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Photolemur is an app that utilizes artificial intelligence to make your photos look better

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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.


Flipboard on Flipboard

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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.


Deep learning architecture diagrams - FastML

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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.


133 Startups Disrupting Brick-and-Mortar Retail

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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.


Watch: Highlights of the Microsoft Data Science Summit

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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.


This charming robot: Amazon starts hunt for a AI bot you can gossip with ZDNet

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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 To Be Managed By Artificial Intelligence Systems And Cloud Services

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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.


Google's New Translator Works Almost as Well as Humans

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A jump in the fluency of Google's language software will help efforts to make chatbots less lame. Google's latest advance in machine learning could make the world a little smaller. The company is reëngineering its translation service after Google researchers invented a system that is significantly more accurate. In a competition that pitted the new software against human translators, it came close to matching the fluency of humans for some languages, such as when translating from English to Spanish. Google has already begun rolling out the new system for translations from Chinese to English (see examples showing the improvement).


Microsoft taps the brainpower of its legendary research unit in an artificial intelligence push

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Microsoft has decided it needs more real brains working on artificial intelligence. The company said Thursday it is combining the team working on bots like Cortana with its longstanding Microsoft Research lab into a single 5,000-person unit. "Microsoft has been working in artificial intelligence since the beginning of Microsoft Research, and yet we've only begun to scratch the surface of what's possible," Shum said in a statement. The move comes amid the departure of Qi Lu for health reasons, as first reported by Recode. Shum will take over the search efforts that Lu had been responsible for, while Rajesh Jha will take over responsibility for all of Office and get a promotion to executive vice president.


IBM and MIT team on cognitive computing, machine vision, artificial intelligence for healthcare

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IBM Research and the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology have joined forces to further develop the scientific field of machine vision – a core aspect of artificial intelligence. Big Blue and MIT will build the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension, or BM3C, in Cambridge, Mass. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from multiple sources for use in a variety of computer applications in industries such as healthcare, education, and entertainment. MIT researchers will collaborate with IBM scientists and engineers who will provide technology expertise and advances from the IBM Watson platform. The BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine vision that are currently impossible for machines alone to accomplish.