A Gaussian probabilistic bit derived from a stochastic spintronics device has been used in new computing hardware developed by researchers at Tohoku University and the University of California, Santa Barbara.
A new MIT technique improves machine learning by removing key biased data points, boosting model performance for minority populations while preserving accuracy.
The EXPLINGO system by MIT converts intricate machine-learning explanations into readable narratives, improving trust in AI predictions for users.
A novel approach called 'black-box forgetting' enhances vision-language classifiers, allowing selective class forgetting to boost AI efficiency and accuracy.
LabEmbryoCam facilitates simultaneous monitoring of over 3,000 embryos, providing insights into environmental impacts on early life stages in aquatic species.
The world’s first AI-designed urban wind turbine, customized to the particular wind conditions of a particular region, was unveiled by precision metal fabricators KwikFab and AI design experts EvoPhase.
Researchers at Tokyo University of Science developed a dye-sensitized solar cell synapse, enhancing edge AI with low-power, high-accuracy motion detection.
According to a study published in Radiology, radiologists and other medical professionals may rely too heavily on AI when making diagnostic decisions, particularly when it identifies a specific region of interest in an X-ray.
A study published in Device details how researchers have developed a robot capable of identifying different plant species at various growth stages by "touching" their leaves with an electrode.
Researchers from the University of Liverpool demonstrate in a study that was published in the journal Nature how mobile robots that make decisions using AI logic could complete exploratory chemistry research tasks just as well as humans, but much more quickly.
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