Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
When we are in the outdoors, many of us often feel the need for a camera- that is intelligent enough to follow us, adjust to the terrain heights and visually navigate through the obstacles, while capturing panoramic videos. Here, I am talking about autonomous self-flying drones, very similar to cars on auto pilot. The difference is that we are starting to see proliferation of artificial intelligence into affordable, everyday use cases, compared to relatively expensive cars. This helps them distinguish between objects and get better with more data. Recently, Roni Fontaine at Hortonworks published a blog titled "How Apache Hadoop 3 Adds Value Over Apache Hadoop 2", capturing the high-level themes.
Today robotics is a vibrant field of research and it has tremendous application potentials not only in the area of industrial environment, battle field, construction industry and deep sea exploration but also in the household domain as a humanoid social robot. To be accepted in the household, the robots must have a higher level of intelligence and they must be capable of interacting people socially around it who is not supposed to be robot specialist. All these come under the field of human robot interaction (HRI). Our hypothesis is- "It is possible to design a multimodal human robot interaction framework, to effectively communicate with Humanoid Robots". In order to establish the above hypothesis speech and gesture have been used as a mode of interaction and throughout the thesis we validate our hypothesis by theoretical design and experimental verifications.
Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.
The world's second-largest economy, China, is en route to achieving great things in the next decade and a half. Projections suggest that by 2032, the Chinese Republic will overtake the United States and become the largest economy in the world. This is a far cry from the China of the '70s before which it was a largely agrarian society. After the introduction of economic reforms in 1978 by Deng Xiaoping and the reopening of Shanghai Stock Market in 1990, China evolved into an industrial powerhouse and its economy started expanding at a brisk pace, averaging growth rates of nearly 10 per cent for almost three decades. Though the benefits of growth in GDP did trickle down to the public as wages and subsequently living standards received a considerable bump, it was largely the Communist Party-controlled state machinery and the People's Liberation Army (PLA) that enjoyed the fruits of China's meteoric growth.