MongoDB, Inc. announced a series of products that comprise the MongoDB Cloud platform that give developers a better way to work with data, wherever it resides. The launch of MongoDB 4.4, general availability of Atlas Data Lake and Atlas Search, and the general availability of MongoDB Realm offers organizations an escape from data silos and fragmented APIs as MongoDB Cloud delivers a developer-optimized, cloud-to-mobile platform. With MongoDB’s document data model, developers can structure data any way the application requires – from rich, hierarchical objects to simple key-value pairs and tables to connected graphs – and then query it with a single API. This gives developers a consistent and productive experience across the broadest set of workloads.
The addition of Atlas Data Lake and Atlas Search to the MongoDB Cloud platform simplifies modern data infrastructure, extends applications with rich search experiences and unlocks analytics for data archived in a data lake. Using the same MongoDB Query Language (MQL) and data model, with Atlas Data Lake a user can run a query and have the data brought back to them: whether it is real-time transactional data in the global Atlas global cloud database or a relevance-based search query with Atlas Search or a long-running analytical query on data in object storage. Using MongoDB Cloud, developers no longer need to deal with the cognitive burden of flipping back and forth between multiple technologies, query languages and data models. MongoDB’s Realm Sync enables bi-directional data synchronization between Realm’s mobile client on the front end and Atlas on the backend. This allows for data to be seamlessly shared between devices and with the backing database without complex conflict resolution and integration code.
SDL announced its machine translation (MT) technology is now available through the Reynen Court LLC platform, enabling legal firms and departments to provision and deploy SDL Machine Translation to securely translate any type of legal document or file. The Reynen Court platform combines a content-rich solution store and a control panel that simplifies the process for law firms and legal departments to source, evaluate, deploy, monitor and manage legal technology applications. Platform users can employ a multicloud technology strategy that includes on-premises data centers and virtual private clouds under the platform user’s control without compromising informational security, environmental stability, and infrastructure control. The platform also allows users to manage software subscriptions and evaluate usage and consumption metrics from across its tech stack in one place, permitting them to optimize technological investment through the deployment of legal technology. Reynen Court was established with support from a consortium of 19 leading global law firms. The latest version of SDL Machine Translation goes beyond automatic translation and integrates with multiple platforms to power digital customer experience, eDiscovery, due diligence, contract review, analytics, internal communications and collaboration.
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