An onboard computer watching your every move might sound like something out of 2001: A Space Odyssey. But now, a futuristic superyacht plans to use AI to learn what you want before you even realise it. Just like HAL 9000 from Stanley Kubrick's sci-fi classic, the ship's computer will spy on its passengers to learn more about their desires. Designed by the Italian shipyard Rossinavi, the 43-metre-long Solsea will use that information to tailor itself to the needs of individual guests. Rossinavi says that this onboard AI has been designed to make travel more comfortable and maximise the yacht's eco-friendly potential.

In a 2018 Workforce Institute survey of 3,000 managers across eight industrialized nations, the majority of respondents described artificial intelligence as a valuable productivity tool. But respondents to that survey also expressed fears that AI would take their jobs. The Guardian recently reported that in the UK "more than 6 million workers fear being replaced by machines." AI's advantages can be cast in a dark light: Why would humans be needed when machines can do a better job? To allay such fears, employers must set AI up to succeed rather than to fail.

For years, the evolution of image sensors has been about packing in more pixels and slimming down their size to fit into smaller devices. Now, they're about to get smart. Today, Sony is unveiling the IMX500 and IMX501, two 12.3-megapixel sensors with onboard AI processing chips. They'll be able to handle "light" machine learning tasks -- like recognizing if a stray dog or cat enters your backyard -- on their own, without sending any video to the cloud or another system. Instead, they can deliver anonymous metadata pings to alert you about what they've seen.

Researchers are looking to employ onboard artificial intelligence systems to improve the control and sophistication of prosthetic hands, by using deep learning approaches that read and react to nerve signals transmitted through the arm. The practice of tracking the natural electric impulses sent by the brain to control individual muscles, known as electromyography, has been used to operate prosthetic limbs and hands before, as well as wheelchairs and other devices. But performance gaps remain when it comes to the fine motor control of fingers and hands. By running a neural network in real-time on a dedicated processing unit within the prosthetic, researchers at the University of Texas at Dallas (UT Dallas) hope to speed up responses for faster hand movements. In addition, the proposed system could be retrained based on the actions of the user to increase its accuracy.

By employing an artificial intelligence network typically used for image recognition, researchers at University of Texas at Dallas aim to skip labor-intensive processing steps while reacting to raw nerve signal data in real time.