Data Science


How Bloomberg journalists use data science to move financial markets

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Bloomberg journalists have been breaking business news since 1990, but these days their reporting relies increasingly on data science. This change has thrust the head of data science, Gideon Mann, into a key role in the newsroom. The computer science graduate spent seven years as a staff research scientist at Google before he joined Bloomberg in 2014, but had little prior experience of finance and was initially surprised to see the influence that journalists have on markets. "Before I started at Bloomberg, I didn't understand the nature of how news moves markets," Mann told Computerworld UK from Bloomberg's new £1 billion European headquarters in the heart of the City of London. "Things happen in the real world and usually there's a journalist that's writing and talking about them and spreading the word, and that's how that information gets disseminated."


AI-Driven Marketing Offers High Hopes to B2B Firms Marketing

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Versium on Tuesday announced a partnership with LiveRamp, an Axiom company, to launch artificial intelligence-powered B2B audience segments,as part of a new business-to-business data management platform. The partnership will let companies perform online targeting of offline business professional data that often is housed within their own CRM systems. LiveRamp customers will get access to Versium's modeling engine to create custom audiences optimized for their likelihood of engagement. Versium will also offer unique business and consumer audiences built from its extensive LifeData Warehouse, which contains more than 1.5 trillion proprietary consumer and business professional behavioral data attributes, including social-graphic details, real-time event-based data, purchase interests, financial information, activities, skills and demographics. When those attributes are matched to an enterprise's internal data and used in Versium's machine learning models, clients improve customer acquisition, retention and cross-sell and upsell marketing activities, the company said.


Feedzai Unveils AutoML: Automated Machine Learning That Fights Fraud in a Fraction of the Time

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By automating tasks such as feature engineering and machine learning model creation, data scientists are now able to create fraud prevention solutions as much as 50 times faster than is possible with the traditional data science workflow. Increasingly intelligent fraud attacks require teams to act faster than ever to fight evolving fraud risks on multiplying fronts. Feedzai AutoML enables teams to deliver results faster and to quickly expand to new use cases, channels, and geographies. Now, data scientists can quickly generate the most relevant features and models, and adapt more quickly to fast-evolving fraud schemes and attack vectors. Feedzai AutoML works by automating and integrating the most repetitive and time-consuming steps in the data science pipeline, freeing data scientists to perform more consequential tasks.


Fake goods seizures surge after customs unleashes AI on counterfeiters

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Artificial intelligence is being credited for helping Hong Kong customs officials increase seizures of fake goods sold online by about one-third in the first six months of this year, resulting in a haul of counterfeit items worth HK$1.96 million (US$247,000). A new supercomputer they began using last December scoured websites 24 hours a day and detected close to 2,000 of the 5,200 items seized by the Customs & Excise Department. Over the same period last year, officers netted 11,800 pieces of counterfeit goods worth HK$1.47 million. A source said the department might look into expanding the capacity of the computer, which gathers important information during investigations, but he stressed it would complement rather than replace manual enforcement work by customs officers. "The analytics tool saves us a lot of time screening online platforms manually," the source said.


TuSimple Selects Parallel File System for Artificial Intelligence WekaIO

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Matrix is the fastest, most scalable parallel file system for AI and technical compute workloads. TuSimple's goal is to develop a Level 4 autonomous truck driving solution, for the dock-to-dock delivery of commercial goods. The company, which was founded by entrepreneurs from the California Institute of Technology, has facilities in San Diego, Calif. and Tucson, Ariz., and to date its technology has been road-tested for some 15,000 miles. TuSimple chose WekaIO Matrix after comparisons with other scale-out file systems demonstrated that only Matrix has the ability to meet its most demanding performance requirements. "WekaIO Matrix was the clear choice for our on-premises DNN training in the U.S. It was understood from the outset that a standard network-attached storage (NAS) solution would not be able to scale to the extent we would need it to, and apart from Matrix being the most performant of all the parallel file systems we evaluated, we really liked the fact that it is hardware-independent, allowing us better control over our infrastructure costs.


