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Sky's the limit: Rise of delivery drones has U.S. cities asking who owns airspace
WASHINGTON - Blacksburg was already well prepared when the U.S. government announced in April that the Virginia town would be home to the country's first commercial drone delivery service. Virginia Tech University, based in Blacksburg, has for years hosted a major drone development program, which has carried out experimental deliveries of ice cream, fast food and more. "I moved (to Blacksburg) last August, and when I was telling people I was moving, they said, 'I know somebody there had their Chipotle (Mexican restaurant chain) delivered by drone!' " said Megan Duncan, a communications professor at Virginia Tech. So, when Wing became the first drone company to be approved as an air carrier by the federal government, allowing the Google parent company Alphabet Inc. to start drone deliveries in and around Blacksburg, many of the locals were excited, Duncan said. "I think there's superinteresting possibilities for remote areas that are underserved, particularly with people who need prescriptions and can't make a 45-minute drive," she said by phone.
Workshop: 'PredPsych', R toolbox for machine learning
The workshop will be held at Casa Paganini, InfoMus Research Centre, Piazza di Santa Maria in Passione, 34 – Genoa (Italy). The cost is € 80,00 for each participant. Registration closes on July 1st, 2019. Due to the limited availability of seats, early registration is strongly recommended to ensure participation. Please note that your registration is completed only after the registration form and payment are received.
Nordic Banks Look to Machine Learning to Fill Compliance Roles: Report
The market for anti-money laundering (AML) compliance jobs may be on the rise in Nordic countries, but don't count on that trend continuing. Advances in technology could render many compliance roles at Nordea Bank and Danske Bank obsolete, Bloomberg reported Monday. While Helsinki-based Nordea Bank relies on hundreds of employees to help scrutinize billions of transactions for signs of criminal activity, the system is costly and inefficient, and one the lender hopes to move away from, Mikael Bjertrup, head of the bank's financial crime prevention unit, told the news outlet. The bank, which currently uses machine-learning algorithms to close approximately 20 percent of its suspicious transaction alerts, is seeking to increase that total to 80 percent--a shift that would scale back the number of compliance officers needed by the institution, according to the report. "We'll be fewer people in the future, but our defense will be better," Bjertrup told Bloomberg.
Nordic Banks Look to Machine Learning to Fill Compliance Roles: Report
The market for anti-money laundering (AML) compliance jobs may be on the rise in Nordic countries, but don't count on that trend continuing. Advances in technology could render many compliance roles at Nordea Bank and Danske Bank obsolete, Bloomberg reported Monday. While Helsinki-based Nordea Bank relies on hundreds of employees to help scrutinize billions of transactions for signs of criminal activity, the system is costly and inefficient, and one the lender hopes to move away from, Mikael Bjertrup, head of the bank's financial crime prevention unit, told the news outlet. The bank, which currently uses machine-learning algorithms to close approximately 20 percent of its suspicious transaction alerts, is seeking to increase that total to 80 percent--a shift that would scale back the number of compliance officers needed by the institution, according to the report. "We'll be fewer people in the future, but our defense will be better," Bjertrup told Bloomberg.
Nvidia to work with ARM chips in supercomputer push
Nvidia Corp on Monday said it will make its chips work with processors from ARM Holdings Inc to build supercomputers, deepening Nvidia's push into systems that are used for modeling both climate change predictions and nuclear weapons. Nvidia was long known as a supplier of graphics chips for personal computers to make video games look more realistic, but researchers now also use its chips inside data centers to speed up artificial intelligence computing work such as training computers to recognize images. To do so, Nvidia's so-called accelerator chips work alongside central processors from companies such as Intel Corp and International Business Machines Corp. At a supercomputing conference held in Germany on Monday, Nvidia said its accelerator chips will work with ARM processors by the end of the year. ARM, owned by Japan's SoftBank Group Corp, provides the underlying processor technology for the chips in most mobile phones. But companies such as Ampere Computing, headed by Intel's former president, have been working to take those chips into data centers, where Intel's chips are dominant.
The Secrets of Successful AI Startups. Who's Making Money in AI Part II?
AI is in full gold rush mode. Every day we hear headlines of AI companies raising vast sums of capital to give them the resources to prospect the veins of AI gold. The money is flowing to these new frontiers. In the US venture capital funding for AI grew 72% year over year to a whopping $9.3B in 2018. Dataminr, a New York based AI and machine learning company that makes sense of news and information in real time, raised US$392 million in 2018, for example.
The Future of Artificial Intelligence Comes Alive in Our Buildings - USC Viterbi School of Engineering
USC Viterbi Professors Burcin Becerik-Gerber and Gale Lucas launch CENTIENTS, a center aimed at fostering research and collaboration toward human-centered design and integration of intelligent technologies into built environments. In the 1960s cartoon The Jetsons, the future was a world full of self-driving cars and sassy, meticulous robots. Individuals, like the patriarch George, could move through space--and the shower--without having to lift a finger. The mechanisms around him played a pivotal role in making decisions on his behalf, based on a learned understanding of his most basic preferences. For a while, this future seemed distant, but upon us now is an unprecedented opportunity to merge human behavior and preferences with automation to create a personalized, dynamic and improved daily reality for individuals at work and at home.
Artificial intelligence and the new age beauty and cosmetics industry - Prescouter - Custom Intelligence, On-Demand
The concept of beauty and cosmetics has advanced since the ancient Egyptian standards of smooth hair, clear skin, and beautiful eyes to include hair color and extensions, face contouring, and eyebrow enhancement. For each curve on our face, there now exists a product available to enhance and project it beautifully. The definition of beauty has changed over the years. Growing global economies, increasing disposable incomes, changes in lifestyle (indulgence in cosmetics for skin care, salon and spa treatments), and climate changes have resulted in increased skin care demands. The popularity of natural and organic beauty products, particularly in the United States and European countries, has also fostered the growth of the cosmetics market.
Amazon Alexa team uses machine learning to better handle regional language differences – TechCrunch
Amazon's Alexa voice assistant faces a massive challenge: Operating not only as a multi-lingual product, but also ensuring that all regional variants of languages it supports are well understood by Alexa, too. To help accomplish that, Alexa has been retrained entirely for every variant needed -- a time and resource-heavy activity. But a new machine learning-based method for training speech recognition created by Alexa's AI team could mean a lot less rework in building out models for new variants of existing languages. In a paper presented to the North American Chapter of the Association for Computational Linguistics, Amazon Alexa AI Senior Applied Science Manager Young-Bum Kim and his colleagues laid out a new system that was able to demonstrate improvements in accuracy of 18%, 43%, 115% and 57%, respectively, on four variants of English (from the U.S., the U.K., India and Canada) used in the trial. The team managed this by implementing a means through which it can tweak its learning algorithm to focus its attention more heavily on just a locale-specific model when it knows in advance that answers to requests from users made in that domain are highly region-specific (i.e. when asking to find a good nearby restaurant) versus when the results are going to be relatively similar regardless of where the request is being made. Alexa's team then combined their locale-specific models into one and also added their location-independent model for the language, and found the improvements measured above.