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Finance

AI to Plug FX Liquidity Gaps

UBS is utilising machine learning technology to carry on dealing. UBS’s ORCA-Direct learns in real time, utilising historical trading data to find the bank’s clients the best available liquidity when volatility rises. ORCA’s machine learning enables the algorithm to determine within microseconds the best platforms and execution sequence to use, estimating the probability of trading and market impact for each specific order and reducing costs for the bank’s client. That can be crucial in the fragmented currency market, where about 70 different platforms exist with multiple banks, hedge funds and technology firms jostling for market share. The growing number of flash crashes – where prices of currencies can swing wildly within seconds – also complicates matters. The bank expanded ORCA to US Treasury trading in late 2018, with further roll-outs expected in the foreign exchanges, rates and credit space. Read More

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Agriculture

AI Can Pick Tomatoes More Efficiently Than Humans

Root AI’, a start-up in Somerville, Massachusetts, has created an agricultural robot called Virgo 1. The robot can pick tomatoes without bruising them and detects ripeness better than humans. The Virgo is a self-driving robot with sensors and cameras that serve as its eyes. Because it also has lights on board, it can navigate large commercial greenhouses any hour of the day or night, detecting which tomatoes are ripe enough to harvest. A “system-on-module” runs the Virgo’s AI-software brain. A robotic arm, with a dexterous hand attached, moves gently enough to work alongside people and can independently pick tomatoes without tearing down vines. The robot’s “fingers” are made of a food-safe plastic that’s about as flexible as a credit card and can be easily cleaned. One of the most unique things about the Virgo is that the company can write new AI software and add additional sensors or grippers to handle different crops. The robot has already been tested at commercial greenhouses, including in the US and Canada. Read More

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Brewing

Now an AI Created Whisky!

Swedish distillery, Mackmyra is teaming up with Microsoft and Fourkind, a Finnish technology consultancy, to use AI develop a special whiskey recipe. The first AI assisted whisky is a single-malt with herbal notes of aniseed, ginger, and white pepper and a citrusy, spicy mouth with a dry finish. An AI algorithm which is running from Microsoft's Azure cloud platform and AI cognitive services will be fed raw data including the distillery’s legacy recipes, sales numbers and customer preferences. The algorithm can then generate more than 70 million recipes, that should be both popular and tasty. The goal of the project is to find new combinations of techniques and ingredients that humans wouldn’t think about themselves. The AI can be taught to understand what elements previous recipes and products are made of and how they are perceived and ranked by customers and experts. With this as a raw data asset, a combination of explorative algorithms can be leveraged to generate endless new recipes and products and then use a set of discriminative algorithms to understand which of them might be great. Read More

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Healthcare

AI System to Predict Heart Attack Better Than Humans

Scientists have developed an AI system that is better than human doctors at predicting the risk of heart attack or death. By repeatedly analysing 85 variables in 950 patients with known six-year outcomes, an algorithm “learned” how imaging data interacts. It then identified patterns correlating the variables to death and heart attack with more than 90.0% accuracy. The study enrolled 950 patients with chest pain, who underwent the center's usual protocol to look for coronary artery disease. A coronary computed tomography angiography scan yielded 58 pieces of data on presence of coronary plaque, vessel narrowing, and calcification. Those with scans suggestive of disease underwent a positron emission tomography scan which produced 17 variables on blood flow. Ten clinical variables were obtained from medical records including sex, age, smoking and diabetes. During an average six-year follow-up there were 24 heart attacks and 49 deaths from any cause. The 85 variables were entered into a machine learning algorithm called LogitBoost, which analysed them over and over again until it found the best structure to predict who had a heart attack or died. Read More

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Governance

Confused by Congress’ Bills? Maybe AI Can Help

The US Congress officials are developing an AI tool to automate the process of analysing differences between bills, amendments and current laws. They are working on an “AI engine” that may be ready as soon as next year. The idea is to offer members and staff a tool that would accurately compare legislative text. The tool is already available to Office of Legislative Counsel staffers, who then must check the accuracy with human intelligence. It’s about 90% there. The AI project in the clerk’s office stems from House rules for the 115th Congress that called for more tools to help lawmakers, staff and the public understand legislative changes. Such technology could help lawmakers avoid unintended consequences when moving legislation. Read More

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Miscellaneous

AI Can Predict Opioid Overdoses From Crime

Researchers at the East Technical University in Turkey and the University of Pittsburgh have created an AI system capable of forecasting opioid overdoses. The researchers’ algorithm — CASTNet – identifies which local and global features are most predictive and isolate high-risk communities. The team employed two types of features to inform their AI’s projections: static and dynamic. The former included 2010 census data about economic statuses, education level and more, while the dynamic features captured per-neighborhood crime stats culled from public safety data portals. To keep the scope manageable, the team focused on two cities - Chicago and Cincinnati - for which they collected the geolocation, time, and category for each crime feature. For Chicago specifically, they collected opioid overdose death records from the open source Opioid Mapping Initiative Open Datasets, and for Cincinnati, they used the EMS response data. CASTNet achieved better performance than the baseline architecture against which it was tested and it selected crimes like “narcotics,” “assault,” “theft,” and “burglary” as the most important features for future opioid overdose deaths. Read More

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Miscellaneous

Hummingbird Robot Uses AI to Go Where Drones Can't

The AI Hummingbird robot has been developed by researchers at Purdue University. Scientists have used machine learning algorithms to study the way these birds fly in order to replicate their abilities in drones. This is useful because of limitations on how small a drone can be made. However, hummingbirds move with a high angle of attack. This research involved the researchers spending multiple summers observing hummingbirds in their natural habitats and translating their movements to computer algorithms. The robot could then learn from these algorithms and work out the most effective ways to use its wings. The robot is made from carbon fiber and membranes which are cut with lasers and its body is 3D-printed. This means the hummingbird robot weighs only 12 grams and the researchers also created an insect-sized robot which weighed just 1 gram. The small size and quiet operation of the robot makes it well suited for covert operations as well as search and rescue operations. The robot does not have visual sensors, but it uses changes in electrical current to track its movements around objects. Read More

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Miscellaneous

AI to Help Select Grant Reviewers in China

The National Natural Science Foundation of China (NSFC) is piloting an AI tool that selects researchers to review grant applications, in an attempt to make the process more efficient, faster and fairer. The NSFC is building a sophisticated system that will check online scientific literature databases and scientists’ personal web pages, using natural-language processing to glean detailed information about the publications or research projects of potential referees. The system will use semantic analysis of the text to compare the grant application with this information and identify the best matches. An early version of the tool selected at least one member of each of nearly 44,000 panels that approved projects last year. The NSFC’s pilot AI system works only on websites written in Chinese characters, but Li wants it to be able to check English-language websites in the future. Moreover, Li plans to introduce other tools to make the grant system fairer over the next five years. These include a credit system that will reward researchers for good, fair and timely reviews. Read More

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