NEW YORK--(BUSINESS WIRE)--With ransomware and distributed denial of service (DDoS) attacks on the rise, the average number of focused cyberattacks per organization has more than doubled this year compared to the previous 12 months (232 through January 2018 versus 106 through January 2017). In the face of these growing cyber threats, organizations are demonstrating far more success in detecting and blocking them, according to a new study from Accenture (NYSE:ACN). Yet, despite making significant progress, only two out of five organizations are currently investing in breakthrough technologies like machine learning, artificial intelligence (AI) and automation, indicating there is even more ground to be gained by increasing investment in cyber resilient innovations and solutions. The study was conducted from January to mid-March 2018 and investigated focused attacks defined as having the potential to both penetrate network defenses and cause damage, or extract high-value assets and processes from within organizations. Despite the increased pressure of ransomware attacks, which more than doubled in frequency last year, the study found organizations are upping their game and now preventing 87 percent of all focused attacks compared to 70 percent in 2017.

Redwood City, Calif., April 16, 2018 – Informatica, the enterprise cloud data management leader, today announced the launch of its reimagined Enterprise Data Catalog with intelligent APIs and deeply enhanced AI algorithms, powered by the CLAIRE engine, for self-service data discovery by any line-of-business user. With new, intelligent APIs, users can have one-click access to the rich content of Enterprise Data Catalog from within their own applications. Developers can empower their applications with metadata intelligence and data recommendations. The AI-powered Enterprise Data Catalog intelligently scans and catalogs data assets across the enterprise and adds business context for understanding. It can identify domains and entities, such as customer, product, order, and more, providing seamless integration of all data with easy access and search capabilities.

Report Scope: In this report, the market has been segmented based on type, deployment, organization size, end-user industries, and geography.The report covers the overview of the global market for machine learning and analyses the market trends, considering the base year of 2016 and estimates for 2017 to 2022. Revenue forecasts from 2017 to 2022 for segmentation based on deployment, organization size, end-user industries, and geography have been estimated with values derived from solutions and service providers' total revenues. The report also includes a section on the major players in the market.Further, it explains the major drivers, competitive landscape, and current trends in the machine learning market. The report concludes with an analysis of the machine learning vendor landscape and includes detailed profiles of the major players in the global machine learning market. Report Includes: - 45 data tables and 32 additional tables - An overview of the global market for machine learning - Analyses of global market trends, with data from 2016 and 2017, and projections of compound annual growth rates (CAGRs) through 2022 - Identification of segments with high growth potential and their future applications - Explanation of major drivers and regional dynamics of the market and current trends within the industry - Detailed profiles of major vendors in the market, including Amazon.com Inc., Alphabet Inc., Baidu Inc., Intel Corp. and Hewlett Packard Enterprise Company Summary Machine learning is one of the fastest growing areas of computer science, with a wide range of applications.Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

DEEP AERO has announced today that it will give passenger drones as a reward to three lucky winners from the pool of all contributors who contribute 1 ETH or more to its pre-sale campaign, subject to the pre-sale campaign getting fully subscribed*. "The use of unmanned aerial vehicles is increasing exponentially," says Mr. Gurmeet Singh, CEO of DEEP AERO. "We're heading towards a future in which millions of drones will fly billions of flights. At some point in the not-too-distant future, fleets of commercial drones are expected to swarm across the skies. Current airspace management and air traffic flow management systems don't have the capabilities to handle the type of operations relevant to drones. In addition, the anticipated traffic density of drones is far beyond the capabilities of current air traffic management systems."

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence (AI) in North America: AI Market by Platforms, Components, Deployment Mode, Applications, and Industry Verticals 2018 - 2023" report has been added to ResearchAndMarkets.com's offering. Artificial Intelligence (AI) represents machine-based intelligence, typically manifest in "cognitive" functions that humans associate with other human minds. There are a range of different technologies involved in AI including Machine Learning, Natural Language Processing, Deep Learning, and more. One of the primary drivers for AI is automated machine-driven decisions. Consequently, AI is rapidly making its way into many advanced solutions including autonomous vehicles, smart bots, advanced predictive analytics, and more. Some of the more well-known companies leading the way in the United States include IBM, Intel, Microsoft, Siemens, and others.

