美国能源企业Blue Energy与GE Vernova合作，在得克萨斯州开发一座2.5吉瓦的混合电站，同时部署核能与天然气发电设施，以应对AI数据中心激增的电力需求。该项目首创“气转核”模式，通过天然气快速供电，再逐步过渡到核能，有效解决传统核电审批和建设周期长的痛点，为高能耗产业提供灵活、稳定的电力解决方案。
美国能源部与AMD签署10亿美元合作协议，将共同建造两台超级计算机，用于支持核能利用、癌症治疗和国家安全等重大科研领域。美能源部长表示，此举将显著提升美国在复杂实验中的数据处理能力。
劳斯莱斯CEO宣布计划利用小型模块化核反应堆为AI数据中心供电，若成功可能使公司成为英国市值最高企业。此举旨在应对AI发展带来的能源需求挑战。
谷歌与电力公司签署协议，通过需求响应计划减少AI数据中心在高峰期的电力消耗。该计划将调整机器学习工作负载，预计2023年启动，可缓解电网压力并减少新电厂建设需求。国际能源署预测，到2030年AI数据中心能耗可能增长四倍，接近日本当前用电量。谷歌此前已通过类似方案成功减轻电网负担，科技公司正积极寻求核能、可再生能源等解决方案应对电力需求激增。
atomic-canyon
fermi-bert-1024是一款专门针对核能领域优化的BERT预训练模型。该模型在维基百科、Books3和美国核管理委员会ADAMS数据库数据上训练，特别优化了核能行业的技术术语和监管语言处理能力。在橡树岭国家实验室的Frontier超级计算机上使用128个AMD MI250X GPU训练10小时，为核能应用提供坚实基础。
面向核能领域优化的稀疏检索模型，将查询和文档编码为高维稀疏向量，提升核能专业术语的处理效率
kumo24
该模型是基于MistralAI 7B架构微调的文本分类模型，专门用于分析Twitter/X平台上关于核能话题的情感倾向，分类准确率达到94%。
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