France is integrating new AI tools into security cameras in the Paris metro system to check whether passengers are wearing face masks. The software, which has already been deployed elsewhere in the country, began a three-month trial in the central Chatelet-Les Halles station of Paris this week, reports Bloomberg. French startup DatakaLab, which created the program, says the goal is not to identify or punish individuals who don't wear masks, but to generate anonymous statistical data that will help authorities anticipate future outbreaks of COVID-19. "We are just measuring this one objective," DatakaLab CEO Xavier Fischer told The Verge. "The goal is just to publish statistics of how many people are wearing masks every day."

Their study, published today in Science Advances, is the first to apply an experimentally validated machine learning method to rapidly design and develop advanced gas separation membranes. "Our work points to a new way of materials design and we expect it to revolutionize the field," says the study's PI Sanat Kumar, Bykhovsky Professor of Chemical Engineering and a pioneer in developing polymer nanocomposites with improved properties. Plastic films or membranes are often used to separate mixtures of simple gases, like carbon dioxide (CO2), nitrogen (N2), and methane (CH4). Scientists have proposed using membrane technology to separate CO2 from other gases for natural gas purification and carbon capture, but there are potentially hundreds of thousands of plastics that can be produced with our current synthetic toolbox, all of which vary in their chemical structure. Manufacturing and testing all of these materials is an expensive and time-consuming process, and to date, only about 1,000 have been evaluated as gas separation membranes.

As we continue to navigate our way through unknown territory, with lockdown in full swing around the world, the Coronavirus pandemic is changing online behaviours significantly and possibly permanently both for consumers and businesses. People have been forced to access information in new ways, interact and purchase new and different products and services online, and the longer this continues, the more likely these are to become habits. So I thought I would take this opportunity to explain what it might mean for businesses and recruitment in a short to longer timeframe as we progress through lockdown. My fellow co-founder at Leadoo Marketing Technologies, Mikael de Costa is author of The Startup Warrior and a multiple entrepreneur in our native Finland including founding Jobilla which was a recruitment digital marketing venture. Launching Leadoo MT, which concentrates on website conversion by engaging in chat bot conversations with customers, was born from Mikael's recruitment experience as he discovered that talent marketing and employer branding efforts were going to waste, as potential applicants were not converting.

It automates the process by which companies and website owners make their content accessible to users with hearing, visual, and motor impairments as well as some other functional disabilities. The total funding company raised is $12.5M in funding over 2 rounds. It's an AI-based solution scans website and automatically offers key modifications to transmit data and accessible content to end-users in a manner compliant with the international and US disability standards, which includes the Web Content Accessibility Guidelines and the Americans with Disabilities Act. Executive Opinion Shir Ekerling, Co-founder and CEO of accessiBe, said, "What excites us most about our partnership with K1 is that now, with the amazing support of our investors, we can bring accessibility to the world. Our vision is to make the internet truly accessible to everyone. By utilizing machine learning, our solution can help millions of businesses comply with legislation and avoid lawsuits on the one hand, while enabling users with disabilities to browse the internet effectively on the other. Mike Velcich, Principal at K1, said, "K1 is excited to partner with Shir Ekerling and the accessiBe team as they continue their rapid global expansion.

Members get 60 days free site access, $6.95/article thereafter. Airbnb is colliding with traditional hotel companies like Marriott International and Hilton. In just over a decade, the online lodging marketplace has assembled an inventory of more than 7 million rooms -- six times as much lodging capacity as Marriott managed to accumulate over 60-plus years. In terms of U.S. consumer spending, Airbnb overtook Hilton in 2018 and is on track to move ahead of Marriott.1 Although Airbnb serves similar consumer needs, it is a completely different kind of company.

Artificial intelligence (AI) comprises a type of computer science that develops entities, such as software programs, that can intelligently perform tasks or make decisions.1 The development and use of AI in health care is not new; the first ideas that created the foundation of AI were documented in 1956, and automated clinical tools that were developed between the 1970s and 1990s are now in routine use. These tools, such as the automated interpretation of electrocardiograms, may seem simple, but are considered AI. Today, AI is being harnessed to help with "big" problems in medicine -- such as processing and interpreting large amounts of data in research and in clinical settings, including reading imaging or results from broad genetic-testing panels.1 In oncology, AI is not yet being used broadly, but its use is being studied in several areas.

HealthMap uses artificial intelligence and data mining to spot disease outbreaks and issue location-specific alerts (colored dots) on COVID-19 and other diseases. It sounded an early alarm on the pandemic. Science's COVID-19 reporting is supported by the Pulitzer Center. The international alarm about the COVID-19 pandemic was sounded first not by a human, but by a computer. HealthMap, a website run by Boston Children's Hospital, uses artificial intelligence (AI) to scan social media, news reports, internet search queries, and other information streams for signs of disease outbreaks.

If artificial intelligence truly becomes intelligent, the computer brains of the future will be AC/DC fans, won't they? They might even start their own tribute bands – and if they take it a step further and start writing their own songs, the results could sound like a new track created by YouTuber Funk Turkey called "Great Balls." The song was assembled after he put all of AC/DC's lyrics through a Markov chain. The modeling software is normally used for complex analysis of things like predicting thermodynamic states, DNA evolution, solar panel efficiency, computer speech recognition, web-surfing behavior and stock market trends. "I put the lyrics of AC/DC into a bot and asked it to write a song," Funk Turkey explained.

The new dataset contains more than 1,000 anonymised sets of chest CT scans. This expands on the earlier database of CT studies of patients with laboratory-confirmed infection created by scientists at the Diagnostics and Telemedicine Centre. The data set aims to inform AI to diagnose COVID-19. The dataset is the largest to date, and all CT studies in the dataset have a special marking made according to the classification, which reflects the manifestation of pathological abnormalities of COVID-19 in the lung tissue based on the chest computed tomography. According to experts at the Diagnostics and Telemedicine Center, a database with CT scans converted into the'research' Neuroimaging Informatics Technology Initiative (NIFTI) format is intended for developing artificial intelligence algorithms.

Latanya Sweeney is a professor of government and technology in residence at Harvard University's Department of Government, editor-in-chief of Technology Science and the founding director of the Technology Science Initiative and the Data Privacy Lab at the Institute for Quantitative Social Science at Harvard. Max Weiss is a senior at Harvard University and the student who implemented the Deepfake Text experiment. As federal agencies take increasingly stringent actions to try to limit the spread of the novel coronavirus pandemic within the U.S., how can individual Americans and U.S. companies affected by these rules weigh in with their opinions and experiences? Because many of the new rules, such as travel restrictions and increased surveillance, require expansions of federal power beyond normal circumstances, our laws require the federal government to post these rules publicly and allow the public to contribute their comments to the proposed rules online. But are federal public comment websites -- a vital institution for American democracy -- secure in this time of crisis?