Qualified data providers include category-leading brands such as Reuters, who curate data from over 2.2 million unique news stories per year in multiple languages; Change Healthcare, who process and anonymize more than 14 billion healthcare transactions and $1 trillion in claims annually; Dun & Bradstreet, who maintain a database of more than 330 million global business records; and Foursquare, whose location data is derived from 220 million unique consumers and includes more than 60 million global commercial venues. For qualified data providers, AWS Data Exchange makes it easy to reach the millions of AWS customers migrating to the cloud by removing the need to build and maintain infrastructure for data storage, delivery, billing, and entitling. Enterprises, scientific researchers, and academic institutions have been using third-party data for decades to conduct research, power applications and analytics, train machine-learning models, and make data-driven decisions. But, as these customers subscribe to more third-party data, they often have to wait weeks to receive shipped physical media, manage sensitive credentials for multiple File Transfer Protocol (FTP) hosts and periodically check for updates, or code to several disparate application programming interfaces (APIs). These methods are inconsistent with the modern architectures customers are developing in the cloud.

Cars.com is a leader in the automotive digital marketplace. Since 1997, we have built our B2B and B2C brand to preeminent status in the industry. While enjoying great stability, we continue to grow. Our workforce has more than doubled since 2006, and our revenue has increased more than 150% in that same time. Our highly engaged workforce enjoys our dedication to work/life balance, wellness and career growth as well as a rich set of employee programs.

Cars.com is a leader in the automotive digital marketplace. Since 1997, we have built our B2B and B2C brand to preeminent status in the industry. While enjoying great stability, we continue to grow. Our workforce has more than doubled since 2006, and our revenue has increased more than 150% in that same time. Our highly engaged workforce enjoys our dedication to work/life balance, wellness and career growth as well as a rich set of employee programs.

Reuters, the world's largest multimedia news provider, announced today that it has joined the newly launched AWS Data Exchange to provide access to trusted news and data to Amazon Web Services (AWS) customers. Even more enterprises will now have quick access to Reuters trusted, independent and impartial news content and data, which are produced by 2,500 journalists in more than 200 locations globally, to power their artificial intelligence (AI) applications. "Reuters is constantly seeking new ways to broaden the reach of our independent, trusted and unbiased news content and data. We are excited to be among the first providers of such content in AWS Data Exchange, where our multi-language news data will be made available to a diverse range of AWS customers around the globe," said Alphonse Hardel, Global Head of Business Development and Strategy, Reuters at Thomson Reuters. "With the increasing demand across industries in using news content to train and power their mission critical AI and analytics applications on the cloud, the depth and accuracy of Reuters coverage means AWS customers are now able to seamlessly access the highest quality of data from AWS Data Exchange," added Hardel.

MOUNTAIN VIEW, Calif., Nov. 12, 2019 -- Synopsys, Inc. (Nasdaq: SNPS) today announced that Himax's newly launched artificial intelligence (AI)-enabled WiseEye WE-I Plus ASIC platform has integrated Synopsys' DesignWare ARC Data Fusion IP Subsystem. The WE-I Plus ASIC is designed for application developers deploying CNN-based machine learning (ML) models on artificial intelligence (AI) and IoT applications, including smart home appliances and surveillance systems. "The demand for battery-powered smart devices with AI-enabled intelligent sensing is rapidly growing, especially in markets such as home appliances, door lock, TV, notebook, and building control or security," said David Lyou, executive vice president of Himax Technologies. "Our WiseEye WE-I Plus ASIC Platform, leveraging Synopsys' ARC EM9D processor IP, can be used with popular ML frameworks for the development of a wide range of applications in audio, video, and signal processing where power is a strict constraint and on-device memory is limited. We are receiving positive feedback on our solution from our partners and leading industry players."

Having established itself as a provider of continuous data ingestion and management software to support agile data operations, StreamSets has closely aligned itself with the DataOps movement since 451 Research last update. The two are a natural fit, given that DataOps seeks to bring the agility and automation advantages of DevOps to data operations. The latest update to the rebranded StreamSets DataOps Platform is Transformer, a native execution engine based on Apache Spark that boosts StreamSets' ability to perform both batch and streaming data transformations in support of ETL (extract, transform and load) and machine learning workloads. Download this report to learn how StreamSets transforms its DataOps platform with Spark-based execution.

