AI Technology & Industry Review
Google AI has announced a new audiovisual speech enhancement feature in YouTube Stories (iOS) that enables creators to make better selfie videos by automatically enhancing their voices and reducing noise.
A team from Google, University of Cambridge, DeepMind, and Alan Turing Institute have proposed a new type of Transformer dubbed Performer, based on a Fast Attention Via positive Orthogonal Random features (FAVOR+) backbone mechanism.
Researchers introduced retrieval-augmented generation - a hybrid, end-to-end differentiable model that combines an information retrieval component with a seq2seq generator.
Google Brain recently introduced a new open-sourced TensorFlow package, TensorFlow Recommenders designed to simplify the process of building, evaluating, and serving sophisticated recommender models.
Facebook AI researchers have open-sourced the new wav2vec 2.0 algorithm for self-supervised language learning.
Top Data Scientists Honored for Advanced Research and Applied Data Science in the Field of Knowledge Discovery in Data and Data Mining
The trimmed-down pQRNN extension to Google AI’s projection attention neural network PRADO compares to BERT on text classification tasks for on-device use.
UIUC, Adobe Research and University of Oregon propose HDMatt, a Deep Learning-based image matting Cross-Patch Context module for high-resolution image inputs.
Augmented Temporal Contrast (ATC), a new unsupervised learning (UL) task for learning visual representations agnostic to rewards and without degrading the control policy.
A group of researchers from Google Research and the University of Oxford have introduced a novel technique that can “retiming” people’s movements in videos.
NumPy is the foundation upon which the scientific Python ecosystem is constructed.
From an augmented view of an image, the researchers trained the online network to predict the target network representation of the same image under a different augmented view.
Monster Mash, a novel AI-powered 3D modelling and animation tool, aims to make these arduous 3D animation processes a whole lot easier.
Facebook AI researchers and engineers just made live video content more accessible by enabling automatic closed captions for Facebook Live and Workplace Live.
Microsoft has released four additional DeepSpeed technologies to enable even faster training times, whether on supercomputers or a single GPU.
This research addresses a well-known phenomenon regarding large batch sizes during training and the generalization gap.
OpenAI researchers introduce GPT-f, an automated prover and proof assistant for the Metamath formalization language.
Novel attention condensers designed to enable the building of low-footprint, highly-efficient deep neural networks for on-device speech recognition on the edge.
Researchers introduce a test covering topics such as elementary mathematics, designed to measure language models’ multitask accuracy.
Researchers introduced a novel flow-based video completion algorithm that compares favourably with the state-of-the-art in the field.
This research proposes an efficient and cost-effective solution for multi-frame video interpolation.
The ReDNA Labs research team has devised a new lightweight approach called IGLOO which allows to deal with sequences up to 25,000 steps long.
Although OpenAI hasn’t yet officially announced the GPT-3 pricing scheme, Branwen’s sneak peek has piqued the interest of the NLP community.
DeepMind unveiled a partnership with Google Maps that has leveraged advanced GNNs to improve ETA accuracy.
“Wav2Lip,” a novel lip-synchronization model that outperforms current approaches by a large margin in both quantitative metrics and human evaluations.
Facebook AI this week released a new high-speed library called Opacus.
AMBERT (A Multigrained BERT) leverages both fine-grained and coarse-grained tokenizations to achieve SOTA performance on English and Chinese language tasks.
The paper outlines a predictive model we’ve developed that has the potential to help significantly reduce wasteful healthcare spending.
Researchers propose reducing the workloads of urban planners by introducing deep learning systems to handle some of their responsibilities.
Intel Labs researchers have proposed a novel method for building a robot called “OpenBot” on just a US$50 budget.
Researchers proposed a new model that is designed to spot deepfakes by looking at subtle visual artifacts.
The 16th European Conference on Computer Vision (ECCV) kicked off on Sunday as a fully online conference. In the Conference Opening Session this morning, the ECCV organizing committee announced the conference’s paper submission stats and Best Paper selections.
Researchers from The Chinese University of Hong Kong, Facebook Reality Labs, and Facebook AI Research have unveiled a state-of-the-art monocular 3D hand motion capture method, FrankMocap, which can estimate both 3D hand and body motions from in-the-wild monocular inputs with faster speed and better accuracy than previous approaches.
Researchers argue that “attention mechanism is the update rule of a modern Hopfield network with continuous states.”
The proposed algorithm is approximately 180 times faster than an automated random search of the parameter space.
Researchers from Stanford University, UC Berkeley and CMU review neuromechanical simulations and DRL, with a focus on modelling the control of human locomotion.
University of Zurich and ETH Zurich’s deep reinforcement learning agents have achieved superhuman performance in the time trials of popular racing simulator game Gran Turismo Sport.
Elon Musk tweeted that Tesla is recruiting AI or chip talents for the company’s neural network training supercomputer project “Dojo.”
DeepMind and McGill University researchers believe the problem could be solved through a strategic “divide-and-conquer” approach.
Bengio and researchers from Université de Montréal and the École Normale Supérieure in Paris have introduced a new curriculum learning algorithm based on the notion of mastering rate.