A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce a structured prediction over variable-size input structures, or a scalar prediction on it, by traversing a given structure in topological order.

Hey! I've been working for the last couple months on a set of tools for machine learning research for autonomous vehicles. I've tested them out with a couple early users and they've really enjoyed the tools so far. I wanted to share them with you here to see what you think. One of the biggest issues that I found with existing tools is that you are forced to decide on your visualizations before training. However, the most interesting results are often the unexpected ones. Setting up a visualization for an unexpected situation is impossible!

Previously I wrote about the Cyberworld that's coming – the world of extended reality, or XR, enabled by a confluence of maturing foundational technologies, with AI a central part – computer vision and graphics, 3D reconstruction, natural language processing and more. It goes without saying that this seamless overlay of digital and real worlds will be populated by digital humans and avatars, both realistic and stylistic, driven by real humans and/or artificial intelligence. Here I am going to dive deeper into one of these foundational technologies: the creation and animation of digital humans (mainly faces). The good news first – it won't take us another decade to get there. When I started the Disney Research Laboratory back in 2008, I launched a long-term research vision to find the Holy Grail of special effects in film; i.e. to create and animate digital human faces indistinguishable from reality.

Jay-Z's company Roc Nation have filed takedown notices against "deepfake" videos that use artificial intelligence to make him rap Billy Joel's We Didn't Start the Fire and Hamlet's "To be or not to be" soliloquy. The two aforementioned videos have been removed, though others remain, including one of the rapper taking on the Book of Genesis. Vocal Synthesis said – via a deepfake video using the ersatz voices of Barack Obama and Donald Trump – that they had "no malicious purpose" and were "disappointed that Jay-Z and Roc Nation have decided to bully a small YouTuber in this way". The Guardian has contacted Roc Nation for comment. Deepfake videos have already caused great controversy in political and celebrity circles, with California outlawing them in 2018, and Facebook banning them in January.

Peloton has added a new groups feature to allow people to exercise together despite being in lockdown. The company – which makes internet-enabled spinning bikes and treadmills, as well as running an app of online exercise classes – has seen a huge surge in users in recent months as people have looked for a way to work out at home. Now it has added a new groups feature, officially called "tags", allowing people to track their exercise alongside other people in communities they have formed off the bike. With the new feature, users are able to add hashtags to their profile, which designate certain groups: a certain set of people all from the same workplace, for instance, or one of the many "tribes" of users that have formed on other platforms such as Facebook and Reddit. If a user has a given hashtag in their profile, they will be able to see what classes other members have taken and when they are working out.

We introduce Jukebox, a model that generates music with singing in the raw audio domain. We tackle the long context of raw audio using a multi-scale VQ-VAE to compress it to discrete codes, and modeling those using autoregressive Transformers. We show that the combined model at scale can generate high-fidelity and diverse songs with coherence up to multiple minutes. We can condition on artist and genre to steer the musical and vocal style, and on unaligned lyrics to make the singing more controllable. We are releasing thousands of non cherry-picked samples at https://jukebox.openai.com, along with model weights and code at https://github.com/openai/jukebox

Abstract: Large-scale pre-trained language models such as BERT have brought significant improvements to NLP applications. However, they are also notorious for being slow in inference, which makes them difficult to deploy in real-time applications. We propose a simple but effective method, DeeBERT, to accelerate BERT inference. Our approach allows samples to exit earlier without passing through the entire model. Experiments show that DeeBERT is able to save up to 40% inference time with minimal degradation in model quality.

You normally need to listen to a song or read its lyrics to tell if it's using explicit language, but Deezer thinks AI might be up to the job before long. The streaming music service is researching a machine learning technique that would detect explicit lyrics solely through audio. Instead of merely training an AI to recognize colorful words with a giant set of annotated samples, like you often see with machine learning, Deezer extracts the vocals and looks for instances where it's likely that a word matches entries in a dictionary of foul expressions. From there, a simple binary classifier decides if a given word is naughty. It's an "explainable" system that can show why the AI came to a decision, the company said.

ASTARTE project to create a strong common operating picture using artificial intelligence (AI) algorithms.