Digitization has changed the way we process and analyze information. There is an exponential increase in online availability of information. From web pages to emails, science journals, e-books, learning content, news and social media are all full of textual data. The idea is to create, analyze and report information fast. This is when automated text classification steps up.

In December, Motherboard reported that a Redditor called "deepfakes" was using machine learning to create pornography in which adult actresses' faces were somewhat realistically replaced by female celebrities. The process is similar to the Paul Walker face-mapping from "Furious 7" or the young Carrie Fisher scene from the end of "Rogue One." The example given at the time was a typical porn video where the actress's face was replaced by Gal Gadot of "Wonder Woman" fame. Since then, the technology has been streamlined to the point where even the least technical people can put faces into a new app and make whatever celebrity porn they want to make, Motherboard reported Wednesday. The future is terrible: Now everyone is making AI-generated fake porn with other people's faces https://t.co/AWYVkDENRd

ABSTRACT We use automatic speech recognition to assess spoken English learner pronunciation based on the authentic intelligibility of the learners' spoken responses determined from support vector machine (SVM) classifier or deep learning neural network model predictions of transcription correctness. Using numeric features produced by PocketSphinx alignment mode and many recognition passes searching for the substitution and deletion of each expected phoneme and insertion of unexpected phonemes in sequence, the SVM models achieve 82% agreement with the accuracy of Amazon Mechanical Turk crowdworker transcriptions, up from 75% reported by multiple independent researchers. Using such features with SVM classifier probability prediction models can help computeraided pronunciation teaching (CAPT) systems provide intelligibility remediation. Index Terms-- phoneme alignment, pronunciation assessment, computer aided language learning, binary features 1. INTRODUCTION Authentic intelligibility, the ability of listeners to correctly transcribe recorded utterances, initially used for CAPT by [1] and [2], is a better measure of pronunciation assessment for spoken language learners compared to mispronunciations identified by expert pronunciation judges or panels of experts, because such mispronunciations are associated with only 16% of intelligibility problems, according to [3], who state: We investigated... which words are likely to be misrecognized and which words are likely to be marked as pronunciation errors. Words perceived as mispronounced remain intelligible in about half of all cases.

When we point our smartphone camera, tap on the screen and take a picture, it's easy to forget, photography hasn't always been as simple as it is today – but that's the illusion of AI – what appears simple is in fact, incredibly complex. Phones like the Honor View10 are powered by the Kirin 970 processor, with AI at its heart. It sees through the dual lenses around the back, identifies what it's looking at using its Neural Processing Unit and captures your memories in stunningly high-resolution. But how did we arrive at the age of AI photography and what will smartphone photography look like in the future? As little as 20 years ago, digital cameras were anything but the norm – and the idea of a camera on your smartphone?

I became fascinated with machine learning about a month ago after looking into how alphazero beat stockfish (chess). I am throwing together this blog documenting my first attempt at building a neural network from scratch in the hopes that other beginners can follow the logic as I break it down for myself. Would love any feedback for the content, graphics, format, etc! Also especially appreciate any corrections!

Back in December, it was discovered that Reddit users were creating fake pornography using celebrity faces pasted on to adult film actresses' bodies. The disturbing videos, created by Reddit user deepfakes, look strikingly real as a result of a sophisticated machine learning algorithm, which uses photographs to create human masks that are then overlaid on top of adult film footage. Now, AI-assisted porn is spreading all over Reddit, thanks to an easy-to-use app that can be downloaded directly to your desktop computer, according to Motherboard. Star Wars lead Daisy Ridley has been featured in a fake video on the Reddit thread. One of the site's users, deepfakeapp, created a desktop application called FakeApp that lets users take adult film footage and swap any female celebrity's face onto porn actresses' bodies The app, called FakeApp, uses deepfakes' algorithm, but doesn't require any knowledge of coding.

American poet Ralph Waldo Emerson once said, "Every artist was first an amateur." He likely never thought those words would apply to machines. Yet artificial intelligence has demonstrated a growing aptitude for creativity, whether writing a heavy-metal rock album or producing an original portrait that is strikingly reminiscent of a Rembrandt. Applying AI to the art world might seem unnecessarily derivative; there are, of course, plenty of humans delivering awe-inspiring work. Proponents say, however, the real beauty of training AI to be creative does not lie in the end product--but rather in the technology's potential to expand on its own machine-learning education, and to solve problems by thinking outside the box far faster and better than humans can.

Thu 25 Jan 2018 12.07 EST Last modified on Thu 25 Jan 2018 12.33 EST Advanced machine learning technology is being used to create fake pornography featuring real actors and pop stars, pasting their faces over existing performers in explicit movies. The resulting clips, made without consent from the women whose faces are used, are often indistinguishable from a real film, with only subtly uncanny differences suggesting something is amiss. A community on the social news site Reddit has spent months creating and sharing the images, which were initially made by a solo hobbyist who went by the name "deepfake". When the technology site Motherboard first reported on the user in December last year, they had already made images featuring women including Wonder Woman star Gal Gadot, Taylor Swift, Scarlett Johansson, and Game of Thrones actor Maisie Williams. In the months since, videos featuring other celebrities including Star Wars lead Daisy Ridley, Game of Thrones's Sophie Turner, and Harry Potter star Emma Watson have been posted on the site, which has become the main location for sharing the clips.

The fight to sell you speakers you can also talk to is getting more intense – and more cheap. Sonos has announced it will sell its One smart speaker – which uses Amazon's Alexa – for cheaper than normal, in a deal launching just a day before the Apple HomePod. Apple's smart speaker contains many of the same features, and the two are part of an increasingly busy markets for sound systems you can talk to. Sonos is referring to the bundle as "Sonos Two" – that is, two of its Sonos One smart speaker. That speaker includes many of the same features as the HomePod: built-in microphones for talking to a voice assistant, and the ability to listen to music from your home.

Quantcast, an AI technology company focused on the marketing and publishing industries, announced that it will expand its advertising solutions into seven markets across Asia, connecting brands with an online audience of up to 300 million consumers. The company already operates in Australia and New Zealand. Marketers across Hong Kong, Indonesia, Malaysia, Philippines, Singapore, Taiwan, and Thailand will now be able to tap into Quantcast's live data insights drawn from more than 100 million online destinations to drive more effective brand awareness and performance campaigns. Andrew Double, Quantcast's Australia and New Zealand Managing Director, will taking on an expanded role to lead the company's growth in the Asia-Pacific region. Konrad Feldman, Quantcast's Chief Executive Officer and Founder commented, "Marketing is at a tipping point with AI set to transform every customer experience, every company and every industry. Marketers in APAC are looking for better ways to engage digital audiences that are both efficient and effective. We're excited to help brands and their agency partners leverage the power of Q, our audience behavior platform."