ARM Holdings lines up $600mn swoop for Treasure Data

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ARM Holdings is preparing a $600mn takeover bid for data analytics specialist Treasure Data, reports Bloomberg. SoftBank-owned ARM, which is based in the United Kingdom and is an industry-leader in semiconductor and software design, is eyeing the acquisition to expand its footprint in the Internet of Things (IoT). IoT is at the forefront of ARM's long-term strategy - in June, it completed the acquisition of leading technology connectivity management provider Stream Technologies and by 2035 it hopes to operate a trillion connected devices around the world. ARM was sold to SoftBank in 2016 for a reported $32bn, a purchase funded by SoftBank's Vision Fund which delivers investment for startups in advanced technologies such as artificial intelligence, driverless cars, robotics and ride sharing, as well as IoT. Treasure Data operates cloud services tailored to Big Data collection, storage and analysis and already works with a number of major IoT companies.


Insurtech start-up Groundspeed Analytics raises $30m funding - Compelo Insurance

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Founded in 2014, Groundspeed Analytics provides artificial intelligence (AI) and data science solutions to the global commercial property and casualty insurance industry, serving insurance brokers, carriers and managing general agents (MGAs) alike. The insurtech company plans to utilize the new funding to continue to expand its products and fooprint apart from growing its data science and engineering team from the current number of 40. Groundspeed Co-CEO Jeff Mason said: "We are thrilled to partner with Oak HC/FT as we embark on our next phase of growth. "Given Oak HC/FT's deep expertise in InsurTech and extensive network of industry leaders, we are confident that this new association will help Groundspeed aggressively expand our products and reach to help brokers and carriers unlock the tremendous value trapped in their unstructured information." Groundspeed Analytics said that it focuses on solving the toughest data challenge in the insurance industry which is to unlock the value of unstructured information.


Anaconda Leverages Containers to Accelerate AI Development - Container Journal

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Anaconda Inc. announced today it is leveraging Docker containers and Kubernetes clusters to accelerate the development of AI applications built and deployed using graphical processor units (GPUs) from NVIDIA. Previously, Anaconda added support for Docker and Kubernetes to version 5.0 of Anaconda Enterprise, a commercially supported instance of an open source platform for developing, governing and automating data science and AI pipelines on Intel processors. A version 5.2 of Anaconda Enterprise extends that platform to add support for GPUs. Matthew Lodge, senior vice president of products and marketing at Anaconda, says that training AI applications has been proven to be significantly faster on GPUs. But over time, developers of AI applications will be employing a broad range of algorithms across Intel processors, GPUs, field programmable gate arrays and new classes of processors such as the TPU processors developed by Google, which are designed specifically for AI applications.


Big Data Federation to Exhibit at @CloudEXPO NY #BigData #AI #MachineLearning #ArtificialIntelligence

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DXWorldEXPO LLC announced today that Big Data Federation to Exhibit at the 22nd International CloudEXPO, colocated with DevOpsSUMMIT and DXWorldEXPO, November 12-13, 2018 in New York City. Big Data Federation, Inc. develops and applies artificial intelligence to predict financial and economic events that matter. Their products are deployed by some of the world's largest financial institutions. The company develops and applies innovative machine-learning technologies to big data to predict financial, economic, and world events. The team is a group of passionate technologists, mathematicians, data scientists and programmers in Silicon Valley with over 100 patents to their names.


Willis Towers Watson selects Relativity6 for predictive analytics Markets Insider

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Willis Towers Watson, a leading global advisory, broking and solutions company, and Relativity6, Inc., a machine learning and artificial intelligence (AI) insurance-technology company, today announced that Willis Towers Watson has selected the Relativity6 platform to predict and optimise customer retention and win-back. Brent Lehmann, General Manager Affinity & Commercial Australasia said the partnership with such an innovative technology company will help to ensure Willis Towers Watson remains competitive in the marketplace. "Relativity6's product offerings are a good fit to accomplish our strategic objectives across the organisation, so we are very excited to partner with them to take full advantage of the data that we have accumulated within our core systems in Australia." Alan Ringvald, Chief Executive Officer at Relativity 6, commented: "We are honoured to partner with such a distinguished organization. We believe that our solution will enable Willis Towers Watson to better serve their customers and ultimately drive significant top line revenue growth.