Computers can already recognize you in an image, but can they see a video or real-world objects and tell exactly what's going on? Researchers are trying to make computer video recognition a reality, and they are using some image recognition techniques to make that happen. Researchers in and outside of Google are making progress in video recognition, but there are also challenges to overcome, Rajat Monga, engineering director of TensorFlow for Google's Brain team, said during a question-and-answer session on Quora this week. The benefits of video recognition are enormous. For example, a computer will be able to identify a person's activities, an event, or a location.

In the burgeoning field of computer science known as machine learning, engineers often refer to the artificial intelligences they create as "black box" systems: Once a machine learning engine has been trained from a collection of example data to perform anything from facial recognition to malware detection, it can take in queries--Whose face is that? Is this app safe?--and spit out answers without anyone, not even its creators, fully understanding the mechanics of the decision-making inside that box. But researchers are increasingly proving that even when the inner workings of those machine learning engines are inscrutable, they aren't exactly secret. In fact, they've found that the guts of those black boxes can be reverse-engineered and even fully reproduced--stolen, as one group of researchers puts it--with the very same methods used to create them. In a paper they released earlier this month titled "Stealing Machine Learning Models via Prediction APIs," a team of computer scientists at Cornell Tech, the Swiss institute EPFL in Lausanne, and the University of North Carolina detail how they were able to reverse engineer machine learning-trained AIs based only on sending them queries and analyzing the responses.

IBM Watson can do much more than answer questions on Jeopardy. Earlier this month, the artificial intelligence system created a movie trailer. It also powers driverless cars and is helping doctors with cancer care and research. Watson is IBM's bet on the next era of computing that is built to understand, reason, learn and interact, according to IBM Watson's Chief Marketing Officer Steve Gold. "It's not speech recognition like Siri, not speech synthesis like Alexa, but actually understanding human languages," Gold told Mashable.

Photolemur is the world's first fully automated photo enhancement solution with both casual and seasoned photographer in mind. It is powered by a state-of-the-art Artificial Intelligence algorithm that not only fixes your image's imperfections without human involvement, it learns! What does this mean for you? You can create amazing images as vivid as you remember them without the use of complicated image editing software. As you process your images in Photolemur, the AI analyzes common compression, noise and color balance problems and corrects them on the fly.

It was the best of times p His photographs capture the culture of rock and punk music; the beguiling moments with the Ramones, Patti Smith, Talking Heads, Blondie, Dead Boys, Richard Hell, Lydia Lunch and many more as they made New York's CBGB club their home in the late 1970s. John Thackwray, a French and South African commercial filmmaker and photographer, has traveled the globe since 2010, and photographed over 1,200 bedrooms of young people born in the 1980s and 1990s. More than a decade ago, the European Space Agency launched an orbiter named Rosetta, bound on a circuitous voyage to comet 67P/Churyumov-Gerasimenko. In the years since, Rosetta has been drawn in and flung along by multiple gravity assist maneuvers, visiting the Earth three times and making … A few weeks ago we suggested you follow 5 topics that cover the more basic aspects of the business of blogging. Today let's focus on something equally important: the life of a blogger. This week I attended MMA SM2 Innovation Summit in New York, which took place during Advertising Week.

Like a wild stream after a wet season in African savanna diverges into many smaller streams forming lakes and puddles, deep learning has diverged into a myriad of specialized architectures. Each architecture has a diagram. Here are some of them. Neural networks are conceptually simple, and that's their beauty. A bunch of homogenous, uniform units, arranged in layers, weighted connections between them, and that's all.

I just got back from Atlanta, the host of the Microsoft Machine Learning and Data Science Summit. This was the first year for this new conference, and it was a blast: the energy from the 1,000 attendees was palpable. I covered Joseph Sirosh's keynote presentation yesterday, but today I wanted to highlight a few other talks from the program now that the recordings are available to stream. But for me personally, the highlight of the event was the keynote presentation by Dr Edward Tufte on the Future of Data Analysis. I had the distinct honour of introducing Dr Tufte to the stage, who has long been a hero of mine. Please enjoy his presentation, embedded below.

Augmented/Virtual Reality Tools – Startups that leverage augmented or virtual reality to aid retailers in layout of stores and the design of promotional displays. InContext Solutions, which has worked with clients like Walmart, Nestle, and Kellogg's, lets brands visualize marketing concepts and test new designs on shoppers in virtual reality to gauge their efficacy before launch. Augment aims to help brands, such as General Mills, L'Oreal, and Coca-Cola, pitch their vending machines, kiosks, or merchandise displays to retailers by showing how they would look in augmented/virtual reality. Beacon-Based Analytics and Marketing – Companies that provide hardware and software to help stores track visitors. Many focus on data collection for internal analytics, such as merchandise tracking, adjusting staffing levels, monitoring promotions, etc. Euclid Analytics, for example, tracks visitors to monitor the impact of promotions on driving store visits and to better understand when people visit stores and specific aisles.

Amazon has launched a 2.5 million competition for teams of students to create an artificial intelligence charming enough that people can chat to it about celebrity gossip and sports. The'Alexa Prize' is named after the service that powers Amazon's voice-activated smart speaker, the Amazon Echo. The goal of the inaugural competition is to build a'socialbot' for Alexa that will converse with people about popular topics and news events. The team with the highest-performing socialbot will win a 500,000 prize, while there's a 1 million for the team's university if their socialbot can chat "coherently and engagingly" with humans for 20 minutes. Up to ten teams of students will also win a 100,000 award, Alexa-powered devices, free AWS services, and support from the Alexa team.

Smart transportation uses information technology and artificial intelligence to efficiently manage and coordinate transportation systems. The application of smart transportation network allows the travelling population to have better knowledge of the traffic for better coordination. In addition, the use of smart transportation also ensures safety for the drivers. The market is experiencing growth due to their increasing demand across all geographic locations. The rising need for safe and secured transportation and planning of smart cities by governments have propelled the growth of the global smart transportation market. However, the high initial investment and lack of data might restrain the market's growth during the forecast period.