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Artificial Intelligence (AI) in Retail Market worth $15.3 billion by 2025 - Exclusive Report by Meticulous Research

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Geographically, the global artificial intelligence in retail market is segmented into five major regions, namely, North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. The global AI in retail market is analyzed methodically with respect to major countries in each of the regions with the help of bottom-up approach to arrive at the most precise market estimation. At present, North America holds a dominating position in the global AI in retail market. The region has high technology adoption rate, presence of key players & start-ups, and high penetration of internet. Consequently, North America is expected to retain its dominance throughout the forecast period.


Scientists used artificial intelligence to discover a 2,000 year-old stick figure in Peru's mysterious Nazca Lines

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Artificial intelligence has helped archaeologists uncover an ancient lost work of art. The Nazca Lines in Peru are ancient geoglyphs, images carved into the landscape. First formally studied in 1926, they depict people, animals, plants, and geometric shapes. The formations vary in size, with some of the biggest running up to 30 miles long. Their exact purpose is unknown, although some archaeologists think they may have had religious or spiritual significance.


How AI Can Reduce Electricity Theft

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Since renewable energy is more economically feasible, this has led to self-generation, with solar panels or wind turbines on the roof of our home. We hope that such installations will reduce our energy bills while helping the planet and everything at the same time. If we cannot save the electricity generated, Then it will fall and power theft is a surprisingly big thing. The Revenue Protection Association estimates that such theft costs 40 440 million a year in the UK alone. In Brazil, Electrobras claims that 22% of its electricity is lost due to fraud and theft.


Speech Analytics Market Analysis of Key Players, Market Key Players, End User, Demand and Consumption By 2025 - Montana Ledger

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Rising number of contact centers and necessity for compliance and risk management across several verticals have led the companies to invent solutions in speech analytics which will aid companies to comprehend the changing necessities of customers. Several organizations functioning in diverse industrial domains have been evolving interests for the transcription and analyzing of customers and structural media and uptake rational decisions for the management of business and consumers with the help of speech and text intelligence. This is the main factor that is responsible for the growth of the speech analytics market and a protuberant driving factor in the growing demands for speech analytics in several industrial applications. This rising demand can also be accredited to the burdens on businesses for safeguarding their rational assets for improving agility and competence in business operations via the all-embracing insights quarried in the Voice of Customer (VoC). Speech analytics is used in sectors such as customer experience management, agent performance, business processes, compliance and risk management, and market intelligence.


What We Can Learn From the Near-Death of the Banana

TIME - Tech

The banana has been the subject of Andy Warhol's cover art for the Velvet Underground's debut album, can arguably be the most devastating item in the Mario Kart video game franchise and is one of the world's most consumed fruits. And humanity's love of bananas may still be on the rise, according to data from the Food and Agriculture Organization of the United Nations. On average, says Chris Barrett, a professor of agriculture at Cornell University, citing that U.N. data, every person on earth chows down on 130 bananas a year, at a rate of nearly three a week. But the banana as we know it may also be on the verge of extinction. The situation led Colombia--where the economy relies heavily on the crop, as it does in several other countries including Ecuador, Costa Rica and Guatemala--to declare a national state of emergency in August.


Deep in the dark: enhancing malware traffic detection with deep learning Tryolabs Blog

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The IEEE Symposium on Security and Privacy (IEEE S&P) is one of the top-tier conferences in computer security and electronic privacy. This year, the IEEE S&P was held in May, in San Francisco. It was not a regular edition, as this flagship conference marked its 40th anniversary. This year's symposium was a special celebration that included a plenary session with some exceptional panelists from the S&P community, Test of Time awards for papers that have made a lasting impact on the field, and even an amazing birthday cake! I had the pleasure of presenting two research papers at two different workshops while at the conference: the Deep Learning and Security Workshop (DLS 2019) and the Workshop on Traffic Measurements for Cybersecurity (WTMC 2019). Both papers were based on my master's thesis, that I developed for the most part when I was a research intern at the Austrian Institute of Technology (AIT) in Vienna, Austria.


Estimation of the yield curve for Costa Rica using combinatorial optimization metaheuristics applied to nonlinear regression

arXiv.org Machine Learning

The term structure of interest rates or yield curve is a function relating the interest rate with its own term. Nonlinear regression models of Nelson - Si egel and Svensson were used to estimate the yield curve using a sample of historical data supplied by th e National Stock Exchange of Costa Rica. The optimization problem involved in the estimation process of model parameters is addressed by the use of four well known combinatorial optimization metaheu-ristics: Ant colony optimization, Genetic algorithm, Part icle swarm optimization and Simulated annealing. The aim of the study is to improve the local minima obtained by a classical quasi - Newton optimization m ethod using a descent direction. Good results with at least two metaheuristics are achieved, Particle sw arm optimization and Simulated annealing.


A model for predicting price polarity of real estate properties using information of real estate market websites

arXiv.org Machine Learning

November 20, 2019 A BSTRACT This paper presents a model that uses the information that sellers publish in real estate market websites to predict whether a property has higher or lower price than the average price of its similar properties. The model learns the correlation between price and information (text descriptions and features) of real estate properties through automatic identification of latent semantic content given by a machine learning model based on doc2vec and xgboost. The proposed model was evaluated with a data set of 57,516 publications of real estate properties collected from 2016 to 2018 of Bogot a city. Results show that the accuracy of a classifier that involves text descriptions is slightly higher than a classifier that only uses features of the real estate properties, as text descriptions tends to contain detailed information about the property. K eywords housing price prediction · real estate property · machine learning · doc2vec · xgboost 1 Introduction A fairly popular way for property sellers to advertise a property for sale is through a real estate market website which guarantees many more possible buyers than just the street for sale sign.


143 New Nazca Lines Discovered in Peru with the help of A.I. Technology Ancient Architects

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A team of Japanese researchers from Yamagata University and IBM Research have discovered an incredible 143 stunning geoglyphs, etched into the desert in southern Peru around the enigmatic Nazca Lines. It is yet another example of how technology is assisting archaeology because a number of images were found using state-of-the-art AI technology developed by IBM, finds that were then confirmed with an on-site investigations. The geoglyphs include humans, birds, camels, cats and other animals and were found between 2016 and 2018. They were identified through fieldwork and analysing high-resolution 3D data and aerial photography. Incredibly, one geoglyph in particular was solely discovered with AI technology, without the aid of humans, making it the first geoglyph discovered by an AI.


Webinar: Grow your Revenue with Artificial Intelligence (AI) Munvo

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Since joining Munvo in 2013, Dave has continuously focused on helping organizations enable their strategic vision through the evaluation and onboarding of key value-based technologies and processes. With direct experience in implementing over 25 EMM projects across Canada, the US, South America, and Europe, he specializes in designing business-driven solutions for the Banking, Travel, Telecom, and Healthcare industries. Prior to joining Munvo, Dave has held positions at Rogers Communications, Arthroteq Preclinical, and Forniture Technice Europee – an Italian-based electronics distributor servicing the RF communication sector. Dave holds a Bachelor's degree in Computing from Queen's University, as well as a Master's in Management from Harvard University. A frequent traveller by nature, he speaks English, Italian, French, Spanish, and Hebrew, and can sometimes be found swimming laps, enjoying a live jazz show, or discovering a new pizzeria.