查看更多>>摘要：The patent’s assignee for patent number 12043515 is Otis Elevator Company (Farmi ngton, Connecticut,United States).News editors obtained the following quote from the background information suppli ed by the inventors:“The subject matter disclosed herein generally relates to e levator systems and, more particularly, to elevatorsystem management utilizing machine learning.
查看更多>>摘要：No assignee for this patent application has been made.Reporters obtained the following quote from the background information supplied by the inventors:“This disclosure generally relates to training specialized mac hine learning models, and more specifically,to machine learning models that can make recommendations
查看更多>>摘要：This patent application is assigned to Adobe Inc. (San Jose, California, United States).The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “A typical computing device often includes multi tude of different applications, examplesof which include graphic design applica tions, photo editing applications, video editing application, stockimage databa ses, and so on. These applications typically include a search feature that suppo rts a userquery to initiate a search for content, features, products, functions , and so on, which are made available bya respective application. To provide be tter search results, application search features typically implementspell corre ction functionality as part of the user query. However, conventional spell corre ction techniquesimplemented for in-application searches often lead to user frus tration due to slow search (i.e. high latencytimes) and inability to correct ap plication-specific spelling mistakes. Further, conventional spell correctionmec hanisms are often built and trained on a particular language (e.g., the English language) and facedifficulties scaling to additional languages, thus surfacing inaccurate search results for user queries inputin different languages”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from os f.io:“Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potentialto dramatically enhance the computing power and energy effici ency of mainstream electronic processors,due to their ultra-large bandwidths of up to 10’s of terahertz together with their analog architecture that avoids the need for reading and writing data back-and-forth. Different multiplexing techni ques have beendemonstrated to demonstrate ONNs, amongst which wavelength-divisi on multiplexing (WDM) techniquesmake sufficient use of the unique advantages of optics in terms of broad bandwidths. Here, we reviewrecent advances in WDM-bas ed ONNs, focusing on methods that use integrated microcombs to implementONNs.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Computational approaches leveraging computer vision and machine learning have t ransformed thequantification of animal behavior from video.“However, existing methods often rely on task-specific features or models, which struggle to generalizeacross diverse datasets and tasks. Recent advances in ma chine learning, particularly the emergence ofvision foundation models, i.e., la rge-scale models pre-trained on massive, diverse visual repositories, offersa w ay to tackle these challenges. Here, we investigate the potential of frozen vide o foundation modelsacross a range of behavior analysis tasks, including classif ication, retrieval, and localization. We use asingle, frozen model to extract g eneral-purpose representations from video data, and perform extensiveevaluation s on diverse open-sourced animal behavior datasets.
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