Hironori Fukuoka of Fukuoka Weaving in Kyoto, Japan, is turning to AI and Sony Computer Science Laboratories to help keep the ancient Nishijinori kimono-weaving technique alive, using the technology as a collaborator.
Nishijinori's repetitive and geometric patterns are conducive to digital translations, and Fukuoka views AI as useful in identifying new motifs to define the angular lines of traditional patterns.
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Meta has developed a prototype wristband that uses electromyography to detect electrical signals from forearm muscles, enabling touch-free control of digital devices. These signals, generated by alpha motor neurons before physical movement occurs, allow the device to interpret user intent.
In particular, the device operates using surface electromyography, a non-invasive way to track the electrical activity of muscles. The wristband captures the signals externally and can move cursors, open apps, or even transcribe air-written text in real time.
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https://mashable.com/article/meta-research-device-wrist-control
Farms are moving toward full autonomy thanks to advances in AI, robotics, and digital tools. High costs and the lack of broadband Internet in rural areas, however, pose major obstacles.
Technologies being deployed on farms include autonomous tractors, robots and drones capable of picking fragile fruits, sensors that provide soil analysis, virtual fences to rein in livestock, and remote sensing and image analytics tools.
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Recently, the latest edited book I co-authored with colleagues from CYENS – Centre of Excellence and the University of Cyprus was published by Springer Series on Cultural Computing. The book is entitled ‘Interactive Media for Cultural Heritage’ and presents the full range of interactive media technologies and their applications in Digital Cultural Heritage. It offers a forum for interaction and collaboration among the interactive media and cultural heritage research communities.
The aim of this book is to provide a point of reference for the latest advancements in the different fields of interactive media applied in Digital Cultural Heritage research, ranging from visual data acquisition, classification, analysis and synthesis, 3D modelling and reconstruction, to new forms of interactive media presentation, visualization and immersive experience provision via extended reality, collaborative spaces, serious games and digital storytelling.
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LENS (Locational Encoding with Neuromorphic Systems) uses brain-inspired computing to set a new, low-energy benchmark for robotic place recognition. To run these neuromorphic systems, they designed specialised algorithms that learn more like humans do, processing information in the form of electrical spikes, like the signals used by real neurons.
In the study, researchers developed a system that was able to recognise locations along an 8 km journey but using only 180KB of storage, almost 300 times less than other systems. LENS combines a brain-like spiking neural network with a special camera that only reacts to movement and a low-power chip, all on one small robot.
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Automated surgery could be trialled on humans within a decade, after an AI-trained robot armed with tools to cut, clip and grab soft tissue successfully removed pig gall bladders without human help. The robot surgeons were schooled on video footage of human medics conducting operations using organs taken from dead pigs. Eight operations were conducted on pig organs with a 100% success rate by a team led by experts at Johns Hopkins University in Baltimore in the US. The technology allowing robots to handle complex soft tissues such as gallbladders, which release bile to aid digestion, is rooted in the same type of computerised neural networks that underpin widely used AI tools such as Chat GPT or Google Gemini.
The surgical robots were slightly slower than human doctors, but they were less jerky and plotted shorter trajectories between tasks. The robots were also able to repeatedly correct mistakes as they went along, asked for different tools and adapted to anatomical variation, according to a peer-reviewed paper published in the journal Science Robotics. In the Johns Hopkins trial, the robots took just over five minutes to carry out the operation, which required 17 steps including cutting the gallbladder away from its connection to the liver, applying six clips in a specific order and removing the organ. The robots on average corrected course without any human help six times in each operation.
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