Sam Esmail is apparently taking a very unusual strategy for his next big project beyond Mr. Robot: he's tackling one of the earliest sci-fi epics. Hollywood Reporter sources say that Esmail is creating a miniseries based around Metropolis, Fritz Lang's classic 1927 film about a dystopic society. The show is still very early (Esmail may need to finish Mr. Robot before devoting his full attention), but partner Universal Cable Productions is apparently willing to give it a budget fitting Metropolis' pioneering visuals. Reportedly, the company would be willing to spend a whopping $10 million per episode, and is willing to shop it around to numerous providers, including streaming services. Metropolis would be an appropriate fit for Esmail, though.

This year's news about what artificial intelligence can do in the arts has been both exciting and scary. Neural networks have learned to paint like masters and compose sophisticated music. Those of us in creative endeavors might be as endangered by technological advances as blue-collar workers are often said to be--though we are protected by certain limitations that technology is never likely to overcome. Last summer, a team of Russian developers released Prisma, a mobile app based on the work of some German artificial intelligence researchers. The neural network behind it could redraw an image using techniques it had learned from studying the oeuvre of a number of painters, including Vincent Van Gogh and Edvard Munch. The end product was impressive: Prisma could reproduce brushstrokes and palettes, using only a photo for guidance, almost the way a human painter could have.

'Passengers' stars chat about future space travel, tech Sitting down with Chris Pratt, Jennifer Lawrence and Michael Sheen to talk about space travel and the tech in the film. The ramifications of waking people up from cryogenic stasis sooner than planned. "Passengers" has some lofty, fascinating concepts, but unfortunately, it never really connects with the core of any of them. It's a place he describes as relatively colonial; he's hoping for the chance to start over and become a useful member of society again by building things. Jim (Chris Pratt) and Aurora (Jennifer Lawrence): Now that I've woken you up, will you love me?

In 2005, Atlanta-based voiceover artist Susan Bennett recorded hundreds of hours of audio for a text-to-speech company. Six years later, on 4 October 2011, she quickly learned that those recordings had been licensed by Apple for the iPhone 4S's built-in personal assistant, Siri. Overnight, Susan's voice became globally recognised, whether she liked it or not. In this week's episode of Chips with Everything, Matt Shore speaks to Susan about her experiences of being thrust into the world of Siri and how her life has changed since that fateful day. Follow us on Twitter: @mattshore and @guardianaudio Tell us how technology affects you.

And how can they each illuminate the nature of mind and self? These were some of the questions on Siri Hustvedt's mind as she began her new book of essays, A Woman Looking At Men Looking At Women. Hustvedt herself has an omnivorous professional history that blends the two worlds in unconventional ways. She is an essayist, poet, and novelist (best known for her recent novel The Blazing World), an English literature PhD by training, and lectures on psychiatry at the Weill Medical School of Cornell. In her essays, Hustvedt uses this eclectic expertise to jump freely from the arts to empirical science and back again.

In science fiction, spaceships are often about more than transportation. The Millennium Falcon is as integral to the plot of Star Wars as the characters it shuttles from planet to planet. In Passengers, a new movie starring Jennifer Lawrence and Chris Pratt, the Avalon plays a similarly central role. The film is set entirely aboard the starship, which carries 5,000 hibernating passengers on a 120-year journey to a distant utopian planet called Homestead 2. Thirty years into the journey, two of those travelers, Lawrence and Pratt, accidentally wake up and are left to explore the massive spaceship on their own. That means the Avalon is far more than an elaborate backdrop.

Virtually everywhere you look, Bay Area tech businesses are running into walls. Smartphones were revolutionary and lucrative, but the U.S. market is saturated, and Apple's iPhone sales have fallen for three quarters. The "app economy" has matured, with more people using existing apps than downloading new ones. And Facebook, which has filled users' news feeds with so many ads it can barely add more, is predicting its revenue growth will slump next year. Silicon Valley needs its next big thing, a focus for the concentrated brain power and innovation infrastructure that have made this region the world leader in transformative technology.

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?

Pat Bagley is easily my favorite political cartoonist, period. For the politically aware in Utah, he is almost legendary, enjoying superstar status. I've been aware of him since I was a kid, and I always loved his cartoons. Not only does his artistic style appeal to me, he has a way of illustrating a situation in politics that explains it more clearly than a thousand words. His cartoons are humorous, though darkly so. And with every one, you can't help but feel he's had the last word.

Artificial Intelligence and Machine Learning in Big Data and IoT: The Market for Data Capture … NEW YORK, Dec. 16, 2016 /PRNewswire/ Overview:More than 50% of enterprise IT organizations are experimenting with Artificial Intelligence (AI) in various forms such as Machine Learning, Deep Learning, Computer Vision, Image Recognition, Voice Recognition, Artificial Neural Networks, and more. AI is not a single technology but a convergence of various technologies, statistical models, algorithms, and approaches. Machine Learning is a sub-field of computer science that evolved from the study of pattern recognition and computational learning theory in AI.Every large corporation collects and maintains a huge amount of human-oriented data associated with its customers including their preferences, purchases, habits, and other personal information. As the Internet of Things (IoT) progresses, there will an increasingly large amount of unstructured machine data.