This year's Consumer Electronics Show is bringing the latest in tech including self-driving suitcases and motorcycles. The Numi toilet from Kohler was impossible to ignore. Announced at the Consumer Electronics Show in January, 2018, the new $8,000 toilet was not just touted to "bring you the finest in personal comfort and cleansing," but it also had voice commands via Alexa. Ready to flush or want to heat up the seat? Just ask Amazon's Alexa personal assistant to do it for you.

At last, you've found yourself with an Amazon Echo speaker. The Echo (or Echo Dot, or Echo Tap, or Echo Show, or Echo Plus, or Echo Spot) is now in your kitchen, and it's ready for your every command. With so many Echo models, is that Echo even the best fit? Before you toss that gift receipt, here's a quick read to figure out which Amazon Echo is right for your lifestyle. Alexa can perform so-called "skills."

Graph classification is a problem with practical applications in many different domains. To solve this problem, one usually calculates certain graph statistics (i.e., graph features) that help discriminate between graphs of different classes. When calculating such features, most existing approaches process the entire graph. In a graphlet-based approach, for instance, the entire graph is processed to get the total count of different graphlets or subgraphs. In many real-world applications, however, graphs can be noisy with discriminative patterns confined to certain regions in the graph only.

Although I mainly saw males, I did encounter Dutch speakers with Belgian, northern dutch and southern dutch accents. So although of course there is a million different combinations of genders and accents, at least here is quite a bit of diversity already. I can't speak for the Belgians but the fact that there is a seperation between'zachte g' and'harde g' is already praise worthy if you ask me. I won't be donating my voice but really if it's for the greater good i'm willing to do a few dozen of validations per day. I've noticed though that after i registered i only heard dutch phrases.

Graph classification is a problem with practical applications in many different domains. To solve this problem, one usually calculates certain graph statistics (i.e., graph features) that help discriminate between graphs of different classes. When calculating such features, most existing approaches process the entire graph. In a graphlet-based approach, for instance, the entire graph is processed to get the total count of different graphlets or subgraphs. In many real-world applications, however, graphs can be noisy with discriminative patterns confined to certain regions in the graph only.

Train the model k time based on a k-fold cross validation, predict the out of folds, concatenate them, and find the optimal threshold for it. This currently works the best, but I can also see that I can either get lucky on the threshold, or not and sometimes the optimal test threshold is quite far away. Also, the different models have sometimes quite different optimal thresholds on their own folds. There seems to be some form of "winner's curse" [1].

Very naive question, but when we perform augmentations on the training set, do we scale ALL the classes constantly or just the minority class?

We've quickly come to accept that brands know as much about us as we know about ourselves. Facebook serves you ads for cat food after you talk about getting a cat. Target knows you're pregnant before you tell your friends and family. Even Instagram knows about your shameful predilection for Hallmark Christmas movies. So it stands to reason that fewer pics of you with your significant other on Instagram could signal to apps and brands that your relationship may be coming to an end.

For the first issue of the PCMag Digital Edition in 2019, we're fast-forwarding to envision what technology--and our tech-driven society--will look like in 2039. We wanted to explore the myriad ways in which tech will be more intertwined with our lives and will have changed our culture. To do so, we interviewed a select group of futurists, execs, academics, researchers, and a speculative fiction writer, who gave us some thoughtful predictions. Each of our interviewees has a unique perspective on the most important factors that will influence our tech-driven future, including artificial intelligence, automation, biotechnology, nanotechnology, autonomous vehicles, Internet of Things devices, smart cities, and much more. They also speculate how broader issues such as climate change and online privacy and security will affect us and the technology with which we'll be living. It's our best educated guess at predicting what our world and technology's role in it will look like--whether our lives will be dystopian, utopian, or somewhere in that vast gray area in the middle. Jason Silva is host of the Emmy-nominated series Brain Games on National Geographic. He also created and hosts the YouTube series "Shots of Awe." The ebullient Venezuelan-born documentary filmmaker, speaker, and TV personality--who was once described by The Atlantic as "a Timothy Leary of the viral video age"--is a techno-optimist whose ideas are influenced by (among others) fellow futurist Ray Kurzweil, Wired founding editor Kevin Kelly and his concept of the Technium. In the next 20 years, we're going to see exponential progress in some of these nascent technologies, like virtual reality and augmented reality. I think the next thing to dematerialize is the smartphone itself. What that looks like, who knows? Maybe it's a pair of eyeglasses we put on that are connected to some kind of computational device, and it will beam an augmented reality interface that fully overlays, that is contextually aware, and enhances the way we interface with the world--so that essentially, each one of us has that kind of personalized experience of reality.

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