All posts by Artificial Intelligence News -- ScienceDaily

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Scientists create AI that ‘watches’ videos by mimicking the brain

Imagine an artificial intelligence (AI) model that can watch and understand moving images with the subtlety of a human brain. Now, scientists have made this a reality by creating MovieNet: an innovative AI that processes videos much like how our brains interpret real-life scenes as they unfold over time.

Black-box forgetting: A new method for tailoring large AI models

Pretrained large-scale AI models need to 'forget' specific information for privacy and computational efficiency, but no methods exist for doing so in black-box vision-language models, where internal details are inaccessible. Now, researchers addressed this issue through a strategy based on latent context sharing, successfully getting an image classifier to forget multiple classes it was trained on. Their findings could expand the use cases of large-scale AI models while safeguarding end users' privacy.

Smallest walking robot makes microscale measurements

Researchers have created the smallest walking robot yet. Its mission: to be tiny enough to interact with waves of visible light and still move independently, so that it can maneuver to specific locations -- in a tissue sample, for instance -- to take images and measure forces at the scale of some of the body's smallest structures.

Inside the ‘swat team’ — how insects react to virtual reality gaming

Humans get a real buzz from the virtual world of gaming and augmented reality but now scientists have trialled the use of these new-age technologies on small animals, to test the reactions of tiny hoverflies and even crabs. In a bid to comprehend the aerodynamic powers of flying insects and other little-understood animal behaviors, the study is gaining new perspectives on how invertebrates respond to, interact with and navigate virtual 'worlds' created by advanced entertainment technology.

Researchers highlight Nobel-winning AI breakthroughs and call for interdisciplinary innovation

A new article examines the convergence of physics, chemistry, and AI, highlighted by recent Nobel Prizes. It traces the historical development of neural networks, emphasizing the role of interdisciplinary research in advancing AI. The authors advocate for nurturing AI-enabled polymaths to bridge the gap between theoretical advancements and practical applications, driving progress toward artificial general intelligence.

The future of edge AI: Dye-sensitized solar cell-based synaptic device

Physical reservoir computing (PRC) utilizing synaptic devices shows significant promise for edge AI. Researchers from the Tokyo University of Science have introduced a novel self-powered dye-sensitized solar cell-based device that mimics human synaptic behavior for efficient edge AI processing, inspired by the eye's afterimage phenomenon. The device has light intensity-controllable time constants, helping it achieve high performance during time-series data processing and motion recognition tasks. This work is a major step toward multiple time-scale PRC.

Vultures and artificial intelligence(s) as death detectors: High-tech approach for wildlife research and conservation

In order to use remote locations to record and assess the behavior of wildlife and environmental conditions, the GAIA Initiative developed an artificial intelligence (AI) algorithm that reliably and automatically classifies behaviors of white-backed vultures using animal tag data. As scavengers, vultures always look for the next carcass. With the help of tagged animals and a second AI algorithm, the scientists can now automatically locate carcasses across vast landscapes.

Robot identifies plants by ‘touching’ their leaves

Researchers have developed a robot that identifies different plant species at various stages of growth by 'touching' their leaves with an electrode. The robot can measure properties such as surface texture and water content that cannot be determined using existing visual approaches. The robot identified ten different plant species with an average accuracy of 97.7% and identified leaves of the flowering bauhinia plant with 100% accuracy at various growth stages.
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