Headlines have been singing the praises of Apple's iOS 12 update. The new operating system is "totally worth downloading"--not only does it come with features that "may improve your life," it's also faster and smarter, according to Christina Bonnington's summary here in Slate. It's also said to be more of a gossip. According to reports, Siri's latest iteration is a lot more clue-y about the stars, with celebrity trivia among its new tricks (which include shortcuts, calorie-counting support, and the weirdly targeted "motorsports results, schedules, stats and standings"). Siri, it seems, is keeping up with the Kardashians.

Indian actress Priyanka Chopra will invest in dating app Bumble as the service prepares to expand into her native country later this year. She will also act as an adviser to the app - which requires women to make the first move - for its Indian launch. Bumble's expansion comes as firms push to make women feel safe using dating apps in India. The actress becomes the latest in a string of celebrities to take a stake in a tech venture. Bumble said Chopra will become "partner, advisor, and investor" to the tech firm.

Internet giants are getting better at countering fake news. For the most part, though, they screen content on a story-by-story basis and only block entire outlets well after they've done significant damage. Researchers from MIT's CSAIL and Qatar's Computing Research Institute might have a better solution: use AI to measure the quality of the source. Their machine learning algorithm uses collections of existing articles to gauge the accuracy and bias of a given outlet on the assumption that a fake news peddler or spin factory isn't about to change its ways. Rather than focusing on the claims themselves, it studies the language used to express those claims.

Fake news continues to rear its ugly head; in March of this year, half of the U.S. population reported seeing deliberately misleading articles on news websites. A majority of respondents to a recent Edelman survey, meanwhile, said that they couldn't judge the veracity of media reports. And given that fake news has been shown to spread faster than real news, it's no surprise that almost seven in ten people are concerned it might be used as a "weapon." Researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Lab (CSAIL) and the Qatar Computing Research Institute believe they've engineered a partial solution. In a study that'll be presented later this month at the 2018 Empirical Methods in Natural Language Processing (EMNLP) conference in Brussels, Belgium, they describe an artificially intelligent (AI) system that can determine whether a source is accurate or politically prejudiced.

Last December, the world ushered in a new era of popular music: human and artificial intelligence (AI) collaboration. Musical eras are often defined by their dominant modes of production--analog, electronic, digital--each bringing about new styles and ways of listening. This era is marked by the release of the first AI-human collaborated album, Hello World, by the music collaborative Skygge. Skygge, led by composer and producer Benoît Carré and musician and tech researcher François Pachet, translates to "shadow" in Danish and was inspired by the Hans Christian Andersen story of the same name. We now know that algorithms can learn human bias, but can they also create highly creative and emotionally engaging music?

Cameras streaming high-definition images over superfast mobile networks could improve security in schools and on our streets, and help cities run their services more efficiently, tech experts say. Beyoncé Brooks, a 17-year-old student at Millennium High School in Goodyear, Arizona, US, says her school has practice lockdowns each term to deal with gun incidents. She says there is "probably one real lockdown" a year at her school of 2,000 students. "Basically, we turn the lights off, the door is locked, and we all sit in the corner of the room huddled. The teachers don't really say anything, so we don't know if it's something that's real," she says. "We have thousands of cameras around us," says Ms Brooks, who has become a March for Our Lives organiser.

The extension of image generation to video generation turns out to be a very difficult task, since the temporal dimension of videos introduces an extra challenge during the generation process. Besides, due to the limitation of memory and training stability, the generation becomes increasingly challenging with the increase of the resolution/duration of videos. In this work, we exploit the idea of progressive growing of Generative Adversarial Networks (GANs) for higher resolution video generation. In particular, we begin to produce video samples of low-resolution and short-duration, and then progressively increase both resolution and duration alone (or jointly) by adding new spatiotemporal convolutional layers to the current networks. Starting from the learning on a very raw-level spatial appearance and temporal movement of the video distribution, the proposed progressive method learns spatiotemporal information incrementally to generate higher resolution videos. Furthermore, we introduce a sliced version of Wasserstein GAN (SWGAN) loss to improve the distribution learning on the video data of high-dimension and mixed-spatiotemporal distribution. SWGAN loss replaces the distance between joint distributions by that of one-dimensional marginal distributions, making the loss easier to compute. We evaluate the proposed model on our collected face video dataset of 10,900 videos to generate photorealistic face videos of 256x256x32 resolution. In addition, our model also reaches a record inception score of 14.57 in unsupervised action recognition dataset UCF-101.

Technology has shaped the way on which we compose and produce music: Notably, the invention of microphones, magnetic tapes, amplifiers and computers pushed the development of new music styles in the 20th century. In fact, several artistic domains have been benefiting from such technology developments; for instance, Experimental music, nonlinear music, Electroacoustic music, and interactive music. Experimental music is composed in such a way that its outcome is often unforeseeable; for instance, it may contain random generated tones, computer-generated content, variable-duration notes and "free" content. It may also include atonal melodies and microtones. Another domain is nonlinear music, in which the scenario is divided in parts whose order can be chosen at execution time. We will use the term "nonlinear" music in that sense. Nonlinear music exists from many centuries ago; for instance, Mozart's minuets in which the order of work's musical material was determined by coin-tosses. Electroacoustic music was originated by the incorporation of electronic sound production into compositional practice.

Last December, the world ushered in a new era of popular music: human and artificial intelligence (AI) collaboration. Musical eras are often defined by their dominant modes of production -- analog, electronic, digital -- each bringing about new styles and ways of listening. This era is marked by the release of the first AI-human collaborated album, Hello World, by the music collaborative Skygge. Skygge, led by composer and producer Benoît Carré and musician and tech researcher François Pachet, translates to "shadow" in Danish and was inspired by the Hans Christian Andersen story of the same name. We now know that algorithms can learn human bias, but can they also create highly creative and emotionally engaging music?

I think it is a really exciting realm of Computer Science and may turn out to be the most important advancement that I've seen in my career. More exciting, impactful and innovative than virtualization, cloud computing or IoT! I've been studying it in my free time. Consider this blog post an initial primer on the topic. What does ML & AI really mean? Machine Learning and Artificial Intelligence are being used interchangeably in the industry today, but they really mean different things and can hence cause confusion. Artificial intelligence is a broad term that has been used for many years and refers to machines being able to carry out tasks that mimic using human intelligence.