This is thanks to computational photography that will make each snap shot look like it was taken using a professional camera. There is no denying that one of the most sought after features of any smartphone today is its camera. Ever since image sharing sites and social media platforms rose to popularity, sharing pictures of just about anything has taken over the lives of many people around the world. Smartphone manufacturers started developing camera phones that can capture high-quality images to satisfy the needs of photo-savvy individuals. If that is not enough, some of these mobile phone giants partnered with famous camera makers to create the best camera phones of today.

Researchers have devised a new way to monitor sleep stages without sensors attached to the body. Their device uses an advanced artificial intelligence algorithm to analyze the radio signals around the person and translate those measurements into sleep stages: light, deep, or rapid eye movement (REM).

As training data, drawn from planes_features.csv,

In cases where an L1-norm or L-infinity norm better describe distance, this could be useful. For example, dealing with a square-grid pattern in city streets may yield better results when using scaled geographic coordinates. K-means is effectively an algorithm that considers all points around each cluster center to be distributed around that point according to an N-dimensional normal distribution with a constant diagonal and no correlations. This works well when your clusters can be approximated to be roughly a circular shape (which corresponds to the L2 norm of Euclidean space). If your cluster patterns were squares, cubes or hypercubes, this would work better for an L-infinity norm, and likewise diamond shapes would work better with an L1-norm.

Artificial intelligence is already transforming the world around us, but one expert predicts terrifying changes on the horizon over the next 30 years. Professor Toby Walsh believes machine learning has the power to radically alter life as we know it by the year 2050. Among the more disturbing prophecies, which could be taken straight from an episode of Black Mirror, is that people will live on as chatbots after they die. AI is already transforming the world around us, but one expert predicts terrifying changes on the horizon over the next 30 years. Dr Walsh's vision for the machine world is outlined in a new book entitled'It's Alive!: Artificial Intelligence from the Logic Piano to Killer Robots'.

Artificial intelligence and machine learning are all the rage in Silicon Valley at the moment, but for consumers, both technlogies are still a real mystery. Thanks to Hollywood movies that villainize AI, most people view it in a negative light. Even Elon Musk and Bill Gates have reservations. I am not an expert in either topic, but I have worked on projects that use AI and ML and understand how, when used properly, both will be transformational in the future. Perhaps their most important application is in the field of medical research.

Amazon is always looking for fresh and innovative ways to make Alexa feel more like a convenient appliance in your home. Whether you're looking to order a pizza, or check the traffic and weather. The virtual assistant can do a whole host of things, and thanks to an upgrade this week, Alexa can now do even more than before. Alexa can now assist you in finding the right music for almost any kind of activity you can think of. Wanting to take a nap, go for a run, cook in the kitchen, or even get intimate with your significant other in the bedroom.

Taking Instagram-worthy photos is one thing, editing them is another. Most of us just upload a pic, tap a filter, tweak the saturation, and post. If you want to make a photo look good without the instant gratification of the Reyes filter, enlist a professional. Researchers from MIT and Google recently showed off a machine learning algorithm capable of automatically retouching photos just like a professional photographer. Snap a photo and the neural network identifies exactly how to make it look better--increase contrast a smidge, tone down brightness, whatever--and apply the changes in a 20th of a millisecond.

We offer an opportunity for companies and individuals working on interesting problems in AI to introduce their work to the community through the IAMA. Please contact /u/dejormo for more information. We would love to hear from you!

Identifying 3 moss species by deep learning, using the "chopped picture" method Graduate School of Agriculture, Kyoto University, Japan * corresponding author: ise@kais.kyoto-u.ac.jp Abstract In general, object identification tends not to work well on ambiguous, amorphous objects such as vegetation. In this study, we developed a simple but effective approach to identify ambiguous objects and applied the method to several moss species. As a result, the model correctly classified test images with accuracy more than 90%. Using this approach will help progress in computer vision studies. Introduction Especially in recent years, deep learning has become a very effective tool for object identification (Krizhevsky et al. 2012, Szegedy et al. 2015).