Recently, scientist Gagandeep Kang had to forcefully remind a room full of senior colleagues -- all men -- that she was the chair and that they should speak only when their turn comes. This kind of thing happens all the time, and you become so inured to it that you don't realise it," she says. Kang is the first Indian woman to be elected as a fellow of the Royal Society, but even that, evidently, does not protect you from microaggressions from men. It is a reminder of the kind of bias that women in science have to deal with. Prejudice at many levels is one reason why there are far fewer women scientists than men in the higher echelons of science in India. A 2016-17 report, "Status of Women in Science Among Select Institutions in India: Policy Implications", supported by NITI Aayog, found that while women constitute over a third of science graduates and postgraduates, they make up only 15-20% of tenured faculty across research institutions and universities in India. "As a group, it is not easy for women to stay in science. Only 14% of scientists are women," science writers Nandita Jayaraj and Aashima Dogra write in their recent book, 31 Fantastic Adventures in Science: Women Scientists in India. However, there are women who have beaten odds and shattered stereotypes and glass ceilings. This special feature looks at nine such women who are doing critical work in science and technology in India. They work on an array of complex problems -- in fields ranging from quantum computation to paleoecology. Neuroscientist Vidita Vaidya is looking to decode how experiences and the environment affect the circuits in our brain, which might offer a clue to how we develop psychiatric disorders. Aditi Sen De, the first woman to receive the Shanti Swarup Bhatnagar Prize in physical sciences, is working on different aspects of quantum communication, a field that uses the laws of quantum physics to protect data. This is by no means an exhaustive list of exceptional women scientists, but they are representative of the brilliant minds that have striven and made it to the top and become exemplars. As Kang says, "If you see role models, you see areas you can aspire to.

File photo - A Microsoft delegate takes a picture during the launch of the Windows 10 operating system in Kenya's capital Nairobi, July 29, 2015. Some users love it while others hate it. Some experts estimate that Windows 10 dominates nearly 40 percent of the desktop OS market, handily surpassing the popularity of Windows 7. Speaking of, are you still using Windows 7? Microsoft is ending support for the 10-year-old operating system in January. Tap or click to learn how to bring your PC up to date before it's too late. Using the slogan "upgrade your world," Microsoft has described Windows 10 as the "final" version.

The graph represents a network of 2,418 Twitter users whose tweets in the requested range contained "#FinServ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 27 November 2019 at 20:47 UTC. The requested start date was Monday, 25 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 5-day, 4-hour, 57-minute period from Tuesday, 19 November 2019 at 20:03 UTC to Monday, 25 November 2019 at 01:01 UTC.

This paper studies the optimality of kernel methods in high-dimensional data clustering. Recent works have studied the large sample performance of kernel clustering in the high-dimensional regime, where Euclidean distance becomes less informative. However, it is unknown whether popular methods, such as kernel k-means, are optimal in this regime. We consider the problem of high-dimensional Gaussian clustering and show that, with the exponential kernel function, the sufficient conditions for partial recovery of clusters using the NP-hard kernel k-means objective matches the known information-theoretic limit up to a factor of $\sqrt{2}$ for large $k$. It also exactly matches the known upper bounds for the non-kernel setting. We also show that a semi-definite relaxation of the kernel k-means procedure matches up to constant factors, the spectral threshold, below which no polynomial-time algorithm is known to succeed. This is the first work that provides such optimality guarantees for the kernel k-means as well as its convex relaxation. Our proofs demonstrate the utility of the less known polynomial concentration results for random variables with exponentially decaying tails in a higher-order analysis of kernel methods.

