From digital assistants like Siri to Tesla's self-driving cars, artificial intelligence and deep learning (a type of machine learning) are churning out today's tech breakthroughs. As new innovations are released, more doors open up to leverage them in existing fields, like integrating facial recognition in iPhones or iOS apps. That said, taking the time to understand how these innovations operate is a smart move -- whether you plan to implement them as an app developer or merely use them at work. Learn the foundations of these groundbreaking fields with the Pay What You Want: AI & Deep Learning Bundle, which nets you a host of e-books and training courses for a price that you get to pick. Here's how the deal works: Simply pay what you want, and you'll instantly unlock one of the collection's ten resources.

Pond5, a content marketplace for high-quality royalty-free video, has developed a new AI (Artificial Intelligence) search engine that allows users to search by images instead of words. The artificial intelligence that drives Pond5 Visual Search gives customers the ability to show, rather than tell, what they're looking for. Eliminating the difficult task of trying to put a visual concept into words, Visual Search delivers instant results for licensable media with a similar look to any file a customer chooses. This technology recognizes patterns in shape, color and composition, and compares them to the tons of images and clips that already exist on the Pond5 platform in order to find similar results. According to the company the technology is a patent-pending AI-based Visual Search engine which gives users the ability to discover media based on existing imagery.

Elon Musk has famously compared AI to'summoning the devil'. Now the Tesla billionaire claims the technology could lead to the creation of immortal robot leaders from which humanity can never escape. His comments were made in the new documentary'Do You Trust This Computer?' by Chris Paine which premiered in Los Angeles last night. Elon Musk has famously compared AI to'summoning the devil'. The documentary explores the potential advantages and dangers of AI.

Elon Musk has famously compared AI to'summoning the devil'. Now the Tesla billionaire claims the technology could lead to the creation of immoral robot leaders from which humanity can never escape. His comments were made in the new documentary'Do You Trust This Computer?' by Chris Paine which premiered in Los Angeles last night. Elon Musk has famously compared AI to'summoning the devil'. The documentary explores the potential advantages and dangers of AI.

The purpose of a consumer drone remains nebulous these days. Depending on who you ask, you'll get a different answer. Drones are great for sophisticated aerial photography and video, but they're also adept at surveying empty lots of land and crowded real estate, or measuring agricultural yield and helping climate model the Arctic. Even as drones get more sophisticated, cheaper, and smaller, there isn't an easy answer beyond the fact that unmanned aerial vehicles are cool gadgets and fun to fly -- granted, where and when the Federal Aviation Administration deems it legal to do so. But what if a drone was smart enough to handle itself, in any and all situations? What if the drone didn't need to be flown at all, because software did it for you?

"Fake news" has become a buzzword, thanks to social media. This becomes even more worrisome in light of the recent scandal about Facebook's shady data-sharing and advertising practices. But we haven't seen anything yet. Because of the latest technological breakthroughs in AI, reality itself--or our perception of it--could be at stake. With tools that are available right now, AI-driven "fake" videos are ready for primetime.

Artificial intelligence can influence your travel plans, anticipate your online orders and improve efficiency around the house. In the entertainment sphere, there's an AI technology to make you feel more while watching a movie. Researchers at the MIT Media Lab were able to train a machine to manipulate the emotional responses of video viewers. Their findings were published in collaboration with strategic consulting firm McKinsey & Company. The MIT team examined the neural perceptions of thousands of people who watched movies, videos, online features and television programs in sections. They paired their reactions to a neural network, which guessed which parts of each clip would spark the greatest emotional response in humans.

'Do You Trust This Computer?'

Binge-watching TV shows on streaming services is becoming increasingly popular. However, there is a paucity of comprehensive metrics to effectively summarize such media watching behavior. We address this gap by presenting two new metrics—Bingeability and Ad Tolerance—to quantify key aspects of watching streaming TV interspersed with ads. These metrics are motivated by consumer psychology literature on hedonic adaptation and also reflect media consumption behavior. Using machine learning methods, including ensembles of classification trees, we identify the key predictors of these metrics, study non-linear effects, and rank the predictors in order of predictive power. The superiority and validity of these metrics is also discussed.

While there have been significant advances in detecting emotions from speech and image recognition, emotion detection on text is still under-explored and remained as an active research field. This paper introduces a corpus for text-based emotion detection on multiparty dialogue as well as deep neural models that outperform the existing approaches for document classification. We first present a new corpus that provides annotation of seven emotions on consecutive utterances in dialogues extracted from the show, Friends. We then suggest four types of sequence-based convolutional neural network models with attention that leverage the sequence information encapsulated in dialogue. Our best model shows the accuracies of 37.9% and 54% for fine- and coarse-grained emotions, respectively. Given the difficulty of this task, this is promising.