Transformers have matched or exceeded earlier architectures in language modeling and image classification. New work shows they can achieve state-of-the-art results in some reinforcement learning tasks as well.

An Android app offers speech recognition model for speech impaired by cerebral palsy, Down syndrome, Parkinson’s disease, stroke, or traumatic brain injury.

Recommendations from the National Security Commission on AI were enshrined in over 190 laws in 2021.

Isomorphic aims to build its business on AlphaFold 2, an ensemble of neural networks that finds the shapes of protein molecules.

Google designed its own AI chip for its new smartphone — a snub to Qualcomm, the dominant chip vendor in Android phones. What’s new: Google debuted the Tensor chip last week

Tech companies generally try to be (or to appear to be) socially responsible. Would some rather let AI’s negative impacts slide?

Google will upgrade its search engine with a new model that tracks the relationships between words, images, and, in time, videos — the first fruit of its latest research into multimodal machine learning and multilingual language modeling.

The transformer architecture is notoriously inefficient when processing long sequences — a problem in processing images, which are essentially long sequences of pixels. One way around this is to break up input images and process the pieces

Models trained using supervised learning struggle to classify inputs that differ substantially from most of their training data. A new method helps them recognize such outliers.

Machine learning researchers tend to trust international organizations, distrust military forces, and disagree on how much disclosure is necessary when describing new models, a new study found.

The paper that introduced the transformer famously declared, “Attention is all you need.” To the contrary, new work shows you may not need transformer-style attention at all.What’s new: Hanxiao Liu and colleagues at Google

Privacy advocates want deep learning systems to forget what they’ve learned. What’s new: Researchers are seeking ways to remove the influence of particular training examples, such as an individual’s personal information, from a trained model without affecting its performance, Wired reported.

Apple, which has made a point of its commitment to user privacy, announced that it will scan iPhones for evidence of child abuse. The tech giant will include a machine learning model on the device.

Compression methods like parameter pruning and quantization can shrink neural networks for use in devices like smartphones with little impact on accuracy — but they also exacerbate a network’s bias.

DeepMind opened access to AlphaFold, a model that finds the shapes of proteins, and to its output so far — a potential cornucopia for biomedical research. The research lab, a division of Google’s parent company Alphabet, made AlphaFold freely available.