How Can We Teach More Students How to Design With AI?

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While Raina's dream to have a dedicated space for AI design research on-campus is still out of reach, other design schools have started incorporating machine learning into their curriculum. Aaron Hill is assistant professor of data visualization at Parsons School for Design, and is the director of the Masters of Science in data visualization in the School of Art, Media, and Technology. "I come from a very quantitative and analytical background," he says, "I'm a statistician by trade, so that's an odd faculty hire for an art and design school." But given that Hill's work often lies at the intersection of art and science, he was in a good position to help establish the graduate program in data vis. "When the program launched, we started thinking about electives that would not just serve the data visualization program, but all of the graduate students at Parsons," Hill explains, "Machine learning was an obvious first elective that we needed to offer because it has become such an essential tool for how we take in information, how we filter it, and also how we interact with the world."


How One of America's Biggest Brands Developed A Data Culture

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It would be difficult to identify a more recognized brand in the underwear and casual wear industry than Fruit of the Loom. Trademarked in 1871, the company has been continuously operating under the illustrious apple and grapes logo since before the invention of light bulbs, cars, and telephones. But the modern Fruit of the Loom, Inc., has evolved over time. A 2002 acquisition by Berkshire Hathaway sparked the company's data transformation, initially starting as a project to standardize data across the four different business units now operating under the Fruit of the Loom, Inc. umbrella, which include Russell Athletic, Spalding, and Vanity Fair. In a recent podcast, Beth Rogers, Senior Manager of Data Science at Fruit of the Loom, talked about how her team uses data to develop foundational methodologies and applications for everything from SKU optimization to predictive price modeling and supply chain forecasting.


Indian Ocean Dipole can be better predicted thru machine learning, say researchers

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Researchers in Japan and The Netherlands have, for the first time, used machine learning techniques, in particular artificial neural networks (ANNs), to predict the Indian Ocean Dipole (IOD), a positive phase of which has affected weather and climate in India and Australia in a spectacular fashion so far in 2019-20. The IOD has both positive and negative phases, and signals large socio-economic impacts on many countries and hence predicting the IOD well in advance will benefit the affected societies, note authors JV Ratnam and Swadhin K Behera (Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama) and HA Dijkstra (Institute for Marine and Atmospheric Research Utrecht, Utrecht University in The Netherlands) in a paper published by Nature. The IOD is a mode of climate variability observed in the Indian Ocean sea surface temperature anomalies with one pole in Sumatra (Indonesia) and the other near East Africa. Therefore, the IOD is represented by an index derived from the gradient between the western equatorial Indian Ocean and the south-eastern equatorial Indian Ocean. It starts sometime in May-June, peaks in September-October and ends in November (2019's rather strong positive phase of the IOD lasted into early January of 2020).


Kristal.AI Offers Intelligent Personalised Investment Advisory, Closes Series A Funding Round

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According to a ResearchAndMarkets report, the digital asset management market was valued at around $1,240 million in 2018, and it is projected to reach $6,901 billion by 2024. The market is expected to grow at a CAGR of 34.1%, during the forecast period, 2019-2024. The report also suggests that the market is witnessing increased adoption of big data analytics and Artificial Intelligence, including facial recognition. Asheesh Chanda was aware of the importance of AI in financial planning and knew how to deploy it to deliver unbiased and factual recommendations to clients; thanks to his experience of managing a Singapore-based global macro hedge fund called KrisCapital. He used this vision and knowledge to create Kristal.AI – an AI-powered Digital Wealth Management Platform – in 2016 along with his friend and former IIT-D room-mate Vineeth Narasimhan.


Accountants to rely more on big data in 2020

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Technology such as data analytics, artificial intelligence, machine learning, blockchain and robotic process automation will be playing a greater role in the accounting profession this year, according to a recent report from the Institute of Management Accountants. The report indicates that finance and accounting professionals are increasingly implementing big data in their business processes, and the pattern is likely to continue in the future. The IMA surveyed its members for the report and received 170 responses from CFOs and other management accountants. Many of the CFOs are predicting big changes for 2020 in their businesses. "Four key elements must be present for organizations looking to become data-driven: data-savvy people, quality data, state-of-the-art tools and a supportive organizational culture," according to the report.


Alec Mackenzie (@AlecSocial)

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Research Infographic

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IMAGE: Researchers of the ICAI Group -- Computational Intelligence and Image Analysis -- of the University of Malaga (UMA) have designed an unprecedented method that is capable of improving brain images... view more Researchers of the ICAI Group -Computational Intelligence and Image Analysis- of the University of Malaga (UMA) have designed an unprecedented method that is capable of improving brain images obtained through magnetic resonance imaging using artificial intelligence. This new model manages to increase image quality from low resolution to high resolution without distorting the patients' brain structures, using a deep learning artificial neural network -a model that is based on the functioning of the human brain- that "learns" this process. "Deep learning is based on very large neural networks, and so is its capacity to learn, reaching the complexity and abstraction of a brain", explains researcher Karl Thurnhofer, main author of this study, who adds that, thanks to this technique, the activity of identification can be performed alone, without supervision; an identification effort that the human eye would not be capable of doing. Published in the scientific journal Neurocomputing, this study represents a scientific breakthrough, since the algorithm developed by the UMA yields more accurate results in less time, with clear benefits for patients. "So far, the acquisition of quality brain images has depended on the time the patient remained immobilized in the scanner; with our method, image processing is carried out later on the computer", explains Thurnhofer.


Silicon Valley Event On Machine Learning Tackles The Latest Riddles Vexing AI Self-Driving Cars

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There's a child's riddle that asks you to indicate what can be held in your left hand and yet cannot be held in your right hand. Take a moment to ponder this riddle. Your first thought might be that anything that could be held in your left hand should also be able to be held in your right hand, assuming of course that there's no trickery involved. One trick might be that you could hold your right hand in your left hand, but that you cannot presumably "hold" your right hand in your right hand since your right hand is your right hand. Another trick might be that your right hand is perchance weaker than your left hand, thus if an object was heavy, potentially you could hold it in your left hand, but you could not do so with your less powerful right hand.