I just finished my first course (fairly rigorous and comprehensive) in machine learning and would like to write a research paper. I'm only an undergrad, so I've never written one before, nor do I have the familiarity with the field to be able to publish. I thought a good way to address both these problems would be to read research papers for several months before I try my hand at a problem. I was hoping for some advice for going about this; would the ideal way be to just sort arXiv by new and read anything that catches my interest? I've heard about Google Scholar but the results seem to be a lot broader and unfocused.
He described what it would be like for Washington to witness the technology of our time: cars, airplanes, the international space station. You could tell him about the large hadron collider and the theory of relativity, said Urban, and play him music that was recorded 50 years ago. "And this is all before he's seen the internet," said Urban, "the magical wizard rectangle in my pocket that can do a trillion crazy levels of sorcery, like pull open a map that can show where we are on it with a paranormal blue dot." Or let you hold a conversation with someone in Japan, on the other side of the world.
NEW DELHI: Artificial Intelligence (AI) should be leveraged to provide quality solutions at scale across education, health, agriculture, infrastructure and mobility in smart cities, said Niti Aayog CEO Amitabh Kant. A paper titled'National Strategy for Artificial Intelligence', said, "AI for All will aim at enhancing and empowering human capabilities to address the challenges of access, affordability, shortage and inconsistency of skilled expertise." AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. In the paper, Niti Aayog has decided to focus on five sectors that includes healthcare, agriculture, education, infrastructure and transportation that can benefit from adoption of AI in solving societal needs. Aiming to truly reap benefits of using AI in all and across sectors, the paper has identified barriers that need to be addressed to achieve success in the use of AI.
The award is made to the technical paper which, according to the team of peer reviewers, delivers not just the most significant new research, but does so in an accessible way. The paper, 'AI in production: video analysis and machine learning for expanded live events coverage', will be presented at midday on Sunday 16 September as part of a new initiative at IBC2018 – 'Tech Talks'. 'Tech Talks' ensures that the highly respected technical papers remain an integral part of IBC and its conference, bringing the latest ideas to all delegates in a fresh and accessible form. Talking of the new innovation, Dr Nick Lodge, executive producer of technical sessions in the conference, said "Senior technologists and researchers who have been responsible for original and thought-provoking advances in media technology will talk about their own work, and audiences will have the rare opportunity to question these world experts. "The technologies that impact the media industry are broad," he added.