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Developers are using artificial intelligence to spot fake news
The animated face of prototype robot GRACE, Graduate Robot Attending Conference, is tested by Carnegie Mellon University computer scientist Reid Simmons, right, in the lab at the school in Pittsburgh Tuesday, July 9, 2002. It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us.
How Does Samuel R. Delany Work?
As he proposes, all writing may, in one way or another, be an expression of desire. "I always assumed that probably Marx had some kind of fetish for workmen, which is why he wanted more of them in the world," he jokes. In his own case, that means that his personal fetishes--most famously, his attraction to men with heavily bitten nails--often find their way into his stories. "That's always what I wrote about," he says, claiming that the practice goes back to childhood. "I started by writing my masturbation fantasies down in a notebook."
The wildest, wackiest tech gadgets of the year
It's that time of year again--time to pay homage to the wackiest, most wonderful tech gadgets around. As you might know by now, I'm a huge fan of "unique" gifts. Lucky for all of us who appreciate the stranger things (and the Stranger Things) this year, the cup runneth over. If you've been jonesing for a robot since the early Jetson days, Kuri ($799) delivers big time on cute and quirky, minus the ability to wash the windows and clean up after Astro. Kuri's a robotic home companion that wanders around the house shooting short videos to send to you while you're away, so that you never miss a moment.
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In this contributed article, Sharmistha Sarkar of India based Progressive Markets, highlights a handful of compelling technology advancements that are helping to drive the evolution of artificial intelligence. Industry is expected to grow at a CAGR of 46.5% from 2017 to 2025. The market is growing fast due to improved productivity through AI, its diversified application areas, and big data integration drive....
Top 10 challenges for implementing marketing mix models
Marketing Mix Modeling refers to statistical methods that attribute product performance to various marketing efforts. In the article below I describe the 10 most difficult challenges my team deals with when tackling these models. In subsequent articles I will discuss the different model choices along with their associated pros/cons. Enjoy the article and please comment at the bottom when you are finished. Below are the top 10 challenges faced by modelers of media mix.
News With Views UN Scheduled Hearings On Approving Killer Robots
There's a well-devised, satanic conspiracy to replace humans with robots. This conspiracy-fact is being played out between government, a specific group of billionaires and the mad scientist assembling this replacement project. The Universal Basic Income aspect of this conspiracy is the monetary pacifier, the mass domestication, the frog in the pot of gradually boiling water, if you will, to prevent a premature, informed revolt before the actual replacement process. You may think a mechanical robot like the one in the movie Chappie is cute and it may make you feel all warm and fuzzy. You may have even acquired a protective instinct for robots, while watching the movie, which I'm sure, is the intended purpose.
Deep learning and artificial intelligence: Making a big deal of big data
AWS DeepLens Looking for a new way to learn machine learning? Let a machine teach you with AWS DeepLens, the world's first deep learning enabled video camera for developers. Designed to connect securely to a variety of AWS offerings, including AWS IoT, Amazon SQS, Amazon SNS, and Amazon DynamoDB, AWS DeepLens uses Amazon Kinesis Video Streams to stream video back to AWS and Amazon Rekognition Video to apply advanced video analytics. Easy to customize and fully programmable with AWS Lambda, AWS DeepLens runs on any deep learning framework, including TensorFlow and Caffe.
Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video
Moore, Brian E., Gao, Chen, Nadakuditi, Raj Rao
Abstract--This work presents a new robust PCA method for foreground-background separation on freely moving camera video with possible dense and sparse corruptions. Our proposed method registers the frames of the corrupted video and then encodes the varying perspective arising from camera motion as missing data in a global model. This formulation allows our algorithm to produce a panoramic background component that automatically stitches together corrupted data from partially overlapping frames to reconstruct the full field of view. We model the registered video as the sum of a low-rank component that captures the background, a smooth component that captures the dynamic foreground of the scene, and a sparse component that isolates possible outliers and other sparse corruptions in the video. The low-rank portion of our model is based on a recent low-rank matrix estimator (OptShrink) that has been shown to yield superior low-rank subspace estimates in practice. To estimate the smooth foreground component of our model, we use a weighted total variation framework that enables our method to reliably decouple the true foreground of the video from sparse corruptions. We perform extensive numerical experiments on both static and moving camera video subject to a variety of dense and sparse corruptions. Our experiments demonstrate the state-of-the-art performance of our proposed method compared to existing methods both in terms of foreground and background estimation accuracy.
[D] What are some novel/unique applications of Machine Learning in Electrical Engineering? • r/MachineLearning
Most of the literature in ML that I've come across has been heavily based in either Computer Vision, Robotics1 or NLP. Are there any other lesser known, but really exciting applications of Machine Learning in Electrical Engineering, currently being researched? Some examples would be designing chips, circuits or control algorithms (not robotics based).