NEW DELHI: India and Germany will explore possibilities for cooperation in green urban mobility and Artificial Intelligence during their Fifth Biennial Inter Governmental Consultations (IGC) here on November 1. During the IGC led by top leaders, the two sides will also discuss the deepening of cooperation in traditional sectors such as transport, skill development and energy. Dr. Angela Merkel, Chancellor of Germany, will be accompanied by several Ministers and State Secretaries of the Federal Government, as well as a high-powered business delegation. Under the IGC format, the counterpart Ministers from both countries will hold initial discussions in their respective areas of responsibility. The outcome of these discussions will be reported on at the IGC Co-Chaired by the Prime Minister and the Federal Chancellor of Germany.

Thinking about a career in data science but not sure where to start? Check out these tips from those already working in the field. As we heard from Anaplan's Tal Sergalov, "being a data scientist doesn't mean sitting alone with your computer all day". So, what does it mean? And what are the skills you might need to carve out a successful career in this field? For Data Science Week at Siliconrepublic.com, we heard from a variety of experts in the area to bring you some valuable inside knowledge.

Work has gone digital, paper is still important, but process intelligence sits at a higher level. Organizations in every vertical have always relied upon a certain quantity of paper since the dawn of known time and, despite the rise of digital, that basic truth isn't going to change. Although invoices are now largely digital, boarding passes live on smartphones and there's even an app (or two) for To-Do lists and notepads, a certain amount of paper will always feature as part of any firm's operational procedures. While the Western world replaces some of its paper consumption with technology, business growth in developing nations and the use of paper in packaging is thought to offset the trend for digitization. If we accept these basic propositions, then it should logically follow that the technology industry seeks to provide solutions to working with information in its digital form.

NEW DELHI – The body of a 2-year-old boy trapped 26-meters (85-feet) down a well in southern India for more than three days was recovered on Tuesday, authorities said. Sujith Wilson was the second toddler in four months to grab nationwide attention after falling into the 30-centimeter (one-foot) diameter pipe while playing near his home in Tiruchirappalli district of Tamil Nadu state on Friday. "The body was retrieved using special equipment and he was in a decomposed state," district official S. Sivarasu told journalists. He added that a post-mortem examination would be carried out to determine the cause of death. A thermal camera had been used to monitor the child's temperature while oxygen was supplied through a pipe.

Ernesto Estrada is ARAID researcher at the Institute of Mathematics and Applications (IUMA) at the University of Zaragoza since January 2019. Before he was the Chair of Complexity Science at the University of Strathclyde in Glasgow. He works on the mathematics of networks where he has published more than 200 papers which have received more than 12,500 citations, and his h-index is 59. He is SIAM Fellow, Member of the Academy of Sciences of Latin America, and was a recipient of the Wolfson Research Merit Award of the Royal Society of London among other distinctions. He is the Editor in Chief of the Journal of Complex Networks (Oxford University Press), and Associate Editor of SIAM Journal of Applied Mathematics and of Proceedings of the Royal Society A. He has given plenary talks at many international conferences in applied mathematics and on network sciences, and he is frequently a lecturer at major international schools on these topics.

The tech giants Amazon, Google and Facebook have all begun to use machine learning to give you tips on what to wear. Is fashion styling the next field to be disrupted by artificial intelligence (AI), or will the human eye remain supreme? It's too soon to know for sure, but understanding what machine learning is good at and how that overlaps with what fashion is all about can help us make some educated guesses. One thing machine learning does very well is finding patterns and common features among groups of items. Taking advantage of this, Google Lens and Amazon Style Snap can each identify a garment from a photo or video and then tell you a bit more, like how other people have worn it or where you can buy it.

Researchers at MIT are helping autonomous cars deliver on the promise of safer roads with a new trick that lets driverless vehicles see around corners to pre-emptively spot other vehicles or moving hazards that human drivers would never see coming. There have been several attempts to make cameras that are able to see around corners, including other MIT researchers who revealed a system that can shine light into a room from the outside, capture the light that's bounced back, and then process the results to calculate a 3D model of objects inside that are otherwise hidden from human observers. It required a special camera, however, including lasers and other hardware that would inevitably increase the cost of an autonomous vehicle, which would, in turn, hurt sales. You didn't think all these carmakers are developing driverless cars for fun, did you? The new approach to spotting oncoming hazards around corners is being presented at the International Conference on Intelligent Robots and Systems in Macau, China, next week, and it builds and improves on an earlier system called ShadowCam that was developed a few years prior.

WIRE)--Gradient AI, the leading enterprise software provider of artificial intelligence solutions in the insurance technology space, announced today that it has raised $6.0 million in a Series A financing led by Forte Ventures and Sandbox Insurtech Ventures. The round also includes participation from Gradient's existing investor MassMutual Ventures. Gradient's artificial intelligence helps commercial insurers automate and improve underwriting results, reduce claim costs, and improve operational efficiencies. The Gradient software-as-a-service (SaaS) platform boasts a proprietary dataset comprised of tens of millions of claims, which is complemented with several economic, health, and litigation datasets. This robust aggregation of data provides out-of-the-box claims and underwriting precision for new clients, and it is continuously refined with client-specific data over time.

AI1 is advancing the way the public sector serves its constituents. In Singapore, AI-powered technologies are scanning the dark web to identify patterns that can help law enforcement officials to understand the illegal drug market, and are giving rise to "digital twin" models (virtual replicas of physical spaces) that simulate emergency situations.2 In other cities and regions around the world, similar stories are emerging: AI activities range from alerting refuse collectors when bins are full, and predicting the need for infrastructure repair, to improving energy efficiency through smart thermometers and powering advanced military security systems with drones. And AI is still in its early days. Governments ready to seize this growing opportunity are ramping up their spending on AI.

Pocket-size ultrasound devices that cost 50 times less than the machines in hospitals (and connect to your phone). These are just some of the innovations now transforming medicine at a remarkable pace. No one can predict the future, but it can at least be glimpsed in the dozen inventions and concepts below. Like the people behind them, they stand at the vanguard of health care. Neither exhaustive nor exclusive, the list is, rather, representative of the recasting of public health and medical science likely to come in the 2020s.