Perhaps the greatest outrage in modern robotics is the continued non-existence of the robot housekeeper. Is it really so much to ask for a robot that sweeps and mops and brings you pills on platters, like Rosie from The Jetsons? Actually, it kind of is a lot to ask: A robot that can do even the simplest of chores (save for vacuuming), like setting a table, is a huge challenge because such tasks require both dexterity and planning. But the scientists at the MIT Computer Science and Artificial Intelligence Laboratory are working toward a world where robots make our coffee and set our tables. And that research is happening inside a simulation. Because if we want the machines to run our homes instead of leveling them, we have to train them up right.

They don't enslave us, but they do decide what news stories you see, Amazon products you're offered, Netflix shows to watch next. Most mornings, I ask Google, "What's the fastest route to work?" Based on traffic, it sends me along one of two highways. Both are six lanes of hot concrete, billboards, McDonalds and brake lights. Google knows which is faster. There's a third highway to work.

Music generation research has grown in popularity over the past decade, thanks to the deep learning revolution that has redefined the landscape of artificial intelligence. In this paper, we propose a novel approach to music generation inspired by musical segment concatenation methods and hash learning algorithms. Given a segment of music, we use a deep recurrent neural network and ranking-based hash learning to assign a forward hash code to the segment to retrieve candidate segments for continuation with matching backward hash codes. The proposed method is thus called Deep Segment Hash Learning (DSHL). To the best of our knowledge, DSHL is the first end-to-end segment hash learning method for music generation, and the first to use pair-wise training with segments of music. We demonstrate that this method is capable of generating music which is both original and enjoyable, and that DSHL offers a promising new direction for music generation research.

The possibilities clog our news feeds, create interesting conversations, and give tech leaders inspiration to explore solutions. What will this mean for us as humans? Could this impact all of society? With all the questions being asked, only one thing is absolutely clear. We're about to enter one of the biggest transformations our society has witnessed in the last century - if not millennium.

Apple has released the first major update for its HomePod smart speaker - and has its sights firmly set on Amazon and Google. The new iOS 11.4 update released today adds multi room capabilities to the Siri smart speaker, allowing users to play music in other rooms, in in every room at once. It comes as Apple is believed to be putting the finishing update to a major update to its Siri AI software. The free update also adds new features such as the ability to store iMessages in the cloud. The new iOS 11.4 update released today adds multi room capabilities to the Siri smart speaker, allowing users to play music in other rooms, in in every room at once.

The little league team you coach just won the big game, and you ask them if they want to go out for pizza or for burgers. Each kid starts screaming their preference, and you go with whatever was the loudest. This is basically how a neural net works but on multiple levels. The top-level nodes get some input, each detects a certain property and screams when it sees it...the more intense the property, the louder they scream. Now you have a bunch of nodes screaming "it's dark!", "it's has red!", "it's roundish!" as various volumes.

Every week, IndieWire asks a select handful of film critics two questions and publishes the results on Monday. Last weekend saw the release of "Solo: A Star Wars Story," a movie that at least one critic maintains is salvaged by the introduction of a brilliant new droid. On that note, what -- or who? -- is the greatest of all movie robots? The only reasonable answer is Robby the Robot from "Forbidden Planet." A trailblazer for android-kind, he was the first instance of a bag of bolts that actually had personality, charm, a sense of fully-formed character.

The new Apple HomePod is displayed at an Apple Store on Feb. 9, 2018 in San Francisco. NEW YORK -- "Hey Siri, play jazz in the living room, hip-hop in the kitchen." Apple's HomePod speaker is getting a little bit smarter today, through a software update that arrives via iOS 11. Smarter, that is, when it comes to playing music. For starters, you now have the ability to "pair" two HomePods for a full stereo effect, with the left and right speakers playing the left and right audio channels accordingly, and independently adjusting to where you place them.

The most interesting character in Solo is a robot. L3-37, voiced by Phoebe Waller-Bridge (Fleabag), is a free-thinking, loud-mouthed Droid who introduces an entirely new concept into the Star Wars universe: robot rights. From the beginning, Droids like R2-D2 and C-3PO were presented as beings with thoughts and personalities of their own. But they also served masters and faced blatant anti-Droid sentiment, like the barkeep who refused to serve their kind in Episode IV. And they were forced to obey humans through restraining bolts, which limited their cognitive functions.

Machine learning (ML) is profoundly significant and alongside it, is the user interface (UI), which denotes wearable parts of a gadget, display screens, texts, graphics, physical look, or appearance. However, as developers begin to take on more complex design tasks to match postmodern technologies such as artificial intelligence, the bone of contention is whether people will unquestionably accept output signals from machines as true reflections of human reasoning. It is to say, machine learning remains a rather complex and opaque process for the layman who doesn't understand how UX superimposes UI. In this post, discover why UX design matters and how it is changing ML in end product designs and products. How are app developers, programmers, webmasters, decision makers, and businesspersons adapting to the need for UX designers?