AI technology is improving at an amazing rate. However, video is still a significant challenge. Wired reported on a development that may improve things, whilst also using less processing power.

A group from MIT and IBM developed an algorithm capable of accurately recognizing actions in videos while consuming a small fraction of the processing power previously required, potentially changing the economics of applying AI to large amounts of video. The method adapts an AI approach used to process still images to give it a crude concept of passing time. The work is a step towards having AI recognize what’s happening in video, perhaps helping to tame the vast amounts now being generated. On YouTube alone, over 500 hours of video were uploaded every minute during May 2019. Companies would like to use AI to automatically generate detailed descriptions of videos, letting users discover clips that haven’t been annotated. And, of course, they would love to sell ads based on what’s happening in a video.

Apple’s much speculated upon self-driving car might have a radar system hidden within the bodywork. That’s according to a patent granted Tuesday and uncovered by AppleInsider.

In Apple’s design, it suggests the use of antennas to transmit a radar beam towards a portion of a field of view, along with a vertical antenna array to receive the bounced-back signal. The receive antenna array can consist of multiple antenna elements grouped into sub-arrays, with each sub-array used to receive scatter signals reflected back at it from a smaller subsection of the field of view. Circuitry is then used to combine the received scatter signals from the antenna array into a combined scatter signal, which is then digitized. A second horizontal receive array performs a similar job, again with sub-arrays and the same process. A signal processor is then used to process the scatter signals from both vertical and horizontal arrays, and to correlate the data from each to give effectively a 3D radar layout.