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 They need to know how to navigate when their pre-programmed maps are out of date.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.

A long-form Backchannel post by Steven Levy gives a fascinating insight into Google's vision of the future of machine-learning. While it's currently a specialist field, Google believes that one day it will be used by all software engineers no matter what the field, and that it will'change humanity.' It invites just 18 software engineers a year to join its Machine Learning Ninja Program, where they work alongside expert mentors for six months before going back to apply the approach to their own work. But Google's machine-learning leader Jeff Dean estimates that around 10% of its 25,000 developers are proficient in the field, and he'd like that number to be 100%. What's notable is that all involved, from those in the Ninja program to the company's key experts in the field, see machine-learning as something transformative … For many years, machine learning was considered a specialty, limited to an elite few.

University of Skövde is seeking a post-doc in machine learning for a project where the main application scenario will be text analytics. The post-doc will have an unique opportunity to develop new machine learning algorithms, e.g., from the field of deep learning, to detect and predict how text flows from the internet evolve over time based on over 700 000 different sources on the open web (through an API provided by our partner company Recorded Future). The post-doc will be affiliated with the Skövde Artificial Intelligence Lab (SAIL), which is one of the oldest and most prominent research groups in artificial intelligence (AI) in Sweden. At the University of Skövde Informatics is defined as the science that addresses how information is represented, processed and communicated in artificial and natural systems, and how such systems are used and developed in order to achieve usable and effective applications and solutions for individuals, organizations or society. The post-doc is positioned at the School of Informatics, which is a school in expansion.

WIRE)--Ipswitch, the leader in easy to try, buy and use IT management software, today announced the findings of an independent global study, carried out by analyst firm Freeform Dynamics. The survey examines the attitudes and readiness of IT decision makers with regard to intelligent machines and business systems (machines with decision making and learning capabilities). Exploring the fast-paced adoption of these systems, the report looks at the positive impacts already being observed in the commercial world and the potential barriers to even further mainstream adoption over the next decade. According to the research, investment in intelligent business systems and automation is well underway across the globe. Top current application deployment areas cited by respondents include digital customer engagement systems (55 percent), process automation and workflow systems (52 percent) and automated risk monitoring and management solutions (50 percent).

Ask any Millennial what their favorite form of communication is these days and you'll often hear "Snapchat". Messages are short, visual and temporary. Emotional clarification is accomplished with emoji and selfies. It's ideally suited for the MTV generation. The "Live Chat" experience is not all that different. Now imagine your next live chat experience online won't be with a human, but with an intelligent machine.

The last few years have seen some impressive steps forward in big artificial intelligence projects. Yahoo has used deep learning for a major recategorization of Flickr's massive photo set. Earlier this year, AlphaGo beat 9-dan professional Go player Lee Sedol in 4 out of 5 games. Everyone from Facebook to open.ai is developing new and exciting AI projects with cutting-edge software and massive data sets. Matt, my co-founder at fuzzy.ai, points out that most of us don't play televised Go matches on an international level.

Over the past several years, many new technological innovations in the healthcare industry have come and gone, but only a handful of trends matured and achieved widespread adoption among healthcare organizations. Bots are another new development that is piquing the interest of healthcare organizations and attempting to become more than a fleeting trend. There's no doubt that mobile health technology improves patient care, engagement, and physician productivity. But, the security risks are vast. Learn how to protect your mHealth devices and data in this exclusive e-guide.

One day in January 2013, I found myself wasting time on the internet. This wasn't a good idea: I was as busy as anyone 2.5 years into their PhD. I had to finish a presentation on some yeast genetics research, I was months behind on a paper with an NYU collaborator and even farther behind on some leftover undergraduate research. I was also busy in my personal life--I had returned from a trip to Israel and had just taken up Brazilian Jiu-Jitsu and jogging. But this one day, I was wasting time by answering a stranger's question about the beta distribution. The question was on Cross Validated, the statistics sister site of developer Q&A site Stack Overflow.