Analytics leader SAS is helping customers gain more value from data with SAS Viya products, extending the value from the SAS Platform. These newest advances, such as embedded artificial intelligence (AI) capabilities, will further address the needs of organisations that are making analytics core to their business. A variety of industries, countries and organisation sizes have embraced SAS Viya products. With SAS, data scientists, analysts, developers, IT, domain experts and executives can all generate data-driven insights – from the same, consistent data, fostering greater collaboration and driving innovations faster. SAS continues to deliver new capabilities, such as image recognition, deep learning and natural language understanding into the SAS Platform.
DUBLIN, IRELAND--(Marketwired - October 17, 2017) - RecommenderX today announced that it won the Best Use of Data Science In A Start Up Award at the DatSci event held in Dublin on September 21, 2017. DatSci is an annual event that brings together and recognizes the best and brightest that Ireland has to offer in the expanding world of Data Science. RecommenderX is a technology company, focused on helping customers and partners improve productivity, performance, customer engagement, sales and profitability, by transforming Artificial intelligence (AI) to Business Intelligence (BI). RecommenderX is the top spin out of Europe's largest Centre for Data Analytics Insight, with deep domain knowledge in Data Analytics, Artificial Intelligence (AI), Machine Learning (ML), Personalization Technology, Recommender Systems and Explainable AI. "We are thrilled to be an award winner at DatSci 2017," stated Kevin McCarthy, Co-Founder & CTO of RecommenderX. "It is a fantastic validation of the efforts that our world-class team have been making helping companies all over the world harness their data by developing cutting edge applications and solutions that leverage data science and AI technologies."
One of the major factors that will have a positive impact on the growth of this market includes the rising usage of deep learning technology among various industries such as automotive, advertisement, medical and others. Moreover, increasing acceptance of cloud based technology, high usage of deep learning in big data analytics, high R&D expansions for enhanced processing hardware for deep learning and rising applicability in healthcare and autonomous vehicles are fueling the market growth. Moreover, the market has tremendous growth opportunity such as utilization of deep learning technology in smartphones and medical image analysis. Depending on application, data mining segment is anticipated to grow at a highest CAGR during the forecast period attributed to growing utilization of deep learning in cybersecurity and database systems and data analytics.
BCS Technology, a Global IT company headquartered in Australia providing end to end solutions in big data and analytics, announced the launch of their chatbot solution -- Interactive Social Airline Automated Companion (ISAAC) built on Cloudera's modern platform for machine learning and analytics optimized for the cloud -- Cloudera Enterprise. The solution combines the use of modern big data analytics technologies and natural language processing (NLP) by leveraging Microsoft's LUIS framework and the Cloudera Enterprise platform. "With Cloudera's machine learning and advanced analytics technology at the core of ISAAC, businesses can now use data to gain valuable insights, make accurate business decisions faster and deliver better products and services to enhance their customers' experiences. With the exponential growth of BCS and big data, a new subsidiary named ML Labs has formed, specialising in providing machine learning and deep learning algorithm solutions to clients looking to begin their journey through big data and analytics.
The main point is to combine mathematical operation together to form a workflow of choice. The graph takes care of evaluating the gradient of all the inputs to ease up setting up the minimizer. I have aimed for the library to be simple and transparent so that it would be easy to understand and modify to fit individual needs. Currently, supports most of the useful matrix operations, the Adam stochastic minimizer as well as modules for simplified deployment of dense, convolution and recurrent (vanilla and LSTM) networks.
Genpact announced that it has acquired TandemSeven, a Boston-headquartered company that delivers customer and digital experience innovation consulting using design thinking at its core. TandemSeven's ability to design better customer experiences complements Genpact's digital capability aimed at transforming business processes end-to-end. That's where TandemSeven's team of consultants, technologists, and designers, as well as its UX360 customer analytics technology, will complement Genpact's global business domain experts and digital and analytics experts in applying Lean Digital and its Genpact Cora AI-powered platform to help clients reimagine their customer experiences. Founded in 2001 and headquartered in Boston, TandemSeven's team of experts expands Genpact's U.S. operations, including its Boston area AI and digital innovation hub built on its recent acquisitions of Rage Frameworks and OnSource.
This press release includes information that constitutes forward-looking statements made pursuant to the safe harbor provision of the Private Securities Litigation Reform Act of 1995, including statements about Amdocs' growth and business results in future quarters. Such statements involve risks and uncertainties that may cause future results to differ from those anticipated. These risks include, but are not limited to, the effects of general economic conditions, Amdocs' ability to grow in the business markets that it serves, Amdocs' ability to successfully integrate acquired businesses, adverse effects of market competition, rapid technological shifts that may render the Company's products and services obsolete, potential loss of a major customer, our ability to develop long-term relationships with our customers, and risks associated with operating businesses in the international market. These and other risks are discussed at greater length in the Company's filings with the Securities and Exchange Commission, including in our Annual Report on Form 20-F for the fiscal year ended September 30, 2016 filed on December 12, 2016 and our quarterly 6-K form furnished on February 13, May 22 and August 14, 2017.
ST. LOUIS September 12, 2017 Amdocs (NASDAQ: DOX), a leading provider of software and services to communications and media companies, is launching Smartbot, an artificial intelligence (AI) and machine learning-based bot that enables digital service providers (DSPs) to provide customer care, sales and marketing engagements to even the most discerning millennial. Amdocs Smartbot with Microsoft Cognitive Services, specifically Microsoft Language Understanding Intelligent Service and Text Analytics API, provides leading DSPs with the ability to transform how they deliver highly personalized, self-service interactions with customers that are simple, quick and helpful. "With Microsoft Cognitive Services at its core, Amdocs Smartbot provides digital service providers (DSPs) with industry-specific context, natural language, emotion, sentiment and usability that supports our mutual customers in the communication and media industry, said Nagu Rangan, senior product marketing manager, Microsoft Azure, Microsoft Corp. "We're pleased to work with Amdocs to help shape the speed of adoption of the next generation customer care services DSPs will deliver." These risks include, but are not limited to, the effects of general economic conditions, Amdocs' ability to grow in the business markets that it serves, Amdocs' ability to successfully integrate acquired businesses, adverse effects of market competition, rapid technological shifts that may render the Company's products and services obsolete, potential loss of a major customer, our ability to develop long-term relationships with our customers, and risks associated with operating businesses in the international market.
In this post, I'll offer a look at data science's buzzwords from multiple perspectives, namely the theorist, the empirical data scientist, and the press release bluster, which too often is parroted by the mainstream press. Data Scientist: Unlike the toy datasets that long dominated machine learning research, today's big data is sufficiently large that it cannot fit conveniently in main memory on a single workstation. In short, big data is more data than can fit in main memory on a single machine. Theorist: Deep neural networks refer to graphical models in which data is computed upon by successive layers of nodes.