Self-driving cars seem an awful lot like magic. They contain elements of automotive technology, computer vision, artificial intelligence and many other cutting-edge fields of tech. So, if you wanted to learn how it all hangs together, where would you even start? MIT decided to start with… rubber duckies. Letting students loose on actual 3-ton vehicles with the power to kill, maim and otherwise cause a nightmare for lawyers might be a little bit much.

Apple has just agreed to settle a long-running patent lawsuit for almost 25 million. The lawsuit, filed by a company called Dynamic Advances, claimed that Apple had infringed on a patent involving "user interfaces that recognize natural language." The patent describes a method for "providing, through a user interface, a result of [a] search" using natural language queries of a number of connected databases. The patent had been originally granted as far back as 2007 to the Rensselaer Polytechnic Institute in upstate New York. Rensselaer, an engineering-focused university, then licensed the patent to Dynamic Advances. When Apple came out with Siri in 2011, Dynamic Advances sued the tech giant the following year, saying it had infringed on the patent.

Our First meetup will be focused on H2O, an open-source Machine Learning Platform. It will take place the CIC on Milk Street in Boston.. the Date is set for 5/12 at 6:00PM. NOTE: Bring Laptops if you want to partake in hands on demo. This workshop will provide an overview of how to use H2O, the scalable open source machine learning library, from Python/R/Flow UI. The core algorithms of H2O are implemented in Java, however, fully-featured APIs are available in R, Python, Scala, and also through the Flow UI web interface.

Business intelligence has gone from static reports that tell you what happened, to interactive dashboards where you can drill into information to try and understand why it happened. New big data sources, including Internet of things (IoT) devices, are pushing businesses from those reactive analytics -- whether you look back once a month to spot trends or once a day to check for problems -- to proactive analytics that give you alerts and real-time dashboards. That makes better use of operational data, which is more useful while it's still current, before conditions change. "There's a demand for real-time dashboards," says Herain Oberoi from Microsoft's Cortana Analytics team. "A lot of businesses want to get the pulse of their business. But dashboards show things that have already happened."

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. You are not sure if this book is for you? Please checkout the excerpts from the Foreword and Preface, or take a look at the FAQ section for further information. Sebastian Raschka's new book, Python Machine Learning, has just been released.

Chris Bishop, Microsoft's director of research at Cambridge, says warnings mankind is on the brink of developing The Terminator's Skynet and other homicidal AIs are'nonsense' and will be for decades to come. Microsoft Research Cambridge laboratory director Chris Bishop dismisses the fear artificial intelligence (AI) is on the cusp of overtaking human intelligence, and says it will continue to lag human performance for decades to come. "Yes, deep learning has achieved human-level performance in object recognition, but what does that mean?" Bishop asks. "It means the machine makes about the same number of errors as the human." Bishop stresses even vaunted examples of machine intelligence, such as Google DeepMind's Go-playing system, have to be understood within the context of the immense time and manpower invested in their development.

Since IBM's Watson computer was born in 2011, interest has been aroused, not only in the tech community, but also from the general public. Venture capital investors have poured money into Artificial Intelligence (AI) start-ups and large corporations, such as Google, Microsoft, Apple, and Facebook have been buying AI companies. The investment in AI companies reached 8.5 billion last year. The team AI has been used in science fiction, about machines that are able to think for themselves. The automated voice on your smart phone is a type of AI.

Artificial intelligence and deep learning are powering interacting messaging services known as chatbots and conversational interfaces, to create deeper, more personalised one-to-one customer experiences, and natural language text conversations. The Chatbot Track will explore the technical advancements in deep learning, NLP and image classification to create conversational self-learning bots for messaging platforms, personalised advice, support and recommendations.

Is creativity a uniquely human trait? Defining the line between human and machine is becoming blurrier by the day as startups, big companies, and research institutions all compete to build the next generation of advanced AI. This arms race is bringing a new era of AI that won't prove its power by mastering human games, but by independently exhibiting ingenuity and creativity. Sophisticated AI is undertaking increasingly complex tasks like stock market predictions, research synthesis, political speech writing--don't worry, this article was still written by a human--and companies are beginning to pair deep learning with new robotics and digital manufacturing tools to create "smart manufacturing." Hod Lipson, professor of engineering at Columbia University and the director of Columbia's Creative Machines Labs, is pushing the next frontier of AI.

Hackathon[3]: "New Realities" examined what's real in the shrinking gap between our physical and digital lives. In terms of existing and emerging technology, reality is whatever we are capable of. We can talk to our TV with Siri, live inside a game with Oculus Rift or travel anywhere through Google Street View. There's never been a time of more reality-challenging innovation, as our Hackathon[3] teams demonstrated in a quick-turn all-or-nothing competition built on the latest forms of what's possible.] "Knack," the winning project, made sales empathy a reality. Knack is a product that demonstrates how artificial intelligence and organic intelligence empower a sales force to sell to the person and not to the script.