The time of year when crystal balls get a viewing and many pundits put out their annual predictions for the coming year. Rather than thinking up my own, I figured I'd regurgitate what many others are expecting to happen. Chris Preimesberger (@editingwhiz), who does a monthly #eweekchat on twitter, covers many of the worries facing organizations. People focus so much on the'things' themselves rather than the risk of an internet connection. This list discusses how IoT will grow up in 2017, how having a service component will be key, the complete mess of standards and simply, 'just because you can connect something to the Internet doesn't mean that you should.' NW talks about how cyber attacks will get worse due to IoT and gives some ideas on how to protect your data in 2017.

With that in mind, I'd like to share one way that Avnet has been using machine learning in the enterprise this year, with highly compelling results. In October 2016, the internet experienced a massive denial of service attack that affected more than 80 major websites and cloud service providers from Amazon to Twitter. A bit of malware that hijacked hundreds of thousands of unsecure Internet of Things devices to overwhelm specific targets. In the cybersecurity arms race, malicious hackers are increasingly looking to machines to strengthen their attacks. So larger organizations like Avnet are also tapping into the power of machines--in this case, machine learning--to strengthen our defenses.

We live in an era of accelerating change, when scientific and technological advancements are arriving rapidly. As a result, we are developing a new language to describe our civilization as it evolves. Here are 20 terms and concepts that you'll need to navigate our future. Back in 2007 I put together a list of terms every self-respecting futurist should be familiar with. I reached out to several futurists, asking them which terms or phrases have emerged or gained relevance since that time. These forward-looking thinkers provided me with some fascinating and provocative suggestions -- some familiar to me, others completely new, and some a refinement of earlier conceptions.

Recently popularized by IBM's highly intelligent Watson supercomputer, which competed on the hit game show Jeopardy, cognitive computing refers to machines that are capable of learning concepts and patterns through advanced language processing algorithms. A system that involves incredibly advanced artificial intelligence, cognitive computing is one facet of computer science that isn't for the faint of heart. Although much of the hype is centered on big business and big data processing, there are a number of consumer applications. Whereas business leaders might use the technology to increase their bottom line, streamline daily operations and achieve greater profitability, consumers can take advantage of computing to ease some of the burdens of everyday life. In fact, many consumers are using some form of it without realizing it.

IBM Watson may be able to win "Jeopardy!" The IBM Watson for Cybersecurity beta program launched this week with 40 partners around the world in an effort to help security analysts make better, faster decisions from vast amounts of data, but experts say this is the same promise offered by many other products. IBM said Watson for Cybersecurity will feature natural language processing that can help it to "understand the unique language of security." "The truth is a lot of security vendors today are attaching '[artificial intelligence]' or'cognitive' to a number of products that are really just advanced analytics or machine learning, which are also important elements that can help in the fight against cybercrime," Diana Kelley, executive security advisor for IBM Security, told SearchSecurity. "What Watson will bring to the equation that is unique is the ability to digest vast amounts of both structured data as well as all of the intelligence that exists in natural language, like blogs, white papers and research reports. For example, there are around 10,000 security research papers published each year, and 60,000 security blog posts published every month."

If Hollywood is to be believed, the development of super-intelligent AI will spell the end of civilization as we know it and spark an unwinnable war between man and machine. It doesn't make for nearly as exciting entertainment, but artificial intelligence also offers tremendous upside, from the potential to deliver customized education to everyone, to improving disease diagnosis and treatment and eradicating poverty. Although AI researchers are focused these beneficial outcomes, the dystopian vision portrayed in so much science fiction is also a real possibility. At the recent Singularity University (SU) New Zealand Summit we talked with Neil Jacobstein, the former president and current chair of the Artificial Intelligence and Robotics Track at SU, about how the outcomes feared by so many can be avoided.

By 2020 it is estimated that the global internet of things (IoT) market will have grown to more than $1.7 trillion. According to a study by Gartner, by the end of this year alone the number of IoT devices on the planet will have reached more than 4 billion. It is not unreasonable to suggest that by the end of this decade, these devices will outnumber humans. Such exponential growth has facilitated two major developments. It has boosted technology markets around the world and it has warped the landscape of cyberspace.

MIT researchers have designed a new machine-learning system that can learn by itself to extract text information for statistical analysis when available data is scarce. This new "information extraction" system turns machine learning on its head. It works like humans do. When we run out of data in a study (say, differentiating between fake and real news), we simply search the Internet for more data, and then we piece the new data together to make sense out of it all. That differs from most machine-learning systems, which are fed as many training examples as possible to increase the chances that the system will be able to handle difficult problems by looking for patterns compared to training data.

This AI-composed Christmas carol makes a strong case for... This AI's attempt to write a Christmas carol is absolutely bone-chilling Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Apple appears to be shifting into the fast lane to exploring the creation of autonomous vehicles. In a letter it submitted to the National Highway Traffic Safety Administration (NHTSA) recently, the tech giant appeared to confirm an open secret: That it is in fact working on a self-driving car. "The company is investing heavily in the study of machine learning and automation, and is excited about the potential of automated systems in many areas, including transportation," Apple said in a letter dated Nov. 22, the deadline set by the NHTSA. The Wall Street Journal first reported that Apple had submitted a letter to the agency. The development is in line with recent headlines about Apple's Project Titan, its rumored self-driving car enterprise.