Whether you're interested in cognitive computing, artificial intelligence or machine learning, you probably know that the fourth industrial revolution is well underway and accelerating rapidly. The speed of change presents a challenge to developers who want to stay abreast of the latest ideas and approaches. Conferences, workshops and other meetings provide opportunities to learn where the jobs and technology is headed and a chance to learn and practice the skills necessary to keep up. Why you should attend: AI engineers, practitioners, researchers and scientists will discuss the latest developments in the field, while tutorials and workshops will give attendees a chance to hone their skills. Speakers will be drawn from a wide variety of sectors, including Microsoft, MIT, the National Science Foundation and NASA Ames Research Center.

Artificial intelligence (AI) represents what I believe to be the next leap forward in technological development. With AI, we can process data faster, design systems that learn based on their environments and possibly solve problems that to date we've been unable to solve. It's only a matter of time before AI takes over the social media world and starts using machine-learning to better serve us as both consumers and business owners. So, which will be the first to take the plunge, and how can you, as an entrepreneur, prepare? AI and machine-learning have already started to infiltrate the functionality of most -- if not all -- major social media apps in the world today, and in multiple areas.

In December 2016 a new venue opened up in London, UK called the Realities Centre, focused on promoting virtual reality (VR), augmented reality (AR) and mixed reality (MR) technology. THe last couple of months have seen several conferences and hackathons taking place and now the venue has revealed its latest events. Taking place in March 2017, the Realities Centre will be hosting another conference and hackathon, this time dedicated to artificial intelligence (AI) and VR. Held on 16th March will be the AI VR Conference, featuring an evening of discussions exploring the two fields, namely how AI machine learning and natural language processing can be used in VR. Speaking at the event will be Rob Whitehead, co-founder and CTO of Improbable, whose talk will be on'A high level introduction of the AI and VR industry'.

Air New Zealand has made its first foray into the field of artificial intelligence (AI) unveiling its new chatbot, Bravo Oscar Tango – Oscar for short. Oscar will initially assist customers with commonly asked queries, saving them time and offering a more personalised experience than searching a traditional Frequently Asked Questions section online. As with other AI technology, Oscar will learn based on the conversations people have with him, becoming more user friendly and more helpful the more he interacts. Air New Zealand Chief Digital Officer Avi Golan says Oscar has been launched as a beta product allowing customers to play an active role in training him. "This is a new approach for us, getting Oscar out fast and in the early-development stages so that we can build and co-create with our customers.

Imagine your smartphone being able to negotiate the best price of a new car for you -- that's one of the potential implications of artificial intelligence beating humans in poker for the first time, experts say. Libratus, an AI built by Carnegie Mellon University (CMU), racked up over $US1.7 million ($2.2 million) worth of chips against four of the top professional poker players in the world in a 20-day marathon poker tournament that ended in Philadelphia on Tuesday.. While machines have beaten humans over the last two decade in chess, checkers, and most recently in the ancient game of Go, Libratus' victory is significant because poker is an imperfect information game -- similar to the real world where not all problems are laid out. The difficulty in figuring out human behaviour is one of the main reasons why poker was considered immune to machines. "The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans," said Tuomas Sandholm, professor of computer science at CMU who created Libratus with a PhD student Noam Brown.

Many technological trends come and go; the great ones last forever, and the not so great fade away, barely remembered as a fad. Not all technologies are purposeful, but when they are, they make our lives easier, neater, and smarter. This article presents an honest evaluation on conversational agents (bots) and where (we think) they stand in the future. Whether you are a business owner or simply a customer, you must have encountered bots in your daily life. From online shopping (conversational commerce) to asking Siri a simple question, bots are everywhere.

I work in computational quantum condensed-matter physics: the study of matter, materials, and artificial quantum systems. Complex problems are our thing. Researchers in our field are working on hyper-powerful batteries, perfectly efficient power transmission, and ultra-strong materials--all important stuff to making the future a better place. To create these concepts, condensed-matter physics deals with the most complex concept in nature: the quantum wavefunction of a many-particle system. Think of the most complex thing you know, and this blows it out of the water: A computer that models the electron wavefunction of a nanometer-size chunk of dust would require a hard drive containing more magnetic bits than there are atoms in the universe.

Almost every machine learning breakthrough you hear about (and most of what's currently called "artificial intelligence") is supervised learning; where you start with a curated and labeled data set. But another technique, reinforcement learning, is just starting to make its way out of the research lab. Reinforcement learning is where an agent learns by interacting with its environment. It isn't told by a trainer what to do and it learns what actions to take to get the highest reward in the situation by trial and error, even when the reward isn't obvious and immediate. It learns how to solve problems rather than being taught what solutions look like. Reinforcement learning is how DeepMind created the AlphaGo system that beat a high-ranking Go player (and has recently been winning online Go matches anonymously). It's how University of California Berkeley's BRETT robot learns how to move its hands and arms to perform physical tasks like stacking blocks or screwing the lid onto a bottle, in just three hours (or ten minutes if it's told where the objects are that it's going to work with, and where they need to end up).

It's report card time for the automakers and Silicon Valley denizens studying the tricky problem of making cars drive themselves, and everyone is passing. The California DMV just released its annual slate of "disengagement reports," documents provided by the 11 companies that received state permits to test autonomous vehicles by the end of 2015. The results, summarized below, reveal how often humans had to wrest control away from the computer, and why (sort of). Although the reports are an imperfect measure of how the technology performs, they do reveal rapid progress toward the day when you are no longer needed behind the wheel. Google and General Motors are leading the class with cars capable of driving hundreds of miles at a stretch without trouble.

This post is the second in a series where we will go over examples of how MapR data scientist Joe Blue assisted MapR customers, in this case a regional bank, to identify new data sources and apply machine learning algorithms in order to better understand their customers. If you have not already read the first part of this customer 360 series, then it would be good to read that first. In this second part, we will cover a bank customer profitability 360 example, presenting the before, during and after. The back story: a regional bank wanted to gain insights about what's important to their customers based on their activity with the bank. They wanted to establish a digital profile via a customer 360 solution in order to enhance the customer experience, to tailor products, and to make sure customers have the right product for their banking style.