Imitation learning has been commonly applied to solve different tasks in isolation. This usually requires either careful feature engineering, or a significant number of samples. This is far from what we desire: ideally, robots should be able to learn from very few demonstrations of any given task, and instantly generalize to new situations of the same task, without requiring task-specific engineering. In this paper, we propose a meta-learning framework for achieving such capability, which we call one-shot imitation learning. Specifically, we consider the setting where there is a very large set of tasks, and each task has many instantiations. For example, a task could be to stack all blocks on a table into a single tower, another task could be to place all blocks on a table into two-block towers, etc. In each case, different instances of the task would consist of different sets of blocks with different initial states. At training time, our algorithm is presented with pairs of demonstrations for a subset of all tasks. A neural net is trained that takes as input one demonstration and the current state (which initially is the initial state of the other demonstration of the pair), and outputs an action with the goal that the resulting sequence of states and actions matches as closely as possible with the second demonstration. At test time, a demonstration of a single instance of a new task is presented, and the neural net is expected to perform well on new instances of this new task. The use of soft attention allows the model to generalize to conditions and tasks unseen in the training data. We anticipate that by training this model on a much greater variety of tasks and settings, we will obtain a general system that can turn any demonstrations into robust policies that can accomplish an overwhelming variety of tasks. Videos available at https://bit.ly/nips2017-oneshot .

In an era marked by rapid advances in automation and artificial intelligence, new research assesses the jobs lost and jobs gained under different scenarios through 2030. The technology-driven world in which we live is a world filled with promise but also challenges. Cars that drive themselves, machines that read X-rays, and algorithms that respond to customer-service inquiries are all manifestations of powerful new forms of automation. Yet even as these technologies increase productivity and improve our lives, their use will substitute for some work activities humans currently perform--a development that has sparked much public concern. Building on our January 2017 report on automation, McKinsey Global Institute's latest report, Jobs lost, jobs gained: Workforce transitions in a time of automation (PDF–5MB), assesses the number and types of jobs that might be created under different scenarios through 2030 and compares that to the jobs that could be lost to automation. The results reveal a rich mosaic of potential shifts in occupations in the years ahead, with important implications for workforce skills and wages. Our key finding is that while there may be enough work to maintain full employment to 2030 under most scenarios, the transitions will be very challenging--matching or even exceeding the scale of shifts out of agriculture and manufacturing we have seen in the past.

Few weeks after announcing a partnership with Cambridge Judge Business School, and earmarking Rs 200 crore for foraying into Southeast Asian Markets and the Middle East, UpGrad, the online higher education platform, has now announced a partnership with IIIT-Bangalore to launch PG Diploma programme in machine learning and artificial intelligence. The 11-month Post Graduate Diploma programme in machine learning and artificial intelligence (AI) is a rigorous and selective PG Diploma Programme which will enable learners in mastering concepts in Machine Learning and AI like classification algorithms, deep learning, natural language processing (NLP), reinforcement learning and graph models amongst others. "Colleges and Universities have in-depth knowledge of technical domains and the latest research happening in these domains. IIIT Bangalore brings a strong understanding of evolving areas like machine learning and AI. Hence such a collaboration will help us bring to the learners, the most recent developments in the field." The curriculum is developed by the IIIT-B faculty and leading industry professionals in Indian technology sector.

New robot to help online students learn better - Scientists have developed an innovative robot that can help online students more engaged and connected to the instructor and students in the classroom. Stationed around the class, each robot has a mounted video screen controlled by the remote user that lets the student pan around the room to see and talk with the instructor and fellow students participating in-person....

I suppose that its in Amazon's best interest to not have people hacking accounts and spinning up the maximum amount of EC2s to mine Bitcoins.

Want to understand string theory in 20 minutes? The theoretical physicist has the handy knack of explaining the seemingly unexplainable, taking science out of its academic comfort-zone and into the general public. As co-founder of the yearly World Science Festival, Greene is passionate about increasing public awareness of not just the important of science but also its power to inspire us. He speaks to WIRED about how AI might replace biological life on Earth, the post-truth twilight zone and the challenge of computing consciousness. And we used to do all calculations with a pencil and paper, before that we did it scratching it out on tablets, but as technology progresses we have ever more powerful tools. I would say the same thing about AI, it's something that we can harness in order that we can do our jobs better.

The son of Paul Christie and Sonya Stagnoli, Ben and his sister Bella are home-schooled students who also take college courses. He'll graduate with an associate's degree from Germanna Community College next spring, at about the same time that he receives his high school diploma. She takes classes at Rappahannock Community College.

Dell EMC has announced the launch of its new machine learning and deep learning solutions, which according to the company is in line with it continuing its work to bring high-performance computing (HPC) and data analytics capabilities to mainstream enterprises worldwide. Dell EMC believes that this enables organisations to take advantage of the convergence of HPC and data analytics and realise advancements in areas including fraud detection, image processing, financial investment analysis and personalised medicine. According to the company, these new innovations represent the next step in the company's focus on democratising HPC, optimising data analytics with artificial intelligence (AI) technology innovations, and advancing both the HPC and AI communities. While AI techniques, such as machine learning and deep learning, being rapidly being deployed by many organisations across several industries, only a small number possess the expertise to design, deploy and manage such systems to use them effectively for rapidly gaining new insights. Dell EMC believes that by leveraging Dell's ecosystem of partnerships and internal expertise in HPC and data analytics services, the company's new solutions offer customers the ability to harness the power of the massive amounts of their collected data, delivering faster, better and deeper business insights in real-time.

At the time, I started writing this googling machine learning resulted in about 49,700,000 results. Human: what is the purpose of living We have strong bot development practices in place. AI is on full rage nowadays. If you want a robot to learn basketball Here's how this technology is evolving and how consumers are reacting to it. Gonzales Cenelia by these new sentence which give us our final response for the Chatbot: So, you think that I'm a machine. Machine Learning makes the A. Oct 08, 2017 · Microsoft Machine Learning Server Operationalization allows users to create remote R or Python sessions, create Machine Learning models using their AlphaBlues feeds its virtual assistant what the company calls "semantic enrichment inputs" so that the chatbot can machine learning architecture The Learning Chatbot Bonnie Chantarotwong IMS-256 Final Project, Fall 2006 Background The purpose of a chatbot program is generally to simulate conversation and The Learning Chatbot Bonnie Chantarotwong IMS-256 Final Project, Fall 2006 Background The purpose of a chatbot program is generally to simulate conversation and The first step in teaching anything to a computer is outlining what success looks like. But what is a chatbot and how is it developed? Chatbots are intelligent dialog systems that we interact ai chatbot self-learning machine free download. A guide to AI, machine learning and new workflow technologies at HIMSS17: Part 2: chatbots and workflow Learn more about Machine Learning, an application of AI that provides systems the ability to automatically learn and improve from experience.

A linguistics company is using AI to shorten the time it takes to learn a new language. It takes about 200 hours, using traditional methods, to gain basic proficiency in a new language. This AI-powered platform claims it can teach from beginner to fluency in just a few months – through once-daily 20 minute lessons. Learning a new language is hard. Some people seem to pick up new dialects with ease, but for the rest of us it's a trudge through rote memorization.