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AI named after V For Vendetta masks protects photos from being gathered by facial recognition apps

Daily Mail - Science & tech

Clearview AI is just one of many facial recognition firms scraping billions of online images to create a massive database for purchase – but a new program could block their efforts. Researchers designed an image clocking tool that makes subtle pixel-level changes that distort pictures enough so they cannot be used by online scrapers – and claims it is 100 percent effective. Named in honor of the'V for Vendetta' mask, Fawkes is an algorithm and software combination that'cloaks' an image to trick systems, which is like adding an invisible mask to your face. These altered pictures teach technologies a distorted version of the subject and when presented with an'uncloaked' form, the scraping app fails to recognize the individual. 'It might surprise some to learn that we started the Fawkes project a while before the New York Times article that profiled Clearview.ai in February 2020,' researchers from the SANLab at University of Chicago shared in a statement.


European Data Science Salary Report 2020 Key Insights » Big Cloud Big Cloud

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We've most certainly learnt a thing or two about what makes a thorough and informative salary report since conducting our first salary survey in 2017. Our European Salary Report for 2020 has seen a response of more than one thousand participants which has enabled us to provide a truly data rich and comprehensive insight on what the Data Science market currently looks like. The top countries to provide responses to our survey during 2019 came from Germany, France, Switzerland, The Netherlands and The UK. Much like our 2019 survey, many respondents were Data Scientists, but we've also collected results from Data Engineers, Researchers, Machine Learning Engineers and C-Level professionals. This report covers a broad scope of professions in the European data science market at all levels.


Planning law overhaul for England takes next step

BBC News

Sweeping changes to England's planning system will "cut red tape, but not standards," Housing Secretary Robert Jenrick has said. Under draft new laws, first revealed on Sunday, developers will be granted "automatic" permission to build homes and schools on sites for "growth". It follows Boris Johnson's pledge to "build back better" after coronavirus. But critics warn it could lead to "bad-quality housing" and loss of local control over development. Mr Johnson promised to speed up investment into homes and infrastructure in June to help the UK recover from the economic impact of coronavirus.


Machine learning methods provide new insights into organic-inorganic interfaces

#artificialintelligence

Oliver Hofmann and his research group at the Institute of Solid State Physics at TU Graz are working on the optimization of modern electronics. A key role in their research is played by interface properties of hybrid materials consisting of organic and inorganic components, which are used, for example, in OLED displays or organic solar cells. The team simulates these interface properties with machine-learning-based methods. The results are used in the development of new materials to improve the efficiency of electronic components. The researchers have now taken up the phenomenon of long-range charge transfer.


Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT

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To present a method that automatically segments and quantifies abnormal CT patterns commonly present in coronavirus disease 2019 (COVID-19), namely ground glass opacities and consolidations. In this retrospective study, the proposed method takes as input a non-contrasted chest CT and segments the lesions, lungs, and lobes in three dimensions, based on a dataset of 9749 chest CT volumes. The method outputs two combined measures of the severity of lung and lobe involvement, quantifying both the extent of COVID-19 abnormalities and presence of high opacities, based on deep learning and deep reinforcement learning. The first measure of (PO, PHO) is global, while the second of (LSS, LHOS) is lobe-wise. Evaluation of the algorithm is reported on CTs of 200 participants (100 COVID-19 confirmed patients and 100 healthy controls) from institutions from Canada, Europe and the United States collected between 2002-Present (April 2020).


AI Chip Startup Syntiant Scales Production

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Syntiant Corp., the "neural decision processor" startup, announced completion of another funding round this week along with the shipment of more than 1 million low-power edge AI chips. The three-year-old startup based in Irvine, Calif., said Tuesday (Aug. The round was led by Microsoft's (NASDAQ: MSFT) venture arm M12 and Applied Ventures, the investment fund of Applied Materials (NASDAQ: AMAT). New investors included Atlantic Bridge Capital, Alpha Edison and Miramar Digital Ventures. Intel Capital was an early backer of Syntiant, part of a package of investments the chip maker announced in 2018 targeting AI processors that promise to accelerate the transition of machine learning from the cloud to edge devices.


Artificial intelligence-enhanced ECGs may speed heart failure diagnosis and treatment – BioNews Central

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When people seek emergency care for shortness of breath, a routine electrocardiogram (ECG or EKG) enhanced by artificial intelligence (AI) is better than standard blood tests at determining if the cause is heart failure, according to new research published today in Circulation: Arrhythmia and Electrophysiology, an American Heart Association journal. "Determining why someone has shortness of breath is challenging for emergency department physicians, and this AI-enabled ECG provides a rapid and effective method to screen these patients for left ventricular systolic dysfunction," said Demilade Adedinsewo, M.D., M.P.H., lead author of the study and chief fellow in the division of cardiovascular medicine at Mayo Clinic in Jacksonville, Florida. The left ventricle supplies most of the heart's pumping power, so it is larger than the other chambers and essential for normal function. In left ventricular systolic dysfunction (LVSD), the left ventricle is weakened and must work harder to maintain adequate blood flow to the body. In a typical year, about 1.2 million people go to emergency departments because they are short of breath.


Cisco challenge winners use AI, IoT to tackle global problems

#artificialintelligence

An IoT-enabled system for transporting dairy products earned its designers the top prize in a competition run by Cisco. The Global Problem Solver Challenge, which is one of Cisco's corporate social responsibility (CSR) initiatives, pays cash awards to entrepreneurial companies using technology to solve the world's biggest challenges. The program also gives out four $25,000 awards and seven $10,000 prizes. This year, I was honored to be invited to help judge the 2020 winners. In full disclosure, I agreed to be a judge but I received no compensation, as I believe we all have to work together to make the world a better place.


Tamr Helps Air Force Wrangle Data

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Data prepper Tamr Inc. will assist the U.S. Air Force in boosting utilization of its air assets under a five-year contract designed to use machine learning techniques to accelerate the flight certification process for new aircraft configurations. Those configurations include equipping front-line aircraft with new weapons, sensors and defenses such as electronic warfare pods. Tamr said the contract with the Air Force's Seek Eagle Office could be worth as much $60 million. The office based at Eglin Air Force Base, Fla., is responsible for integration new technologies into front-line aircraft. The Air Force office will use Tamr's machine learning platform to organize more than 30 years of aircraft performance studies dispersed across the organization.


GSTS awarded contribution for Space-Based Artificial Intelligence

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HALIFAX, NS, Aug. 4, 2020 /CNW/ - Global Spatial Technology Solutions ("GSTS" or "the Company") an Artificial Intelligence (AI) and Maritime Analytics company today announced that it has been selected by the Canadian Space Agency (CSA) to develop space-based AI capability to support enhanced decision-making for a range of space applications focused on tasks using computer vision (such as would be used by exploration landers, rovers, robotics or Earth observation systems). This project is funded under the Space Technology Development Program. "This contribution will enable GSTS to expand our growing AI capabilities into the space sector to support decision making based on the same techniques we utilize in the maritime domain, enabling detection, recognition and prediction," said Richard Kolacz, GSTS CEO. "It is equivalent to placing the brain next to the eyes of any space asset or sensor in order to support decision-making locally, rather than having to relay all the data to Earth for analysis before a decision can be made. It is the first step in the development of truly autonomous space capability." Computer vision involves the automatic extraction, analysis and understanding of information gleaned from digital images. By applying machine learning, which is a type of AI, it can enhance and optimize the production of actionable insights much faster and more accurately than a human can.