首页|Research from University of Nevada Provides New Study Findings on Artificial Int elligence (Generative artificial intelligence for distributed learning to enhanc e smart grid communication)
Research from University of Nevada Provides New Study Findings on Artificial Int elligence (Generative artificial intelligence for distributed learning to enhanc e smart grid communication)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news reporting from Reno, Nevada, by NewsRx journalists, research stated, "Machine learning models are the backbone of smar t grid optimization, but their effectiveness hinges on access to vast amounts of training data. However, smart grids face critical communication bottlenecks due to the ever-increasing volume of data from distributed sensors." The news correspondents obtained a quote from the research from University of Ne vada: "This paper introduces a novel approach leveraging Generative Artificial I ntelligence (GenAI), specifically a type of pre-trained Foundation Model (FM) ar chitecture suitable for time series data due to its efficiency and privacy-prese rving properties. These GenAI models are distributed to agents, or data holders, empowering them to fine-tune the foundation model with their local datasets. By fine-tuning the foundation model, the updated model can produce synthetic data that mirrors real-world grid conditions. The server aggregates fine-tuned model from all agents and then generates synthetic data which considers all data colle cted in the grid. This synthetic data can be used to train global machine learni ng models for specific tasks like anomaly detection and energy optimization. The n, the trained task models are distributed to agents in the grid to leverage the m."
University of NevadaRenoNevadaUnit ed StatesNorth and Central AmericaArtificial IntelligenceCyborgsEmerging TechnologiesMachine Learning
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