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AI Researchers Estimate 97% Of EU Websites Fail GDPR Privacy Requirements- Especially User Profiling

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Researchers in the US have used machine learning techniques to study the GDPR privacy policies of over a thousand representative websites based in the EU. They found that 97% of the sites studied failed to comply with at least one requirement of the European Union's 2018 regulatory framework, and that they complied least of all with regulatory requirements around the practice of'user profiling'. '[Since] the privacy policy is the essential communication channel for users to understand and control their privacy, many companies updated their privacy policies after GDPR was enforced. However, most privacy policies are verbose, full of jargon, and vaguely describe companies' data practices and users' rights. Therefore, it is unclear if they comply with GDPR.' 'Our results show that even after GDPR went into effect, 97% of websites still fail to comply with at least one requirement of GDPR.'


Predicting Protein Interactions With Artificial Intelligence

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UT Southwestern and University of Washington researchers led an international team that used artificial intelligence (AI) and evolutionary analysis to produce 3D models of eukaryotic protein interactions. The study, published in Science, identified more than 100 probable protein complexes for the first time and provided structural models for more than 700 previously uncharacterized ones. Insights into the ways pairs or groups of proteins fit together to carry out cellular processes could lead to a wealth of new drug targets. "Our results represent a significant advance in the new era in structural biology in which computation plays a fundamental role," said Qian Cong, Ph.D., Assistant Professor in the Eugene McDermott Center for Human Growth and Development with a secondary appointment in Biophysics. Dr. Cong led the study with David Baker, Ph.D., Professor of Biochemistry and Dr. Cong's postdoctoral mentor at the University of Washington prior to her recruitment to UT Southwestern.


Machine Learning in Medicine -- Journal Club

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The use of machine learning techniques in biomedical research has exploded over the past few years, as exemplified by the dramatic increase in the number of journal articles indexed on PubMed by the term "machine learning", from 3,200 in 2015 to over 18,000 in 2020. While substantial scientific advancements have been made possible thanks to machine learning, the inner working of most machine learning algorithms remains foreign to many clinicians, most of whom are quite familiar with traditional statistical methods but have little formal training on advanced computer algorithms. Unfortunately, journal reviewers and editors are sometimes content with accepting machine learning as a black box operation and fail to analyze the results produced by machine learning models with the same level of scrutiny that is applied to other clinical and basic science research. The goal of this journal club is to help readers develop the knowledge and skills necessary to digest and critique biomedical journal articles involving the use of machine learning techniques. It is hard for a reviewer to know what questions to ask if he/she does not understand how these algorithms work.


Future Vision & Direction of AI Part II: Scaling AI Whilst Preventing a Big Brother World & Solving The Curse of the Modern Data Scientist

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Venture Capitalists are hoping to find the next superstar tech unicorn, AI startup founders dreaming of creating the next unicorn, and corporates adopting AI need to consider their data growth strategy in order to be able to scale their AI-enabled services or products. The past decade has been one of explosive growth in digital data and AI capabilities across the digital media and e-commerce space. And it is no accident that the strongest AI capabilities reside in the Tech majors. The author argues that there will be no AI winter in the 2020s as there was in 1974 and 1987 as the internet (social media and e-commerce) are so dependent upon AI capabilities and so too with being the Metaverse, and the era of 5G enabled Edge Computing with the Internet of Things (IoT). Furthermore, the following infographics illustrate how many people globally use social media and hence how central these channels have become to the everyday lives of people. Likewise, the size of the e-commerce market is vast. Although the era of standalone 5G networks may enable a window of opportunity for a new wave of consumer-facing applications in the business to consumer (B2C) in relation to e-commerce and perhaps even new digital media platforms that may challenge the current incumbents, after all the arrival of 4G provided a window for the likes of Airbnb, Uber, and leading social media platforms such as Facebook, Instagram, etc. to scale.


