Intel is making it extra-clear that computer vision hardware will play a big role in its beyond-the-PC strategy. The computing behemoth has just acquired Movidius, a specialist in AI and computer vision processors. It sees Movidius as a way to get high-speed, low-power chips that can power RealSense cameras in devices that need to see and understand the world around them. Movidius has already provided the brains behind gadgets like drones and thermal cameras, many of which are a logical fit for Intel's depth-sensing tech -- and its deals with Google and Lenovo give nothing to sneeze at, either. However, it shows that Intel is increasingly determined to find new avenues to explore now that it can't count on large jumps in processor performance to maintain the bottom line.

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Innovation lover, Data addicted, Hyper curious - I'm the one that turns ideas into projects that become reality

Continuing our series of articles on Innovation we recently talked to Mike Zimmerman, Founder of BuildingIQ, about the approaching 3rd Step change in Building Energy Management (BEMS) technology. The 1st step change in BEMS technology was of course the move to DDC controls. Since then we have seen a 2nd wave of innovation in analytics; where companies have started to extract useful data using open protocols and analyze it to help report on performance or identify operating issues. But the limitation of this approach is that it only provides a static "point in time" view of the building. Additionally, any issues identified still require human intervention to address.

Intel is making it extra-clear that computer vision hardware will play a big role in its beyond-the-PC strategy. The computing behemoth has just acquired Movidius, a specialist in AI and computer vision processors. It sees Movidius as a way to get high-speed, low-power chips that can power RealSense cameras in devices that need to see and understand the world around them. Movidius has already provided the brains behind gadgets like drones and thermal cameras, many of which are a logical fit for Intel's depth-sensing tech -- and its deals with Google and Lenovo give nothing to sneeze at, either.

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By 2020, the market for machine-learning applications will reach 40 billion, per IDC. The next time you see Democratic presidential nominee Hillary Clinton with an unflattering look on her face in a TV spot supporting GOP rival Donald Trump, it's all but certain you can attribute the ad creative to artificial intelligence. The Republican National Committee is using machine-learning software from Veritone, a 2-year-old player that just secured 50 million in funding. Designed to work with laser-fast precision, its audio-based system lets the RNC zip through all the publicly available times Clinton has spoken on TV, radio or online video to scoop up her angriest or oddest moments. The company is about to add a visual-sentiment feature, which will zero in on facial expressions and make cringe-worthy moments even easier to find.

How many times have you seen an article start this way? Now, you have just seen another one! But I want to avoid completing that sentence, and consequently I will skip definitions and analogies here, even though they are very important and my colleagues (and students) know that I indulge in analogies profusely when attempting to explain anything. Instead, the focus here will be on fundamental concepts that are important to all students and practitioners of Data Science. Let me begin with a joke (which is not quite an "analogy"): A rich man wanted to invest in breeding and training a class of racing horses that would win as many races as possible.

IBM used its artificial intelligence platform Watson to create a movie trailer for the film Morgan, a tale of the fate of an artificially created human. The IBM team worked with 20th Century Fox, it said. John R. Smith, IBM Fellow, Manager, Multimedia and Vision, said in a blog: "How do you create a movie trailer about an artificially enhanced human? Fox wanted to explore using artificial intelligence (AI) to create a horror movie trailer that would keep audiences on the edge of their seats." It could have been generated using Artificial Intelligence.

Chatbots are a hot topic in tech -- positioned at the intersection of many macro tech trends like the rise of artificial intelligence, messaging apps surpassing social apps in users, and enterprises struggling with customer acquisition and engagement on mobile. Investment dollars are gushing into the leading messaging apps, and all of the tech giants have announced significant new initiatives. If you have ever used Amazon Alexa, you can see what the hype is about. But will chatbots be as revolutionary as the hype would have it? To predict how chatbots will evolve, we can look to Asia, a region that has led the West in this space. WeChat is often cited as the poster child for chatbots.