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.

Seafood company Sanford has developed artificial intelligence to provide detailed information about its mussels.

TensorFlow Lite is the open-source deep learning framework for on-device inference.

One of the most salient features of our culture is that there is so much bullshit." These are the opening words of the short book On Bullshit, written by the philosopher Harry Frankfurt. Fifteen years after the publication of this surprise bestseller, the rapid progress of research on artificial intelligence is forcing us to reconsider our conception of bullshit as a hallmark of human speech, with troubling implications. What do philosophical reflections on bullshit have to do with algorithms? As it turns out, quite a lot. In May this year the company OpenAI, co-founded by Elon Musk in 2015, introduced a new language model called GPT-3 (for "Generative Pre-trained Transformer 3"). It took the tech world by storm. On the surface, GPT-3 is like a supercharged version of the autocomplete feature on your smartphone; it can generate coherent text based on an initial input. But GPT-3's text-generating abilities go far beyond anything your phone is capable of.

Benjamin Tee has long been captivated by a scene in "Star Wars: The Empire Strikes Back" where the surgical droid 2-1B replaces Luke Skywalker's hand after Darth Vader slices it off with a lightsaber in a battle on Cloud City. A fully autonomous robot surgeon is the Holy Grail--and many years off, says Dr. Tee, assistant professor of materials science and engineering at the National University of Singapore. He and other researchers are developing devices that can perform surgical tasks with minimal human oversight.

Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN), and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. Focus is primarily upon the application of deep learning to problems, with some introduction to mathematical foundations. Readers will use the Python programming language to implement deep learning using Google TensorFlow and Keras. It is not necessary to know Python prior to this book; however, familiarity with at least one programming language is assumed.

Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what constitutes the "music mainstream" strongly varies between countries. To complement and extend these results, the article at hand delivers the following major contributions: First, using state-of-the-art unsupervised learning techniques, we identify and thoroughly investigate (1) country profiles of music preferences on the fine-grained level of music tracks (in contrast to earlier work that relied on music preferences on the artist level) and (2) country archetypes that subsume countries sharing similar patterns of listening preferences. Second, we formulate four user models that leverage the user's country information on music preferences. Among others, we propose a user modeling approach to describe a music listener as a vector of similarities over the identified country clusters or archetypes. Third, we propose a context-aware music recommendation system that leverages implicit user feedback, where context is defined via the four user models. More precisely, it is a multi-layer generative model based on a variational autoencoder, in which contextual features can influence recommendations through a gating mechanism. Fourth, we thoroughly evaluate the proposed recommendation system and user models on a real-world corpus of more than one billion listening records of users around the world (out of which we use 369 million in our experiments) and show its merits vis-a-vis state-of-the-art algorithms that do not exploit this type of context information.

Stormzy has filmed the music video for Rainfall, the forthcoming single from his No 1 album Heavy is the Head, entirely inside a video game. The award-winning grime artist and social activist will also star as a future version of himself in a mission in the game, Watch Dogs: Legion, which is released on 29 October. Watch Dogs: Legion invites players to join the hacker resistance in a futuristic post-Brexit London under the thumb of an oppressive surveillance regime and its private military. Any of the thousands of different Londoners wandering the virtual streets can be recruited to the cause, and the player can control any one of them. The game, which is being developed by Ubisoft in Toronto and comes out next month, recreates various London locations from Trafalgar Square to Tower Hamlets and Camden.

Get local stories sent straight to your inbox as news breaks. The University of Oklahoma has received a $20 million grant to research artificial intelligence, which is being called a historic milestone in environmental science. "Let me give an AI definition, because you've probably only seen it in the movies portrayed as the scary robot that comes in and kills everybody. That's not what AI is," OU professor Amy McGovern said. "So, we'll be creating AI methods that will help improve prediction and understanding of tornadoes and hail and wind."

An Israeli company has developed new artificial-intelligence technology … The company's deep–learning technology initially was developed for the …