Built on Feedzai's distributed microservices architecture, the service allows financial institutions and their data science teams to bring their preferred machine learning modelling and runtime frameworks, including open source, research, or commercial, to the Feedzai platform to fight fraudulent activities. Thus, the open machine learning engine enables the use of any language or environment for data science activities (data scientists no longer have to work in a singular environment dictated by a third-party vendor); leverages emerging algorithms as they become available (data science teams can use pre-written machine learning libraries from any open source); and it enables automated end to end connectivity across the data science ecosystem. Feedzai's OpenML is powering Feedzai's fraud prevention products for customers around the world, including 10 of the top 25 banks in the world, processing more than USD 5 billion in transactions every day. For more information about Feedzai, please check out a detailed profile of this company in our dedicated, industry-specific online company database.

WIRE)--Feedzai has launched the Feedzai OpenML Engine, in response to recognizing the need for data science teams to utilize their own tools and expertise. Built on Feedzai's distributed microservices architecture, this powerful service allows data scientists to bring their preferred machine learning modeling and runtime frameworks, including open source, research, or commercial, to the Feedzai platform. Initial product support includes an SDK for Python, R, and Java, and it provides close integration with any open source library, sourcing framework, and modeling environment. The three main innovations in Feedzai's OpenML framework include: "Data scientists shouldn't be forced to comply with closed systems by their legacy vendors, creating unnecessary burdens, and bottlenecks," says Paulo Marques, Feedzai co-founder and CTO. "Feedzai has always worked to make that a thing of the past. OpenML will make those teams more effective, not just by a slight improvement, but by magnitudes that will set them well ahead of their competitors."

IndigoVision has announced that the next release of their Artificial Intelligence powered by BriefCam will include the latest security features in the industry, and will be launched within the coming weeks, additional to it being previewed at ISC West 2018 in Las Vegas. IndigoVision's Artificial Intelligence powered by BriefCam allows IndigoVision customers to quickly and easily review hours of footage in minutes, rapidly identifying people and objects of interest by object type, attribute, direction, color or size. The recently announced BriefCam v5 introduces new capabilities across all three of the platform's seamlessly integrated modules, delivering a powerful approach to making video searchable, actionable and quantifiable. The new version enables customers to rapidly realize both the security and business value their surveillance system can provide by innovatively harnessing the process-once-use-many paradigm throughout the platform. These new features and capabilities are directly aligned with IndigoVision's offering, providing customers with statistical analysis reports, business intelligence insights, as well as multi-camera search and facial recognition.

While Uber's self-driving car endeavors may have been put on hold following a pedestrian fatality in Arizona last month, the company is continuing to expand from its ride-hailing roots at a rapid pace. After launching its dockless bike-sharing initiative Uber Bike in January, the company announced it would be acquiring its electric bike-providing partner Jump earlier this week. Now, the company is embarking on a new venture: a peer-to-peer car rental service called Uber Rent. Like its bike-sharing program, Uber Rent will debut in San Francisco before rolling out to other metropolitan areas. Also like Uber Bike, the service is made possible thanks to a partnership with another startup--Getaround, which lets you rent cars from other people in your area for as little as $5 per hour.

BOSTON--(BUSINESS WIRE)--O'Reilly, the premier source for insight-driven learning on technology and business, today announced the results of its 2018 Artificial Intelligence (AI) survey, "How Companies Are Putting AI to Work Through Deep Learning." Focused on deep learning, a technique used primarily for supervised machine learning, the survey explores the adoption of tools and techniques to build AI applications and the barriers that hinder business adoption. Findings suggest that the democratization of AI and deep learning applications will continue, as development tools and libraries improve. However, the shortage of AI-trained engineers and developers will persist. For example, while 54% of respondents indicated AI will play a big role (35%) or essential role (19%) in their organization's future projects, lack of skilled people was the number one bottleneck reported.