Researchers from UC Berkeley have created a technology that allows robots to imagine how their actions will turn out in the future. Using this approach, the robots are able to interact with objects that they've never come across previously. The way the technology helps the robots predict the future is called visual foresight. It gives the robotic system an ability to anticipate what future actions, like a series of movements, would look like in its camera. In essence, a robotic imagination is invoked, allowing predictions several seconds into the future.

The Optimizing Government Project brings together scholars and researchers to discuss the use of machine learning by government. In recent years, the private sector has succeeded in finding many ways to leverage machine learning--a type of artificial intelligence that enables computers to "learn and adapt through experience." Well-known private sector applications of machine learning include Google's self-driving car project, online recommendations personalized for customers on websites like Amazon and Netflix, and fraud detection by credit card companies. But as the private sector embraces machine learning in new ways, the application of machine learning by government agencies has only started to take root. The use of artificial intelligence by government, though, raises important questions for a democratic society--about fairness, equality, transparency, and accountability.

Organizations that successfully apply AI innovate and compete more effectively. Those who fail to implement AI successfully will fall behind. The AI Conference in New York will give you a solid understanding of the the latest breakthroughs and best practices in AI for business. You'll get insider information on any aspect of AI you may be working on including: You'll discover how the world's most innovative companies are using AI--and how to implement their successes in your products and enterprise. And you'll meet some of the most interesting people in AI: Xerox PARC CEO Tolga Kurtoglu, Intuit CDO Ashok Srivastava, Princeton Professor Olga Russakovsky, Deloitte Chief Data Scientist James Guszcza, FICO Chief Analytics Officer Scott Zoldi, Emma Kinnucan of Booz Allen Hamilton, and more.

AI pioneer Andrew Ng is probably best known for his work on the Google Brain project and for leading Baidu's AI group (and his machine learning course on Coursera). After leaving Baidu earlier this year, it wasn't quite clear what exactly Ng was up to (except for teaching more classes), but today he announced the launch of Landing.ai, a new startup that focuses on bringing artificial intelligence to the manufacturing industry. The idea here is to help bring AI to industries outside the traditional IT world. In his announcement, Ng argues that AI and machine learning have already transformed how many of the big internet companies do business. Other industries, however, are lagging behind.

Recent news on Sophia the robot getting citizenship in the Saudi Arabia has widely attracted daily news and social media. Despite the debates and agitations on a robot getting recognition as humans, experts view this event as a phenomenal milestone in the research of AI. The current level of Artificial Intelligence is achieved through years of research in Machine Learning, Deep Learning and other related fields. With a lot of hype and investments around, Deep Learning technology – a subdivision of Machine Learning is now successfully applied in our daily life from speech recognition apps in smartphones to YouTube recommendations. One of the pioneers of the Deep Learning, Andrew Ng feels that AI is the new form of electricity where every AI application in future electronic devices will be fuelled by Deep Learning models.

The Facebook AI Research (FAIR) Residency Program is a one-year research training program with Facebook's AI Research group, designed to give you hands-on experience of machine learning research. The program will pair you with a senior researcher or engineer in FAIR, who will act as your mentor. Together, you will pick a research problem of mutual interest and then devise new deep learning techniques to solve it. We also encourage collaborations beyond the assigned mentor. The research will be communicated to the academic community by submitting papers to top academic venues (NIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP etc.), as well as open-source code releases.

While the scientific community continues looking for new breakthroughs in artificial intelligence, Andrew Ng believes the tech we need is already here. In his keynote speech Friday at the AI Frontiers Conference, the founder of Coursera & Deeplearning.ai Stop publishing, and start transforming people's lives with technology!" The three-day conference drew over 1,400 attendees from 17 different countries to the Santa Clara Convention Center. Ng's keynote speech was titled "AI is the new electricity".

Before a Google machine learning program discovered an eighth planet in an exoplanet system using NASA spacecraft observations, the only other known system with as many planets was our own. Kepler has been scanning for planet systems beyond our solar system since 2009 and has made countless discoveries of planets orbiting stars, but so far none of those systems have contained as many planets as our own. That changed recently with the help of a Google AI program that found an an eighth planet orbiting the sun-like star Kepler 90, NASA scentists announced Thursday. Like Earth, this new planet, Kepler-90i, is the third rock from its sun. But it's much closer to its sun -- orbiting in just 14 days -- and therefore is a scorching 800 degrees Fahrenheit (427 Celsius) at the surface. In fact, all eight planets are scrunched up around this star, orbiting closer than Earth does to our sun.

We've been talking about data science and data scientists for a decade now. While there's always been some debate over what "data scientist" means, we've reached the point where many universities, online academies, and bootcamps offer data science programs: master's degrees, certifications, you name it. The world was a simpler place when we only had statistics. But simplicity isn't always healthy, and the diversity of data science programs demonstrates nothing if not the demand for data scientists. As the field of data science has developed, any number of poorly distinguished specialties have emerged.

TensorFlow is an open-source machine learning software built by Google to train neural networks. TensorFlow's neural networks are expressed in the form of stateful dataflow graphs. Each node in the graph represents the operations performed by neural networks on multi-dimensional arrays. These multi-dimensional arrays are commonly known as "tensors", hence the name TensorFlow. TensorFlow is a deep learning software system.