ABBYY announced the launch of NeoML, an open-source library for building, training, and deploying machine learning models. Available now on GitHub, NeoML supports both deep learning and traditional machine learning algorithms. The cross-platform framework is optimized for applications that run in cloud environments, on desktop and mobile devices. Compared to a popular open-source library (according to internal tests) NeoML offers 15-20% faster performance for pre-trained image processing models. Developers can use NeoML to build, train, and deploy models for object identification, classification, semantic segmentation, verification, and predictive modeling.

NeoML is designed as a universal tool to process and analyze data in a variety of formats including text, image, video, and others. It supports ​​C++, Java, and Objective-C programming languages; Python will be added shortly. NeoML’s neural network models support over 100 layer types. It also offers 20+ traditional ML algorithms such as classification, regression, and clustering frameworks. The library is cross-platform – a single code base that can be run on popular operating systems including Windows, Linux, macOS, iOS, and Android – and optimized for both CPU and GPU processors.

NeoML supports the Open Neural Network Exchange (ONNX), a global open ecosystem for interoperable ML models. The ONNX standard is supported jointly by Microsoft, Facebook, and other partners as an open source project. ABBYY invites developers, data scientists, and business analysts to use and contribute to NeoML on GitHub, where its code is licensed under the Apache License 2.0. The company offers developer support, ongoing review of reports, regular updates, and performance enhancements.

https://github.com/neoml-lib, https://www.abbyy.com/

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.

https://www.sas.com/, https://news.microsoft.com

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.

https://www.cloudera.com

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.

https://www.mongodb.com