One of the first key takeaways from Vanderbilt Law School's conference on Thursday about artificial intelligence is that the term doesn't carry much value in the scientific community. "A.I. is whatever we can't do this year," David Lewis, a speaker who holds a PhD in computer science, said in between panel sessions. Lewis estimated we're currently experiencing the second or third wave of "A.I. hype," in which everyone uses the term to describe their technology. That's happened before, he said, and then it went out of style as a marketing buzzword. "By 2020, it'll have a negative connotation again," he predicted.

AI experts believe that computers will write as well as humans within the next 15 years. This means that any student will be able to input a poorly-written essay into a software program, which will analyze the text and reconstruct it as well-written, grammatically correct text. Since we use calculators as an extension of our minds, shouldn't we also use AI software to become better writers? This is not a hypothetical question. Across the world, teams of computer scientists are racing at a breakneck speed to construct advanced artificial intelligence that can automate thinking and writing. Last month, AlphaGo, the artificial intelligence program created by Google, beat the world-champion Lee Sodel in Go, a game that is so complex that there are more choices available in a single game than there are atoms in the entire universe.

Microsoft is notching up its Azure Media services platform by a couple of notches. The company is now going to implement its machine learning tools into its collection of cloud-based tools for video workflows. Now, you may wonder at the apparent non-existence of a relation between videos and machine learning. Machine learning after all, is used for data analysis. It can't be used with videos, right?

In 2009, Hal Varian (Google's Chief Economist) famously joked that "the sexiest job in the next 10 years will be Statistics". Fast forward to 2016, and it's abundantly clear that he was right (and how!) Compare that with, say, what the average web developer gets paid: 67,097. Companies are churning out exponentially more data every day yet struggling to derive value from it. According to McKinsey, by 2018, the US alone will face a shortage of 150,000 data analysts and an additional 1.5 million data-savvy managers. But you know this stuff.

"I never thought that I would be accepted into a human school," the robot said upon hearing of his successful enrollment at Hisashi High School in Waseda, Fukushima Prefecture. He also promised to "try my best," TASS reported. Pepper comes to the school with an impressive array of language skills, speaking both Japanese and English. He will mostly take part in English classes, though the school has told Pepper than he can also visit other classes and activities. Teachers believe learning alongside Pepper will be a positive experience for students, encouraging their desire to learn new information.

This paper addresses the problem of localizing audio sources using binaural measurements. We propose a supervised formulation that simultaneously localizes multiple sources at different locations. The approach is intrinsically efficient because, contrary to prior work, it relies neither on source separation, nor on monaural segregation. The method starts with a training stage that establishes a locally-linear Gaussian regression model between the directional coordinates of all the sources and the auditory features extracted from binaural measurements. While fixed-length wide-spectrum sounds (white noise) are used for training to reliably estimate the model parameters, we show that the testing (localization) can be extended to variable-length sparse-spectrum sounds (such as speech), thus enabling a wide range of realistic applications. Indeed, we demonstrate that the method can be used for audio-visual fusion, namely to map speech signals onto images and hence to spatially align the audio and visual modalities, thus enabling to discriminate between speaking and non-speaking faces. We release a novel corpus of real-room recordings that allow quantitative evaluation of the co-localization method in the presence of one or two sound sources. Experiments demonstrate increased accuracy and speed relative to several state-of-the-art methods.

Stitch Fix values the input of both human experts and computer algorithms in our styling process. As we've pointed out before, this approach has a lot of benefits and so it's no surprise that more and more technologies (like Tesla's self-driving cars, Facebook's chat bot, and Wise.io's augmented customer service) are also marrying computer and human workforces. Interest has been rising in how to optimize this type of hybrid algorithm. At Stitch Fix we have realized that well-trained humans are just as important for this as well-trained machines. There are similarities and differences between training humans and computers.

Advanced cyber-learning environments that involve virtual reality and artificial intelligence innovations are becoming powerful tools that can facilitate the explorations and conversations needed to solve society's challenges,

Richard Susskind spoke at a Vanderbilt Law School conference about the impact of technology on the legal profession. You don't have to look far to see how technology has changed the way people live their lives. Many patients check in with WebMD before going to their doctor's office. TurboTax has replaced accountants in some households. A new app even offers repentant churchgoers with a smartphone alternative to the confessional, complete with a drop-down menu of potential sins that need to be forgiven.

A recent project entitled'Your face is big data' saw an art school student photograph people who happened to sit across from him on the subway and then he used FindFace, a facial recognition app that taps neural-network technology, to track them down on Russian social media site VK. The FindFace service was designed for users of the largest Russian social network "Vkontakte" and is based on face recognition technology developed by N-Tech.Lab. According to a report by PC World, the Rodchenko Art School student said it was ridiculously easy to find 60 to 70 percent of the subjects aged between 18 and 35, and, along the way, he said he learned a lot about the lives of complete strangers. "My point in this art project is to show how technology breaks down the possibility of private life," he said. More details and photographs from the art project can be found here.