In the last two decades, unsupervised latent variable models---blind source separation (BSS) especially---have enjoyed a strong reputation for the interpretable features they produce. Seldom do these models combine the rich diversity of information available in multiple datasets. Multidatasets, on the other hand, yield joint solutions otherwise unavailable in isolation, with a potential for pivotal insights into complex systems. To take advantage of the complex multidimensional subspace structures that capture underlying modes of shared and unique variability across and within datasets, we present a direct, principled approach to multidataset combination. We design a new method called multidataset independent subspace analysis (MISA) that leverages joint information from multiple heterogeneous datasets in a flexible and synergistic fashion. Methodological innovations exploiting the Kotz distribution for subspace modeling in conjunction with a novel combinatorial optimization for evasion of local minima enable MISA to produce a robust generalization of independent component analysis (ICA), independent vector analysis (IVA), and independent subspace analysis (ISA) in a single unified model. We highlight the utility of MISA for multimodal information fusion, including sample-poor regimes and low signal-to-noise ratio scenarios, promoting novel applications in both unimodal and multimodal brain imaging data.

Forward-Looking Safe Harbor Statement This press release contains certain forward-looking statements, as that term is defined in the Private Securities Litigation Reform Act of 1995, including those relating to the products and services described herein and to fiscal 2020 business performance and beyond and the Company's plans for growth and improvement in profitability and cash flow. You can identify these statements by the use of the words "may," "will," "could," "should," "would," "plans," "expects," "anticipates," "continue," "estimate," "project," "intend," "likely," "forecast," "probable," "potential," and similar expressions. These forward-looking statements involve risks and uncertainties that could cause actual results to differ materially from those projected or anticipated. Such risks and uncertainties include, but are not limited to, continued funding of defense programs, the timing and amounts of such funding, general economic and business conditions, including unforeseen weakness in the Company's markets, effects of any U.S. Federal government shutdown or extended continuing resolution, effects of continued geopolitical unrest and regional conflicts, competition, changes in technology and methods of marketing, delays in completing engineering and manufacturing programs, changes in customer order patterns, changes in product mix, continued success in technological advances and delivering technological innovations, changes in, or in the U.S. Government's interpretation of, federal export control or procurement rules and regulations, market acceptance of the Company's products, shortages in components, production delays or unanticipated expenses due to performance quality issues with outsourced components, inability to fully realize the expected benefits from acquisitions and restructurings, or delays in realizing such benefits, challenges in integrating acquired businesses and achieving anticipated synergies, increases in interest rates, changes to cyber-security regulations and requirements, changes in tax rates or tax regulations, changes to interest rate swaps or other cash flow hedging arrangements, changes to generally accepted accounting principles, difficulties in retaining key employees and customers, unanticipated costs under fixed-price service and system integration engagements, and various other factors beyond our control. These risks and uncertainties also include such additional risk factors as are discussed in the Company's filings with the U.S. Securities and Exchange Commission, including its Annual Report on Form 10-K for the fiscal year ended June 30, 2019.

Mercury Systems, Inc. today unveiled the EnterpriseSeries RES AI rugged rackmount server line, bringing High Performance Computing (HPC) capabilities to aerospace, defense and other mission-critical applications at the edge. "The proliferation of sensors, ever-growing data loads and the evolution of complex deep learning neural networks continues to increase computational demands, driving the need for supercomputing infrastructure closer to the edge," said Scott Orton, Vice President and General Manager of Mercury's Trusted Mission Solutions group. "Through close collaboration with technology leaders such as NVIDIA and Intel, we've developed reliable parallel computing systems that accelerate demanding artificial intelligence (AI), signal intelligence (SIGINT), and sensor fusion applications where it's needed the most." Why it Matters: Evolving compute-intensive AI, virtualization, big data analytics, SIGINT, autonomous vehicle, Electronic Warfare (EW) and sensor fusion applications require data center supercomputing capabilities closer to the source of data origin. Delivering HPC capabilities to the edge presents challenges as every application has its own security, performance, footprint, budget and reliability requirements.