Carbon sequestration Cutting greenhouse-gas emissions alone won't be enough to prevent sharp increases in global temperatures. We'll also need to remove vast amounts of carbon dioxide from the atmosphere, which not only would be incredibly expensive but would present us with the thorny problem of what to do with all that CO2. A growing number of startups are exploring ways of recycling carbon dioxide into products, including synthetic fuels, polymers, carbon fiber, and concrete. That's promising, but what we'll really need is a cheap way to permanently store the billions of tons of carbon dioxide that we might have to pull out of the atmosphere. Grid-scale energy storage Renewable energy sources like wind and solar are becoming cheap and more widely deployed, but they don't generate electricity when the sun's not shining or wind isn't blowing. That limits how much power these sources can supply, and how quickly we can move away from steady sources like coal and natural gas.

Arthritis is not just an ailment of old age--it can affect children too, causing lifelong pain and disability in its most severe forms. Fortunately, some kids grow out of it. Knowing which patients will develop milder forms of disease could spare them unnecessary treatment and potential medication side effects but currently doctors have no way of predicting disease course or severity. That could now change thanks to a machine learning tool developed by Quaid Morris, a professor of computer science at the Donnelly Centre for Cellular and Biomolecular Research at the University of Toronto, Dr. Rae Yeung, Professor of Paediatrics, Immunology and Medical Science at the University of Toronto, and their recently-graduated, co-supervised student Simon Eng. Morris is also faculty in the Vector Institute for Artificial Intelligence and is an inaugural AI Chair by the Canadian Institute for Advancement of Research.

When mapping the universe, it pays to have some smart programming. Experts share how machine learning is changing the future of astronomy. Astronomy is one of the oldest sciences and the first science to incorporate maths and geometry. It sits at the centre of humankind's search for its place in the universe. As we delve deeper into the space surrounding our planet, the tools we use become more complex.

Name: Dr. Catherine Huang Topic: How can we work towards security in machine learning Date of Webinar: 21st March, 2019 Time and Location: 9pm PST / 9:30am IST/ 6:00am GMT Speaker Bio: Dr. Catherine Huang is a Principal Engineer in McAfee LLC. Her expertise is adversarial machine learning, deep learning and artificial intelligence for security applications. Catherine is currently the chair of IEEE Cognitive and Developmental Systems Technical Committee and a member of IEEE Neural Networks Technical Committee and IEEE Machine Learning for Signal Processing Technical Committee. Previously, Catherine was a Senior Research Scientist at Security & Privacy Research in Intel Labs. She directed ML research at the Intel Science and Technology Center for Security Computing in University of California Berkeley from 2015 to 2016.

Name: Dr. Catherine Huang Topic: How can we work towards security in machine learning Date of Webinar: 21st March, 2019 Time and Location: 9pm PST / 9:30am IST/ 6:00am GMT Speaker Bio: Dr. Catherine Huang is a Principal Engineer in McAfee LLC. Her expertise is adversarial machine learning, deep learning and artificial intelligence for security applications. Catherine is currently the chair of IEEE Cognitive and Developmental Systems Technical Committee and a member of IEEE Neural Networks Technical Committee and IEEE Machine Learning for Signal Processing Technical Committee. Previously, Catherine was a Senior Research Scientist at Security & Privacy Research in Intel Labs. She directed ML research at the Intel Science and Technology Center for Security Computing in University of California Berkeley from 2015 to 2016.

When it comes to Sci-Fi movies, artificial intelligence (AI) is one of Hollywood's go-to themes. As a technology of which we're still yet to fully realize the potential, scriptwriters and technology doomsdayers have been busy predicting a time when AI spins out of our control, and we're forced to welcome our robot overlords. But how accurate are some of pop culture's most well-known AI creations? Communications provider Plusnet sought to find out by asking Peter Scott, an author on AI and former computer scientist at NASA, to grade the AI predictions of some of Sci-Fi greatest movies. Ridley Scott's 80s Sci-Fi masterpiece may be held in the highest esteem in film circles, but when it comes to how well it predicts the direction of artificial intelligence, experts find it wanting. Set in 2019, the film is making a prediction 37 years in the future (45 years if you count the release date of the original book on which it's based).

Gate's new operating system increases motion responsiveness, faster video capture, improved Wi-Fi performance, and power savings in all Gate video smart locks. SAN FRANCISCO, March 1, 2019 -- Gate Labs, Inc., the home security company that manufactures the world's first all-in-one video smart lock, announced a second generation of its operating system for its flagship smart lock product, Gate. The Gate Smart Lock combines a set of features not found in other devices on the market, such as the live video and audio streaming of events taking place outside and inside the home. This update is designed to make everyday functionality faster and more reliable. Users can now select from three settings (high, medium, and low) on the Gate App to adjust motion sensitivity to best fit their particular door environment.

Hyundai Mobis is accelerating for a full-scale collaboration with high-tech companies to become a global technology leader by reinforcing its competence in core technologies for future automotive vehicles. In this line the company announced equity investment of to USD 5 million in China's Deep Glint, to build a strategic partnership. Deep Glint is a Chinese startup specializing in computer vision technology utilizing artificial intelligence. The company is known for its technology in recognizing and analyzing facial, body, and behavior patterns of individuals. The company claims its AI-based object recognition and analysis system to be quick and accurate enough to correctly recognize a face of a target person among 1 billion people from a distance of 50m, within 1 second.

CropIn, a leading SaaS solutions provider to agribusinesses globally, has won the AI Innovation Challenge 2019, organised by the Government of Maharashtra and NITI Aayog, in association with NASSCOM. The challenge was held earlier this month at Taj Vivanta, Mumbai. The AI Innovation Challenge is a platform for AI-based organisations to showcase their solutions and to collaborate with the Government of Maharashtra on a proof of concept. In January 2019, Government of Maharashtra had invited applications from enthusiastic and passionate organisations from across India, that have developed artificial intelligence (AI) based solutions for social problems, to collaborate and partner with the Government in areas that include, but are not limited to agriculture, healthcare, education, smart mobility and water management. Speaking on the challenge, Krishna Kumar, CEO & Founder, CropIn said, "We are happy to win the AI Innovation Challenge 2019 conferred by the Government of Maharashtra. This will be a great opportunity for us to work for a social cause for the farmers in Maharashtra. Making agriculture more predictable is the need of the hour and only technological disruptions can create impact at scale."

IMAGE: The heatmap shows quite clearly that the algorithm makes its ship/not ship decision on the basis of pixels representing water and not on the basis of pixels representing the ship.... view more Artificial Intelligence (AI) and machine learning algorithms such as Deep Learning have become integral parts of our daily lives: they enable digital speech assistants or translation services, improve medical diagnostics and are an indispensable part of future technologies such as autonomous driving. Based on an ever increasing amount of data and powerful novel computer architectures, learning algorithms appear to reach human capabilities, sometimes even excelling beyond. The issue: so far it often remains unknown to users, how exactly AI systems reach their conclusions. Therefore it may often remain unclear, whether the AI's decision making behavior is truly'intelligent' or whether the procedures are just averagely successful. Researchers from TU Berlin, Fraunhofer Heinrich Hertz Institute HHI and Singapore University of Technology and Design (SUTD) have tackled this question and have provided a glimpse into the diverse "intelligence" spectrum observed in current AI systems, specifically analyzing these AI systems with a novel technology that allows automatized analysis and quantification.