The gorgeously handcrafted stop-motion film seems to embark on that familiar hero's journey, only to find its own way home. "As we structured the thing, we were definitely well aware of the ground we were treading on, the formulas, the templates, the classics of the genre," says "Kubo" director and Laika Entertainment chief Travis Knight. "But while'Kubo' is in that tradition, it takes a different path when it gets to the end." The film looks different as well, with its character models and environments inspired by Japanese folklore. It's not a sequel, it's not based on specific myths or books; it just feels like it is rooted deeply somewhere.
For the four-hundredth anniversary of Shakespeare's death, Gregory Doran, the artistic director of the Royal Shakespeare Company, wanted to dazzle. He turned to "The Tempest," the late romance that includes flying spirits, a shipwreck, a vanishing banquet, and a masque-like pageant that the magician Prospero stages to celebrate his daughter's marriage. "The Tempest" was performed at the court of King James I, and it may have been intended in part to showcase the multimedia marvels of Jacobean court masques. "Shakespeare was touching on that new form of theatre," Doran told me recently, over the phone. "So we wanted to think about what the cutting-edge technology is today that Shakespeare, if he were alive now, would be saying, 'Let's use some of that.' " The politics behind Shakespeare and stage illusion are more fraught than usual these days.
Are you familiar with deep learning? Deep learning describes the ability for artificial intelligence (AI) algorithms to learn from our behavior using brain-like structures called neural networks, and it's changing the field of human resources in significant ways. AI programs can predict outcomes based on past experiences fed into the program. Because AI can recognize patterns and analyze data at light speed, it can help HR directors make decisions with greater confidence. From finding and recruiting prospects to streamlining employee assessment processes, machine learning and AI can make it easier for HR executives to do their jobs better--and today's technology is only the beginning.
What makes Bach sound like Bach? MusicNet is a new publicly available dataset from UW researchers that labels each note of 330 classical compositions in ways that can teach machine learning algorithms about the basic structure of music.Yngve Bakken Nilsen, flickr The composer Johann Sebastian Bach left behind an incomplete fugue upon his death, either as an unfinished work or perhaps as a puzzle for future composers to solve. A classical music dataset released Wednesday by University of Washington researchers -- which enables machine learning algorithms to learn the features of classical music from scratch -- raises the likelihood that a computer could expertly finish the job. MusicNet is the first publicly available large-scale classical music dataset with curated fine-level annotations. It's designed to allow machine learning researchers and algorithms to tackle a wide range of open challenges -- from note prediction to automated music transcription to offering listening recommendations based on the structure of a song a person likes, instead of relying on generic tags or what other customers have purchased. "At a high level, we're interested in what makes music appealing to the ears, how we can better understand composition, or the essence of what makes Bach sound like Bach.
Research in artificial intelligence (AI) is known to have impacted medical diagnosis, stock trading, robot control, and several other fields. Perhaps less popular is the contribution of AI in the field of music. Nevertheless, artificial intelligence and music (AIM) has, for a long time, been a common subject in several conferences and workshops, including the International Computer Music Conference, the Computing Society Conference and the International Joint Conference on Artificial Intelligence. In fact, the first International Computer Music Conference was the ICMC 1974, Michigan State University, East Lansing, USA Current research includes the application of AI in music composition, performance, theory and digital sound processing. Several music software applications have been developed that use AI to produce music.
This is the last – for now – installment of my mini-series on sentiment analysis of the Stanford collection of IMDB reviews (originally published on recurrentnull.wordpress.com). So far, we've had a look at classical bag-of-words models and word vectors (word2vec). We saw that from the classifiers used, logistic regression performed best, be it in combination with bag-of-words or word2vec. We also saw that while the word2vec model did in fact model semantic dimensions, it was less successful for classification than bag-of-words, and we explained that by the averaging of word vectors we had to perform to obtain input features on review (not word) level. So the question now is: How would distributed representations perform if we did not have to throw away information by averaging word vectors?
If you have and you want to learn the science behind them, you have come to the right place. In this course, I will show you how these companies use Recommender systems or Machine Learning to influence your purchasing decisions. This course is timely and extremely relevant now as almost all major service-oriented companies function on recommender systems. You will understand how these systems work and learn how to build and use your own recommender systems, just like these big companies do. Learn how to build the recommender systems that are being used by almost every big service-oriented company in today's world with this introductory course for beginners.
The news that Christina Grimmie -- the 22-year-old singer who, as a New Jersey teen, made a name for herself on YouTube before broadening her fame in 2014 on Season 6 of "The Voice" – was shot and killed Friday while signing autographs for fans after a concert in Orlando, Fla., is tragic. But for fans of "The Voice" who watched Grimmie show off, during her time on the show, not only her impressive vocal chops and stage presence, but also her musical creativity, willingness to experiment and upbeat resilience, the loss must be heartbreaking. Those who watched Grimmie turn four chairs during her blind audition and then stick around to finish third on the show, behind only sweet, shy, country-singing runner-up Jake Worthington (of Team Blake Shelton) and silky-soulful winner Josh Kaufman (of Team Usher), knew she was an unusual talent. Grimmie's coach, Adam Levine, believed in her so fiercely that, at one point, he promised the audience she would end up winning the show. Then, when she didn't, he announced that he planned to sign her to his own label.
The skyline in Sydney has become the stage for an impressive drone show. As the city's rainy weather finally subsided, Intel kicked off its show with 100 illuminated drones taking to the sky above Sydney Harbour on Wednesday night. The display will take place across five nights as part of Sydney's Vivid Festival, with Sydney's Youth Orchestra performing Beethoven's Fifth Symphony as the soundtrack. This isn't the first time such a performance has taken place. The inaugural Intel drone event, which broke a Guinness World Record for the most UAVs flying simultaneously, happened in Hamburg, Germany, in 2015.
This wasn't a your average jazz band member, though--this was Shimon, a four-armed robot marimba player built by the Georgia Institute of Technology to be able to listen to music, improvise, and play along with human musicians. Barnes joined Weinberg, his team, and Shimon onstage to play a few songs, and the performance was pretty surreal. His students are also working on making Shimon's creative abilities even stronger, currently working on figuring out what it would sound like if it was fed one style of music and asked to play another, such as feeding it Mozart and asking it to play jazz in the style of Thelonious Monk. But unlike IBM or many other researchers using AI systems for music, Weinberg's team is building working robots that can play real acoustic instruments, rather than programs that output beeps from a speaker.