Alzheimer's: Daily power walks could help stave off the onset of disease, study claims

Daily Mail - Science & tech

A daily power walk or bike ride in old age may cut the risk of developing Alzheimer's disease, a study has claimed. Research has long shown exercise in middle age and beyond can cut the chance of dementia -- which is most commonly caused by Alzheimer's -- by up to 40 per cent. Now researchers from the University of California say the disease can be prevented if people exercise in later life as well. Exercise is thought to help stave off the disease because it improves cognitive function, keeps bodyweight low and prevents plaque forming in the arteries -- a key cause of vascular dementia. But the latest study also suggests exercise in later life can reduce inflammation in the brain, which can cause Alzheimer's to develop.


La veille de la cybersécurité

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A University of California-Berkeley study revealed that lenders charge higher rates to Black and Hispanic borrowers. According to the study, algorithmic strategic pricing uses machine learning to find shoppers who might do less comparison shopping and accept higher-priced offerings. This algorithm is biased against Blacks and Hispanics. Including the word "transgender" in video titles has resulted in YouTubers receiving lower ad revenue on their videos. Commented Meg Green, a user experience researcher for Rocket Homes, "Being gay or being Black or being a trans woman does not mean these things are negative and that you don't want to read this information. Anything about being bisexual and gay is pornographic and not acceptable for children, according to some biased data found with AI."


Research team makes considerable advance in brain-inspired computing: Introduces a more efficient and sustainable hardware device for AI and ML applications

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A lab, whose work is concentrated on neuromorphic computing or brain-inspired computing, has new research that introduces hardware improvements by harnessing a quality known as 'randomness' or 'stochasticity'. Their research contradicts the perception of randomness as a quality that will negatively impact computation results and demonstrates the utilization of finely controlled stochastic features in semiconductor devices to improve performing optimization. This has potential to create a more sophisticated building block for creating computers that can tackle sophisticated optimization problems, which can potentially be more efficient. What's more they can consume less power.


New microrobotic trajectory tracking method using broad learning system

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The use of magnetic microrobots with miniature size and the ability of swimming in liquids with low Reynolds numbers is promising in targeted therapy, since these robots can move in narrow environments flexibly. However, due to the impacts of the nonlinearity and diversity of the desired complex trajectories, it is a challenge to guarantee the microrobot tracking accuracy without frequent controller adjustment. Recently, a research team led by Xu Sheng and Xu Tiantian from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences has developed a new method based on broad learning system (BLS), which can realize accurate and flexible trajectory tracking of microrobot. The study was published in IEEE Transactions on Cybernetics on Nov. 1. Compared with the traditional deep learning method, BLS--which features a flexible and simple structure--could achieve satisfactory accuracy.


Scientists discover lie detector that uses artificial intelligence to detect micro-expressions

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In this file photo, a representative image of Artificial Intelligence can be seen. Scientists have discovered a new lie detector that can read facial muscles that people won't even know they are using. The study, conducted by the researchers at Tel Aviv University, has been in'Brain and Behaviour.' It was conducted on the basis of micro-expressions that vanish in 40 to 60 milliseconds due to which accuracy and speed played a key role. Also read Experts look to recycle dangerous space junk into rocket fuel in Earth's orbit ''Since this was an initial study, the lie itself was very simple,'' he added.


Robot's Delight: Japanese robots rap about their artificial intelligence

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"Robot's Delight – A Lyrical Exposition on Learning by Imitation from Human-Human Interaction" is a video submission that won Best Video at the 2017 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2017). The team also provides an in-depth explanation of the techniques and robotics in the video. Although social robots are growing in popularity and technical feasibility, it is still unclear how we can effectively program social behaviors. There are many difficulties in programming social robots -- we need to design hundreds or thousands of dialogue rules, anticipate situations the robot will face, handle common recognition errors, and program the robot to respond to many variations of human speech and behavior. Perhaps most challenging is that we often do not understand the reasoning behind our own behavior and so it is hard to program such implicit knowledge into robots.