If you have a piece of equipment it and operate it, it will eventually fail. So you note down the failure time (operating hours) and replace it.After some time (especially if you have the identical equipment several times) you collect a collection of failure times. The usual approach is to use Minitab or R or whatever software you fancy and fit a model to the data (Exponential, Weibull, Gamma, etc.). So ideally you find a model which fits rather nice and then for the future you can describe the behaviour of your equipment with just one or two parameters. This is often displayed in form of a Cumulative Failure Probability plot.

A future chart-topping song may soon come from an algorithm. Sony Computer Science Laboratory (CSL) in Paris is developing a system of algorithms which can create songs that cater to the user's taste, based on styles adapted from existing music. The starting point of the song creation is a database of sheet music of more than 13,000 existing songs, from which the user can choose any number of titles with a sound or feel they would like the new song to incorporate. The algorithm analyses the songs' characteristics, and statistical properties related to rhythm, pitch and harmony. It will learn, for instance, which notes "go well" with a given chord, what chord is probable after a given chord, or which notes usually follow after a given note.

Dirk Gently's Holistic Detective Agency has all the makings of a new cult favorite: It's crammed with weird ideas, gore, crazy set pieces and a few charming moments. But you probably won't be able to enjoy it unless you stop thinking of it as a Douglas Adams adaptation. Yes, the BBC America show premiering tonight is based on a book duology by Adams, who also created the Hitchhiker's Guide to the Galaxy series. But other than the basic concept--a "holistic detective" named Dirk who breezes around getting into weird situations and then ties all the threads together with a mixture of luck and intuition--this TV show has little in common with Adams' work. The tone, in particular, is miles away from Adams' absurd wit.

This is my first post on this subreddit. I am interested in what the reddit community thinks of my thesis topic which utilizes machine learning to solve a classification problem. I am investigating the development of a software system for a self-sorting smart bin that can identify and sort plastics, metals, glass, and landfill. One of the biggest problems to crack is the identification and classification of items input into the bin. I have yet to select a machine learning algorithm to solve this classification problem but'adaptive interactive modelling systems' looks very promising.

This is my preliminary understanding of the paper after reading it a few times. Please correct me if I'm wrong. At each "timestep" of the RNN, they process the RNN an extra S times, with an augmented weight matrix. The augmented weight matrix consists of the sum of many helper terms made up of the hidden states from previous timesteps (the outer product h \dot h.T). The proportional coefficient for these outer products will ensure that these helper terms exponentially vanish to zero. Using the outer product of previous states to enforce the weight matrix during inference, is sort of like making the weight matrix "learn" during inference in a Hebbian-learning way, like in a Hopfield network.

Videogame acting sounds like the cushiest gig ever. Go into the studio for a few hours, recite a few lines of dialog, and cash the checks handed out by an industry that makes billions each year. But according to the union that represents them, the actors who bring you blockbuster games like Call of Duty and Grand Theft Auto V are underpaid and work in risky conditions. And so the 160,000 or members of the Screen Actor's Guild-American Federation of Television and Radio Artists went out on strike on Friday. The Guild has spent months negotiating a contract with 11 major publishers, and will not do any voice acting, motion-capture work, or anything else until their contract demands are met.

Imagine this fairly typical scene of modern life. You are half-heartedly watching a recommended show on Netflix while casually checking sports recaps on your phone when you receive a potential fraud alert from your bank because, while making your routine Amazon purchases, you were tempted to treat yourself to a lavish suggested item. This is hardly the kind of scene that makes for a gripping sci-fi movie. However, in this moment, every aspect of your life is positively bathed in artificial intelligence. Thanks to Hollywood, the phrase "artificial intelligence" conjures visions of a full-blown Skynet takeover, or at least a wisecracking robot sidekick.

The best part of "Radio Imagination: Artists in the Archive of Octavia E. Butler" is the view it provides into Butler's archive itself. Butler, who died in 2006, was a bestselling Pasadena novelist and the only science fiction writer to win a MacArthur fellowship. She was also African American, and her novels reworked the sci-fi genre with far-reaching insights on race, sex and gender. The exhibition at the Armory Center for the Arts in Pasadena features works by eight artists who were granted access to Butler's archives at the Huntington Library in San Marino. Their responses take a variety of forms, including sound and video as well as photography, drawing and installation.

In May, Google research scientist Douglas Eck left his Silicon Valley office to spend a few days at Moogfest, a gathering for music, art, and technology enthusiasts deep in North Carolina's Smoky Mountains. Eck told the festival's music-savvy attendees about his team's new ideas about how to teach computers to help musicians write music--generate harmonies, create transitions in a song, and elaborate on a recurring theme. Someday, the machine could learn to write a song all on its own. Eck hadn't come to the festival--which was inspired by the legendary creator of the Moog synthesizer and peopled with musicians and electronic music nerds--simply to introduce his team's challenging project. To "learn" how to create art and music, he and his colleagues need users to feed the machines tons of data, using MIDI, a format more often associated with dinky video game sounds than with complex machine learning.

One week a month, Watch This offers staff recommendations inspired by a new show coming out that week. This week: The return of Black Mirror has us thinking about TV's other visions of ominous futures. Not long after C-3PO and R2-D2's scene-stealing turns as the Bert and Ernie of the Star Wars universe, wise-cracking artificial intelligence became a standard feature of science-fiction film and television. Short Circuit had El DeBarge-loving military'bot Johnny Five, Knight Rider introduced droll Trans Am KITT, and who can forget Rutger Hauer as that barrel of laughs who saw attack ships on fire off the shoulder of Orion, Roy Batty? But they all paled in comparison to Max Headroom (Matt Frewer), a chattering combination of prosthetics, post-production monkeying, and screen-saver-worthy animations. In the mid-to-late '80s, the glitchy talking head in the Klaus Nomi threads became ubiquitous through sheer versatility: He was a VJ, the face of New Coke, and, for 14 episodes broadcast on ABC between 1987 and 1988, the namesake character of a cyberpunk thriller set in a dystopian future where it's illegal to turn off a TV.