Equity deals to startups in artificial intelligence -- including companies applying AI solutions to verticals like healthcare, advertising, and finance as well as those developing general-purpose AI tech -- increased nearly 6x, from roughly 70 in 2011 to nearly 400 in 2015. Q1'16 saw a new peak in deal activity to the category. So far in 2016 (as of 6/15/2016), over 200 AI-focused companies have raised nearly 1.5B in equity funding. Our analysis includes all equity funding rounds and convertible notes.

The most important subpackages provide implementations of boilerplate code that is relevant to machine-learning problems. These include computer vision, natural language processing, and speech processing. Other subpackages may be smaller and focus on more specific problems or even specific data sets.

Over the past year, questions about how emerging technologies will impact employment have taken on a new tenor. Will robots take over our jobs? One thing is indisputable: automation and artificial intelligence (AI) will displace workers in the IT and business process outsourcing services industry. Such tectonic shifts have occurred every few decades over the last two centuries. With each wave of new technology and each accompanying paradigm shift, jobs have disappeared.

In a recent interview at the Code Conference in California, technology entrepreneur Elon Musk suggested we are living inside a computer simulation. On first hearing, this claim seems far-fetched. But could there be some substance to Musk's thinking? As founder of a number of high-profile companies, such as Tesla and Space X, Musk's business interests lie firmly in leading technologies. Key to his claim is that computer games have evolved rapidly over the past 40 years to the point that, inside the next few years, they will be fully immersive, with a computer-generated and controlled world seamlessly merged with the physical world.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

There's a chance it could bring the mood down. Having chosen your shiny new driverless car, only one question remains on the order form: whether your spangly, futuristic vehicle be willing to kill you? To buyers more accustomed to talking models and colours, the query might sound untoward. But for manufacturers of autonomous vehicles (AVs), the dilemma it poses is real. If a driverless car is about to hit a pedestrian, should it swerve and risk killing its occupants?

In catch-22 traffic emergencies where there are only two deadly options, people generally want a self-driving vehicle to, for example, avoid a group of pedestrians and instead slam itself and its passengers into a wall, a new study says. But they would rather not be travelling in a car designed to do that. The findings of the study, released on Thursday in the journal Science, highlight just how difficult it may be for auto companies to market those cars to a public that tends to contradict itself. Related: Statistically, self-driving cars are about to kill someone. "People want to live a world in which everybody owns driverless cars that minimize casualties, but they want their own car to protect them at all costs," Iyad Rahwan, a co-author of the study and a professor at MIT, said.

Self-driving cars have a lot of learning to do before they can replace the roughly 250 million vehicles on U.S. roads today. They need to know how to navigate when their pre-programmed maps are out of date. They need to know how to visualize the lane dividers on a street that's covered with snow. And, if the situation arises, they'll need to know whether it's better to mow down a group of pedestrians or spare their lives by steering off the road, killing all passengers onboard. Once self-driving cars are logging serious miles, they're sure to find themselves in situations where an accident is unavoidable.

The FBI has access to nearly 412 million facial photos in its facial recognition system--perhaps including the one on your driver's license. But according to a new government watchdog report, the bureau doesn't know how error-prone the system is, or whether it enhances or hinders investigations. Since 2011, the bureau has quietly been using this system to compare new images, such as those taken from surveillance cameras, against a large set of photos to look for a match. That set of existing images is not limited to the FBI's own database, which includes some 30 million photos. The bureau also has access to face recognition systems used by law enforcement agencies in 16 different states, and it can tap into databases from the Department of State and the Department of Defense.

Dublin-based Text and Image Analysis startup, AYLIEN, is looking to hire Research Fellows, Postdoctoral Researchers and Lecturers to conduct novel and significant research in the fields of Artificial Intelligence, Machine Learning and Natural Language Processing. This is a unique opportunity to work with a team of talented Scientists and Engineers at AYLIEN to push the boundaries of AI research. Please send a brief introduction about yourself, your CV and links to GitHub, Google Scholar, papers and articles if applicable to jobs@aylien.com AYLIEN is a leading Text and Image Analysis solution provider in Europe, helping tens of thousands of developers and data scientists in more than 500 cities globally to extract meaning and insights from unstructured data, such as news articles, social media updates and customer reviews. We are a team of 13 people spread across Science, Engineering and Sales & Marketing, based near the beautiful River Liffey in the heart of Dublin.