Sep 23, 2020

AI researchers keep coming up with impressive innovations: transformer-based language models, self-supervised learning, deep reinforcement learning, small data. All of these developments hold great promise.

A major corporate acquisition could reshape the hardware that makes AI tick.What’s new: U.S. processor giant Nvidia, the world’s leading vendor of the graphics processing units (GPUs) that perform calculations for deep learning, struck a deal to purchase UK chip designer Arm for $40 billion.

As transformer networks move to the fore in applications from language to vision, the time it takes them to crunch longer sequences becomes a more pressing issue. A new method lightens the computational load using sparse attention.

Facing a tsunami of user-generated disinformation, YouTube is scrambling to stop its recommendation algorithm from promoting videos that spread potentially dangerous falsehoods.

An ambitious company is using deep learning to extract and find associations from all the information on the internet — and it isn’t Google. Diffbot built a system that reads web code, parses text, classifies images, and assembles them into what it says is the world’s largest knowledge graph.

New research teaches robots to anticipate what’s coming rather than focusing on what’s right in front of them. Researchers developed Occupancy Anticipation (OA), a navigation system that predicts unseen obstacles in addition to observing those in its field of view.

AI researchers keep coming up with impressive innovations: transformer-based language models, self-supervised learning, deep reinforcement learning, small data. All of these developments hold great promise.