20政企、创业者必读 21 DeepSeek出现之前的十大预判 之八 智能体推动大模型快速落地  能够调用各种工具，具有行动能力  调用企业专业知识，更懂企业  将日常重复性业务流程形成Playbook，实现流程自动化  通过目标拆解，多次调用大模型以及专家模型协同，形成 慢思考能力 传统软件是辅助人的工具，Agent是能够自主工作的数字员工，是新的生产力政企、创业者必读 22 DeepSeek出现之前的十大预判 基础科学 能源自由 宇宙探索 生命科学 科学 能力 6 AI Fo r Science 知识管理（ 内部知识管理、 外部情报分析、 大数据分析、 工作流知识） 专家经验模型（ 专业模型训练） 业务流程自动化（ A g e n t框架） 组织协同（ 工作流） 人机交互 赋能个人和 企业员工 生产力提升 多模态 能力 3 图片理解和处理 视频理解和处理 音频理解和处理 非结构化文档处理 47政企、创业者必读 对外 四个方向 降低10倍人力 降低10倍成本 提高10倍效率 提升10倍体验 四个“十倍”原则  四个方向  四个十倍 选择场景 分解流程  做过去只有人才能做的事  做人做的重复繁琐易出错的事  拆解繁琐复杂的业 务流程 55政企、创业者必读 场景选择示例：人员招聘系统 场景分得足够细，就可以训练对应的专业模型来解决问题 注：经360内部测试，深色的业务环节更加符合“四个十倍”原则

全等方面的能力，降低 人工智能系统被攻击、重要数据被窃取或泄露的风险，保障业务不中断。 （f） 重点领域使用者应合理限制人工智能系统对数据的访问权限，制定 数据备份和恢复计划，定期对数据处理流程进行检查。 （g）重点领域使用者应确保操作符合保密规定，在处理敏感数据时使用 加密技术等保护措施。 （h）重点领域使用者应对人工智能行为和影响进行有效监督，确保人工 智能产品和服务的运行基于人的授权、处于人的控制之下。

中跳转越少就越快。继续类比，假设有一个服务员在餐厅里处理多个桌子的点菜。在 一个桌子报完所有菜后再移动到下一个桌子是最有效率的。从桌子 A 听一个菜，接着 桌子 B 听一个菜，然后再桌子 A，然后再桌子 B 这样的流程会更加缓慢。出于同样原 68/562Rust 程序设计语言 简体中文版 因，处理器在处理的数据彼此较近的时候（比如在栈上）比较远的时候（比如可能在 堆上）更高效。 当你的代码调用一个函数时，传 std::io::Error; pub trait Write { fn write(&mut self, buf: &[u8]) -> Result; fn flush(&mut self) -> Result<(), Error>; fn write_all(&mut self, buf: &[u8]) -> Result<(), Error>; trait 中的函数最终看起来像这样： pub trait Write { fn write(&mut self, buf: &[u8]) -> Result; fn flush(&mut self) -> Result<()>; fn write_all(&mut self, buf: &[u8]) -> Result<()>; fn write_fmt(&mut

None: break self.write(chunk) fetch_future = convert_yielded(self.fetch_next_chunk()) await self.flush() This is a little easier to do with decorated coroutines, because they start immediately when called: fetch_future if chunk is None: break self.write(chunk) fetch_future = self.fetch_next_chunk() yield self.flush() Looping In native coroutines, async for can be used. In older versions of Python, looping is tricky and elsewhere in Tornado are not thread-safe. In particular, methods such as write(), finish(), and flush() must only be called from the main thread. If you use multiple threads it is important to use IOLoop

self.write(chunk) fetch_future = convert_yielded(self.fetch_next_chunk()) await self.flush() This is a little easier to do with decorated coroutines, because they start immediately when called: break self.write(chunk) fetch_future = self.fetch_next_chunk() yield self.flush() Looping In native coroutines, async for can be used. In older versions of Python, looping is RequestHandler.clear_header() RequestHandler.set_default_headers() RequestHandler.write() RequestHandler.flush() RequestHandler.finish() RequestHandler.render() RequestHandler.render_string() RequestHandler.g

alternately by one process and then the other. (Setting $|=1 in Perl causes each print statement to flush the stdout handle, which is necessary for this example to work. Otherwise all the output is buffered source Base.flush – Function. flush(stream) Commit all currently buffered writes to the given stream. source Base.close – Function. close(stream) Close an I/O stream. Performs a flush first. source – Function. closewrite(stream) Shutdown the write half of a full-duplex I/O stream. Performs a flush first. Notify the other end that no more data will be written to the underlying file. This is not

alternately by one process and then the other. (Setting $|=1 in Perl causes each print statement to flush the stdout handle, which is necessary for this example to work. Otherwise all the output is buffered source Base.flush – Function. flush(stream) Commit all currently buffered writes to the given stream. source Base.close – Function. close(stream) Close an I/O stream. Performs a flush first. source – Function. closewrite(stream) Shutdown the write half of a full-duplex I/O stream. Performs a flush first. Notify the other end that no more data will be written to the underlying file. This is not

alternately by one process and then the other. (Setting $|=1 in Perl causes each print statement to flush the stdout handle, which is necessary for this example to work. Otherwise all the output is buffered source Base.flush – Function. flush(stream) Commit all currently buffered writes to the given stream. source Base.close – Function. close(stream) Close an I/O stream. Performs a flush first. source – Function. closewrite(stream) Shutdown the write half of a full-duplex I/O stream. Performs a flush first. Notify the other end that no more data will be written to the underlying file. This is not

alternately by one process and then the other. (Setting $|=1 in Perl causes each print statement to flush the stdout handle, which is necessary for this example to work. Otherwise all the output is buffered source Base.flush – Function. flush(stream) Commit all currently buffered writes to the given stream. source Base.close – Function. close(stream) Close an I/O stream. Performs a flush first. source – Function. closewrite(stream) Shutdown the write half of a full-duplex I/O stream. Performs a flush first. Notify the other end that no more data will be written to the underlying file. This is not

alternately by one process and then the other. (Setting $|=1 in Perl causes each print statement to flush the stdout handle, which is necessary for this example to work. Otherwise all the output is buffered source Base.flush – Function. flush(stream) Commit all currently buffered writes to the given stream. source Base.close – Function. close(stream) Close an I/O stream. Performs a flush first. source – Function. closewrite(stream) Shutdown the write half of a full-duplex I/O stream. Performs a flush first. Notify the other end that no more data will be written to the underlying file. This is not