Keynotes by NSF Director Dr. France C?rdova, NVIDIA Chief Scientist Dr. Bill Dally, Deputy Director for Cancer Research and Technology Director Jerry Lee, and Chairman of the Council of Economic Advisors, Jason Furman, will each discuss aspects of how A.I. and deep learning will transform the future.

Yet, while the world is busy watching Silicon Valley, these relatively obscure spots in the US and Europe are quietly building the infrastructure for innovation ecosystems that will drive the next technological revolutions. In 2008 General Electric opened a state-of-the-art jet engine component factory in the small Mississippi town, followed by another one in Ellisville in 2013. Both towns are close to technical universities stocked with researchers that specialize in new materials for the next-generation ultralight and silent jet engines. This partnership is crucial for innovation. As GE CEO Jeff Immelt wrote in the Harvard Business Review, "By partnering with Mississippi State University, we have developed a highly sophisticated proprietary process for manufacturing components made of carbon-fiber composites."

A London-based startup has combined some of today's most disruptive technologies in a bid to change the way we'll build the future. By retrofitting industrial robots with 3D printing guns and artificial intelligence algorithms, Ai Build has constructed machines that can see, create, and even learn from their mistakes. When CEO and founder Daghan Cam was studying architecture, he noticed a disconnect between small-scale manufacturing and large-scale construction. "On one side we have a fully automated production pipeline," Cam explained at a recent conference in London. With the emergence of more efficient printing technologies, he thought there must be a better way.

Tesla has reportedly been told to stop advertising an "autopilot" function on its cars after the term was deemed to be misleading. German transport regulator KBA wrote to the company after the feature came under scrutiny following two fatal crashes. Questions have been raised over the system after fatal crashes in northern China and Florida. There was also an incident in Germany in which a Tesla electric car crashed into a tourist bus while on autopilot. "In order to prevent misunderstandings and false expectations from clients, we are asking that the misleading term'Autopilot' no longer be used in advertisements for the system," KBA said, according to the Local.

New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain. Artificial neural networks (ANNs) exhibit learning abilities and can perform tasks which are difficult for conventional computing systems, such as pattern recognition, on-line learning and classification. Practical ANN implementations are currently hampered by the lack of efficient hardware synapses; a key component that every ANN requires in large numbers. In the study, published in Nature Communications, the Southampton research team experimentally demonstrated an ANN that used memristor synapses supporting sophisticated learning rules in order to carry out reversible learning of noisy input data. Memristors are electrical components that limit or regulate the flow of electrical current in a circuit and can remember the amount of charge that was flowing through it and retain the data, even when the power is turned off.

A new age is dawning. Whether it is a wonderful one or a terrible one remains to be seen. Look around and the signs of dizzying technological progress are difficult to miss. Driverless cars and drones, not long ago the stuff of science fiction, are now oddities that can occasionally be spotted in the wild and which will soon be a commonplace in cities around the world. With a few flicks of a finger, we can use our phones to order up a meal, or a car, or a translation for a waiter's query in a foreign country. Gadgets such as the Amazon Echo are finding their way into living rooms, where they sit listening, ready to comply with a voice command. Just a few years ago, one could dismiss the digital age as consisting of little more than social networks and cat videos; no longer.

One amazing feat of combined neuroscience, engineering and computing was achieved by Edda Bilek, Andreas Myer-Lindenberg and colleagues from the Mannheim Central Institute of Mental Health in Germany. They invented a way to study information flow between human pairs during real-time social interaction, using functional magnetic resonance imaging (fMRI), which measures changes in blood flow in the brain. They were particularly interested in studying joint attention because it arises in early development and is important for social learning.

With all the hustle and bustle going on in the world of chatbots at the moment, one crucial event that is very relevant to the future of A.I. has gone relatively unnoticed. If you are interested in chatbots and A.I., you may have heard about the Loebner Prize, which was created by Hugh Loebner and is a form of the Turing Test that Alan Turing first set up in the 1950s. The Loebner Prize is an annual event in which A.I. specialists from around the world come together to play their bots off against a panel of judges in a battle for the most humanlike A.I. The goal is to trick the judges into thinking they are talking to a real person. The event has been hosted all over the world, but since 2014, it has been held in Bletchley Park in the U.K., due to the connection between Alan Turing and Bletchley during the second World War.

Fanuc, maker of the industrial robots used to assemble Apple's iPhone and cars for Volkswagen and Tesla, is now partnering with Nvidia to add the company's graphics processing units to its massive machines. Fanuc launched an initiative to bring artificial intelligence to its robots after investing 7.3 million in Preferred Networks, a machine learning company, in 2015. Nvidia's graphics processing units and deep-learning technology will be used to help Fanuc robots recognize, process and respond to the environment around them. It's especially important for reinforcement learning, which is how machines use artificial intelligence to adopt new skills through practice. A robot may capture video of itself to review how it well it did, then analyze and build on that information as it keeps improving over time.

Does your company suffer from corporate amnesia? Palo Alto, California-based startup Maana has developed a cure for what ails organizations everywhere: Knowledge of how to perform a certain task or make a specific decision walks out the door with employees migrating to another job or retiring. Even when this tacit knowledge is captured, codified and stored in a database, it may not be accessible to the people who need it, when they need it. "We patented a unique and novel way of indexing and organizing the knowledge that is locked in data silos across the organization," says founder and CEO Babur Ozden. Today, Maana released a new version of its AI-driven platform.