Moving Object Detection (MOD) is a critical task for autonomous vehicles as moving objects represent higher collision risk than static ones. The trajectory of the ego-vehicle is planned based on the future states of detected moving objects. It is quite challenging as the ego-motion has to be modelled and compensated to be able to understand the motion of the surrounding objects. In this work, we propose a real-time end-to-end CNN architecture for MOD utilizing spatio-temporal context to improve robustness. We construct a novel time-aware architecture exploiting temporal motion information embedded within sequential images in addition to explicit motion maps using optical flow images.We demonstrate the impact of our algorithm on KITTI dataset where we obtain an improvement of 8% relative to the baselines. We compare our algorithm with state-of-the-art methods and achieve competitive results on KITTI-Motion dataset in terms of accuracy at three times better run-time. The proposed algorithm runs at 23 fps on a standard desktop GPU targeting deployment on embedded platforms.

Success in any area is often a combination of three things: talent, hard work and perseverance. For software-as-a-service (SaaS) company Darts-ip, all three were needed to grow a pioneering idea from a handful of people to a 300-strong organisation in just 13 years. The talent came in the form of two groups from very different industries. The service they wanted to offer, to make legal research as easy as possible, came from trademark lawyer and Darts-ip founder Jean-Jo Evrard. While working in Brussels and Paris for law firm NautaDutilh, Evrard was frustrated.

For some, the spread of artificial intelligence and robotics poses a threat to our privacy, our jobs – even our safety, as more and more tasks are handed over to silicon-based brains. But even the most vocal critics highlight the potential good that AI and automated systems could do for humanity. As part of BBC Future Now's Grand Challenges, a panel of experts recently described how they saw our world changing as the machines we use grow smarter. Now, in our Grand Ideas series, BBC Future Now has sought out projects where advanced AI and automation is already beginning to tackle some of the world's knottiest, and dangerous, problems, from illnesses to violence. "We should view AI not as something competing with us, but as something that can amplify our own capabilities," says Takeo Kanade, a professor of robotics at Carnegie Mellon University.

For more than 4,000 years, the advertising industry has been defined by new technologies that allow companies, governments and individuals to attract and retain the interest of their target audiences. In Egypt, papyrus was used to deliver some of the world's first commercial advertising in poster form. The first ever advertising "jingle" or sonic logo was the result of ladies of the night in 750 BC Greece hammering nails into their shoes to produce a distinctive tone to attract clients. The advent of the printing press, radio, television, and now the internet and social media have all radically changed the way in which products are sold. In the mid-1990s, as companies and organisations began recognising the internet's potential as a marketing tool, huge amounts of time and money were poured into establishing online footprints.

How ready is India for the world of artificial intelligence (AI)? This question is answered in one of the latest global lists researched and created by Oxford Insights and commissioned by Canada's International Development Research Centre. It is called the Government Artificial Intelligence Readiness Index. The just released index measures 194 countries on a scale of 1-10 on how ready their governments are to embrace and make use of a world dominated by artificial intelligence. At the very top of the list is Singapore with a score of 9.186 and at the bottom is Somalia which scores 0.168. This kind of ranking is critical to understand the adoption of a technology which has, famously, been described as the'next electricity' or as fundamental as electricity by Andrew Ng, co-founder of Coursera and former head of Google Brain.

A Chinese firm has signed a Memorandum of Understanding (MoU) with Ethiopia authorities on establishing a National Artificial Intelligence Infrastructure (NAIF) in Ethiopia, reported state media outlet Ethiopia News Agency (ENA) on Saturday. The MoU was signed between Ethiopia Innovation and Technology State Minister, Sisay Tola and Chen Kuan, the founder and CEO of Chinese firm Infervision Technology Corporation in Ethiopia's capital Addis Ababa on Friday evening, reported ENA. Ethiopia hopes the partnership with Infervision will boost the technological capacity of its education, health care and medical services. Ethiopia also hopes the partnership will facilitate a platform for exchange of ideas and investment opportunities between enterprises of both countries in various sectors including energy, textile, agriculture, construction and information technology. Ethiopia and China have recently signed various agreements in the Information Communication and Technology (ICT), as Ethiopia looks to modernize its largely agrarian economy.