Back in 1979, two scientists wrote a seminal textbook on computational complexity theory, describing how some problems are hard to solve. The known algorithms for handling them grow in complexity so fast that no computer can be guaranteed to solve even moderately sized problems in the lifetime of the universe. While most problems could be deemed either relatively easy or hard for a computer to solve, a few fell into a strange nether region where they could not be classified as either. The authors, Michael Garey and David S. Johnson, helpfully provided an appendix listing a dozen problems not known to fit into one category or the other. "The very first one that's listed is graph isomorphism," says Lance Fortnow, chair of computer science at the Georgia Institute of Technology.

That is what I said when I was asked whether we would ever see computer science taught in K–12. It was 2009, and I was addressing a gathering of attendees to a workshop on computational thinking (http://bit.ly/1NjmcRJ) It has been 10 years since I published my three-page "Computational Thinking" Viewpoint (http://bit.ly/1W73ekv) in the March 2006 issue of Communications. To celebrate its anniversary, let us consider how far we've come. Since the dotcom bust, there had been a steep and steady decline in undergraduate enrollments in computer science, with no end in sight.

The 19th-century U.K. Locomotive Act, also known as the Red Flag Act, required motorized vehicles to be preceded by a person waving a red flag to signal the oncoming danger. Movies can be a good place to see what the future looks like. According to Robert Wallace, a retired director of the CIA's Office of Technical Service: "... When a new James Bond movie was released, we always got calls asking, 'Do you have one of those?' If I answered'no', the next question was, 'How long will it take you to make it?' Folks didn't care about the laws of physics or that Q was an actor in a fictional series--his character and inventiveness pushed our imagination ..."3 As an example, the CIA successfully copied the shoe-mounted spring-loaded and poison-tipped knife in From Russia With Love. It's interesting to speculate on what else Bond movies may have led to being invented. For this reason, I have been considering what movies predict about the future of artificial intelligence (AI). One theme that emerges in several science fiction movies is that of an AI mistaken for human.

Today on In Case You Missed It: Boston Dynamics introduced a new robot to the lineup and this one is both the smallest yet, and most adorable. The SpotMini is just two feet tall but in the video Boston Dynamics released, shows it can do dishes, throw cans away and creep around for a good 90 minutes on an electric charge. Meanwhile the EPFL designed a new medical device that looks not-entirely unlike an old school slap bracelet, except it's made of silicon and is designed to grip and squeeze the aorta, keeping the heart beating while a patient might be waiting for a heart transplant. Theater fans will want to know about New York's decision to ban robot buyers; while politically-minded folks (not already talking about Great Britain's vote to leave the EU) will want to hear about C-SPAN's decision to broadcast Periscope videos of the Democrat's sit-in. As always, please share any interesting tech or science videos you find by using the #ICYMI hashtag on Twitter for @mskerryd.

Artificial intelligence has crept into our everyday lives, even though we're not always aware of it. Here are some examples of AI's many applications. Journalists might not care for this, but AI programs are becoming smart enough to compile bits of information and turn them into articles. What's critical to understand about the potential impact machine learning can have on a manufacturing business lies in the way data is studied. The use of artificial intelligence that relies on natural language understanding is vital for achieving the potential outcomes mentioned above - otherwise, market intelligence would be based purely on statistical patterns and not contextual meaning.

WHEN the 2016 Wimbledon Championships start on June 27th millions of tennis fans will begin posting on social networks such as Twitter, Facebook and Instagram about everything from the matches to the attire, hairdos and headbands of their favourite players. The contest's organiser, the All England Lawn Tennis Club (AELTC), would quite like to know what the hottest topics are. So it is using a powerful computer to find out. That computer is Watson, an IBM machine which in 2011 famously won the American TV quiz "Jeopardy!" and nowadays resides as a cloud-computing service. The idea, says Alexandra Willis, the AELTC's digital supremo, is to use its machine learning and natural language-processing techniques to discover the most pressing topics of conversation among the vast output from fans. Knowing that, the club's editorial team--which provides content for Wimbledon's mobile app, its website and its video feeds--can respond quickly with relevant articles, posts, tweets, statistics and images.

Romanian startup Grobyk is organizing ready-to-use, trending information from your chosen sources, using Artificial Intelligence algorithms. Their 3 words pitch is: Instant Relevant Research. Content marketers keep up with a lot of sources, from social media, blogs, news site and so on. Search engine trends are misleading. What's relevant are social media shares.

One early morning in March 2011, Albert Chretien and his wife, Rita, loaded their Chevrolet Astro van and drove away from their home in Penticton, British Columbia. Their destination was Las Vegas, where Albert planned to attend a trade show. Rather than stick to the most direct route, they decided to take a scenic road less travelled, Idaho State Highway 51. The Chretiens figured there had to be a turnoff from Idaho 51 that would lead them east to US Route 93 all the way to Vegas. Albert and Rita had known each other since high school. During their 38 years of marriage, they had rarely been apart. They worked together, managing their own small excavation business.

Thinking about how important the funnel of a customer is for a company, we appreciate when new tools make the process easier. This is why we built Marketeer and today we are presenting version 3.0 with Marketeer Intelligent CRM. I have been working with artificial intelligence for a while – since the end of the 90s to be exact meanwhile I was running an advertising company. In 2012 I decided to invest time and money into building a new product that would help me make communication easier and effective for my clients. And today, we have it!

Giving up the controls was as breathtakingly simple as touching two turquoise coloured buttons below the steering wheel with both thumbs. A melodious bell chimed, a line of LEDs stretching across the dashboard switched from red to yellow to aqua blue, and the steering wheel withdrew slowly and serenely from my sweaty grasp. But any nervousness I felt stemmed far more from being required to steer a multimillion-euro research vehicle the few kilometres from German car manufacturer Audi's headquarters in Ingolstadt, Bavaria, on to the autobahn, than the fact that "Jack" had now taken over the driving. I had signed a liability waiver before embarking on the road test, which required me to accept the risks of a piloted journey on the autobahn, including possible injury or death. But once Jack was calling the shots, it took remarkably little time to get used to the idea.