首先，大模型本身无法主动感知，只能对输入被动响应。智能体需要用外部感知组件来主动获取环境信息。对于数字世界的任务，通过智能体工程可以建立基于时间的触发器，定期检查日志、邮件、股价变动等；或基于事件的订阅、监听，接收API推送的事件通知，或当数据库发生变更时自动唤醒记录数据。在物理世界中，智能体还可以通过传感器、摄像头、麦克风等设备采集视觉、听觉、触觉等信号。
值得注意的是，海外业务作为“第二增长曲线”，2025年保持强劲增长。全年会员收入同比增长超过30%，第四季度同比增速提升至40%，其中巴西、墨西哥和印尼表现尤为亮眼，会员收入同比涨幅均超80%。
。关于这个话题，同城约会提供了深入分析
Раскрыты подробности похищения ребенка в Смоленске09:27，更多细节参见搜狗输入法2026
One challenge is having enough training data. Another is that the training data needs to be free of contamination. For a model trained up till 1900, there needs to be no information from after 1900 that leaks into the data. Some metadata might have that kind of leakage. While it’s not possible to have zero leakage - there’s a shadow of the future on past data because what we store is a function of what we care about - it’s possible to have a very low level of leakage, sufficient for this to be interesting.
Researchers in California are experimenting with air driven actuation