根据IDC的预计，活跃智能体的数量将从2025年的约2860万，攀升至2030年的22.16亿。这意味着五年后，能够帮助企业或个体执行任务的数字劳动力数量将是现在的近80倍，年复合增长率139%；任务执行的数量将从2025年的440亿次暴涨至2030年的415万亿次，年复合增长率高达524%；Token的消耗将从2025年的5000亿激增至2030年的1.5万亿亿，年复合增长34倍。IDC的预测未必准确，但趋势非常明显，每一家企业都要为此做好准备。
cmd: [Function: cmdValidatePromo], // The command waiting to be executed。业内人士推荐91视频作为进阶阅读
。服务器推荐是该领域的重要参考
Scroll to load interactive demo。爱思助手下载最新版本是该领域的重要参考
I have been thinking a lot lately about “diachronic AI” and “vintage LLMs” — language models designed to index a particular slice of historical sources rather than to hoover up all data available. I’ll have more to say about this in a future post, but one thing that came to mind while writing this one is the point made by AI safety researcher Owain Evans about how such models could be trained: