It's easy to be cynical about CES. Every year, hundreds of companies head to Las Vegas to hock their wares to the tech press, which gulps them down like so much fast food. The big companies mostly spend their time showing off untold numbers of TVs which look excellent but aren't all that different from what we saw the year before. True innovation is hard to find, buried under the piles of commodity gadgets -- but when you find it, it's worth the trouble. Take the Oculus Rift, which was first revealed off at CES 2013. Few were publicly thinking about virtual reality as a viable consumer product. We all remember the failure of Nintendo's Virtual Boy -- it may not have totally killed VR as a consumer product, but it was years before we saw VR hardware for consumers that actually felt compelling.

Pretty much all of the tech giants attend the vast Vegas expo - either to unveil new products or to clinch deals behind the scene. But in recent years it's been start-ups that have had many of the most eye-arresting and sensational reveals. There are more at this year's show than ever before, thanks in part to crowdfunding. They now have to convince retailers - hunting through the halls for the next bestsellers - that the promise of their concept videos has been delivered upon. Dozens of start-ups are also there thanks to help from governments and other national bodies - France, Israel, Ukraine and the Netherlands all have stands where they'll fly the flag for local talent.

Whether it was a billion compromised Yahoo accounts or state-sponsored Russian hackers muscling in on the US election, this past year saw hacks of unprecedented scale and temerity. And if history is any guide, next year should yield more of the same. It's hard to know for certain what lies ahead, but some themes began to present themselves toward the end of 2016 that will almost certainly continue well into next year. And the more we can anticipate them, the better we can prepare. Here's what we think 2017 will hold.

That was the repeated response from Magic Leap founder Rony Abovitz when Reed Albergotti of The Information asked about the technology behind the startup's augmented-reality glasses. For months, as Albergotti recently reported, Magic Leap has wooed investors and journalists by strapping them into a bulky helmet that augments their world with Star Wars-like spaceships and other digital creations. But this helmet is too big and too expensive for the mass market, so the company is working to squeeze its technology into a sleek pair of wire-rim glasses. The rub, according to ex-employees speaking with The Information, is that the company is having trouble actually making that happen. Abovitz wouldn't let Albergotti try the glasses on, and when asked how they work, all he would say was: "Squirrels and sea monkeys."

This is the second installment in a three-part review of 2016 in machine learning and deep learning. Part One, here, covered general trends. In Part Two, we review the year in open source machine learning and deep learning projects. Part Three will cover commercial machine learning and deep learning software and services. There are thousands of open source projects on the market today, and we cannot cover them all. We've selected the most relevant projects based on usage reported in surveys of data scientists, as well as development activity recorded in OpenHub. In this post, we limit the scope to projects with a non-profit governance structure, and those offered by commercial ventures that do not also provide licensed software. Part Three will include software vendors who offer open source "community" editions together with commercially licensed software.

I went into a local Gamestop just before the New Year, and I decided to browse through recently released games on the PS4 and Xbox One. I was looking for a fighting game that I might have overlooked. CHIBA, JAPAN - SEPTEMBER 20: An attendee (L) plays Namco Bandai Games Inc.'s'Tekken Tag Tournament 2' with Nintendo Co.'s Wii U video game console during the Tokyo Game Show 2012 at Makuhari Messe on September 20, 2012, in Chiba, Japan. The annual video game expo, which is held from September 20 to 23, attracts thousands of business visitors and the general public with exhibitions of the upcoming game software and latest hardware. It's been a long time since I played one regularly.

This algorithm forms the basis for many modern day ML algorithms, most notably neural networks. In addition, we'll discuss the perceptron algorithm's cousin, logistic regression. And then we'll conclude with an introduction to SVMs, or support vector machines, which are perhaps one of the most flexible algorithms used today. In machine learning, there are two general classes of algorithms. You'll remember that in our last post we discussed regression and classification.

If artificial intelligence (AI) hadn't hit the mainstream before, it did this year. Google chief executive Sundar Pichai came through with the best sound bite, saying that the world is going from being "mobile-first" to "AI-first." Apple squished AI into the iPhone, and Google stuck it in the Pixel. Facebook brought it to the News Feed, and Microsoft put it in Word. Samsung bought AI startup Viv to catch up with Apple's Siri virtual assistant.

The Internet of Things will challenge the status quo of how IT and development organizations operate. Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform. In his session at @ThingsExpo, Craig Sproule, CEO of Metavine, demonstrated how to move beyond today's coding paradigm and shared the must-have mindsets for removing complexity from the development process, accelerating application delivery times, and ensuring that developers will become heroes (not bottlenecks) in the IoT revolution. Speaker Bio Craig Sproule is the CEO of Metavine where he is responsible for the company's vision, product development and customer success.

From Driverless cars being rolled out recently to robots performing surgeries, technology has surely made a stellar progress. One such example is medical robots.Medical robots are set to revolutionize the healthcare sector, especially surgeries, since they are becoming more and more acceptable, globally. They not only help in reducing the time of surgery but also ensure the accuracy of the whole process coupled with better quality of patient care, thereby increasing the demand for surgical robots across the globe. Based on Product Medical Robots is segmented into Surgical Robots, Rehabilitation Robots, Non-invasive Radiosurgery Robots, Hospital and Pharmacy Robots. Surgical Robots is classified intoLaparoscopy Surgical Robotic Systems, Orthopedic Surgical Robotic Systems, Neurosurgical Robotic Systems, Steerable Robotic Catheters.