As recommender systems are being designed and deployed for an increasing number of socially-consequential applications, it has become important to consider what properties of fairness these systems exhibit. There has been considerable research on recommendation fairness. However, we argue that the previous literature has been based on simple, uniform and often uni-dimensional notions of fairness assumptions that do not recognize the real-world complexities of fairness-aware applications. In this paper, we explicitly represent the design decisions that enter into the trade-off between accuracy and fairness across multiply-defined and intersecting protected groups, supporting multiple fairness metrics. The framework also allows the recommender to adjust its performance based on the historical view of recommendations that have been delivered over a time horizon, dynamically rebalancing between fairness concerns. Within this framework, we formulate lottery-based mechanisms for choosing between fairness concerns, and demonstrate their performance in two recommendation domains.

Building an open-domain socialbot that talks to real people is challenging - such a system must meet multiple user expectations such as broad world knowledge, conversational style, and emotional connection. Our socialbot engages users on their terms - prioritizing their interests, feelings and autonomy. As a result, our socialbot provides a responsive, personalized user experience, capable of talking knowledgeably about a wide variety of topics, as well as chatting empathetically about ordinary life. Neural generation plays a key role in achieving these goals, providing the backbone for our conversational and emotional tone. At the end of the competition, Chirpy Cardinal progressed to the finals with an average rating of 3.6/5.0,

Pose Detection in the Browser: PoseNet Model: Once upon a time, you needed a device like the Kinect to track the parts of your body. Using TensorFlow.JS and PoseNet, we can now estimate your pose using a web camera. Web apps built with Magenta.js: During graduate school, I enjoyed doing research in generative art and music using neural networks and an evolutionary strategy called NEAT. So, I especially enjoy seeing how TensorFlow has been applied to music domains.

Lo-Fi Player, a new project out of Google Magenta, wants to help people play around with music creation -- no experience necessary. Lo-Fi Player is a pixelated, 2D virtual room that runs in a web browser. It lets you mix lo-fi hip hop tracks by clicking on different objects in the room, and it uses machine learning to give the tracks a little finesse. Once you have clicked around on everything from the guitars to the window, plants and desk and generated sounds you like, you can share your Lo-Fi Player room with friends. If you click the radio or TV, you'll trigger machine-learning models that produce a few new melodies, and you can click the green ceiling lamp to stop and start the music.

Fox News Flash top entertainment and celebrity headlines are here. Check out what's clicking today in entertainment. Rage Against the Machine is one of the most politically outspoken bands currently making music today and singer Tom Morello loves to toe the line. In a recent interview with Yahoo, he recalled the moment his band stormed the New York Stock Exchange in Manhattan while shooting their 1999 music video for "Sleep Now in the Fire," directed by Michael Moore. "The band shut down the New York Stock Exchange, which was the first time that that happened in its 200-year history, in the middle of a Tuesday afternoon," Morello, 56, recalled to the outlet.

The upcoming US presidential election seems set to be something of a mess--to put it lightly. Covid-19 will likely deter millions from voting in person, and mail-in voting isn't shaping up to be much more promising. This all comes at a time when political tensions are running higher than they have in decades, issues that shouldn't be political (like mask-wearing) have become highly politicized, and Americans are dramatically divided along party lines. So the last thing we need right now is yet another wrench in the spokes of democracy, in the form of disinformation; we all saw how that played out in 2016, and it wasn't pretty. For the record, disinformation purposely misleads people, while misinformation is simply inaccurate, but without malicious intent.

It goes by many names, this thing that we yearn for and that rules us: opium, money, power. William S. Burroughs, the American cult author, likened them all – in his 1959 novel "Naked Lunch" – to the flesh of a gargantuan centipede that lurks in the depths and has an irresistible taste, and whose addicts gorge on it until they lose consciousness. To get a piece of it one must undergo endless ordeals, wandering about in kitchens, sleeping cubicles, wobbly balconies and basements. That's also the sort of route one must follow in order to experience the products of an algorithm that was unveiled in May in Silicon Valley. Generative Pre-trained Transformer 3, aka GPT-3, is a "language model": a machine learning system that's capable of automatically and dynamically generating texts in human-like language. Since its emergence, thousands have wished to touch it, use it, breathe in something of the words it spews out. But only a few have been vouchsafed that privilege.

Christie's made the headlines in 2018 when it became the first auction house to sell a painting created by AI. The painting, named Portrait of Edmond de Belamy, ended up selling for a cool $432,500, but more importantly, it demonstrated how intelligent machines are now perfectly capable of creating artwork. It was only a matter of time, I suppose. Thanks to AI, machines have been able to learn more and more human functions, including the ability to "see" (think facial recognition technology), speak and write (chatbots being a prime example). Learning to create is a logical step on from mastering the basic human abilities.

It's a powerful enabling technology for a new generation of use cases that will leverage edge computing to make IoT more effective and efficient. In many ways, the narrative of 5G is the interaction between two inexorable forces: the rise in highly reliable, high-bandwidth communications, and the rapid spread of available computing power throughout the network. End-point devices that connect to the network are also getting smarter and more powerful. The increasingly dynamic and powerful computational environment that's taking shape as telcos begin to redesign their networks for 5G will accelerate the uptake of IoT applications and services throughout industry. We expect that 5G will enable new use cases in remote monitoring and visual inspection, autonomous operations in large-scale remote environments such as mines, connected vehicles and more.

"We wanted flying cars, instead we got 140 characters" -Peter Thiel The closing quarter of the twentieth century was peak tech innovation in the United States. AT&T's Bell Labs invented the information age with the transistor and data networking, and many transformative technologies tangential to its core business: from solar cells to the Unix operating system to lasers.1 Xerox's Palo Alto Research Center (PARC) brought about human-computer interaction with the initial computer mouse, as well as laser printing and Ethernet networking.2 In the 80's Pixar was born, creating the first ever computer-animated sequence in a feature film with novel computer-generated imagery (CGI).3,4 At the same time Gates and Allen were hacking at something special that soon revolutionized computing, as were Wozniak and Jobs.5,6 Amidst the heyday of invention in the world of bits, the "space race" brought about massive innovation and accomplishments in the world of atoms: government competition between the US and Russia put humans on the moon for the first time.