与「OPM」相关的搜索结果

Open-weight models are essential to a healthy AI ecosystem. Together with others across our industry, we are outlining a path for open-weight models to strengthen American competitiveness and expand economic opportunity, while protecting national security.

Elon Musk's DOGE helped end one of America’s most outdated government systems. Deep inside a limestone mine in Pennsylvania, the U.S. government was still processing federal retirement paperwork by hand. • Around 10,000 retirement applications were being manually processed every month. • More than 400 million paper records were stored underground. • Retirees often had to wait months because of this outdated paper-based system. • Elon Musk publicly exposed how broken the process was. Now OPM says it has reached the “Last Day of Paper,” with records being digitized and physical copies set to be shredded. Elon Musk: “Now people can retire as soon as they want, instead of waiting 6 months for paper to be carried into a mine.” This is exactly why DOGE was needed.

Yesterday was the end of paper retirement processing at OPM, a major milestone in modernizing how we serve the federal workforce. Read the @foxnews exclusive:

Build agents that can see, reason, and take action across browser, desktop and mobile environments. Gemini 3.5 Flash now features built-in computer use capabilities: 📱 Custom client-side functions for human-in-the-loop takeover 🔒 Configurable action-level safety policies 🛡️ Intent arguments to maximize transparency Learn more in the blog →

最近和朋友聊得最多的话题，不是AI代理能做什么，而是AI代理做完事以后，怎么判断它做得好不好。 智能合约走到这块就卡住了。它能验证钱付了没、交易发生了没、时间戳对不对，但完全判断不了质量符不符合预期、交付物是不是真的有用、有没有偷懒或者编造信息。 传统方案都不太站得住。中心化平台有作恶风险和利益冲突，Oracles只能喂确定性数据，ZK/opML这类零知识证明能验证大模型推理结果的真实性，但只能证明确实是某个模型跑了这个输入，对判断结果本身的好坏无能为力。传统声誉系统也被大家刷分刷怕了，根本就不敢信。 所以我想聊一个很有意思的用例：UGC内容激励市场的自动化仲裁。 想像一个场景，Web3社区发起任务，比如“在Twitter上分析当前市场叙事趋势”，AI代理提交内容，人类编辑完成最终审核，通过GenLayer的Intelligent Contracts自动仲裁并分发激励。项目方把任务需求和锁定的激励资金一起发到GenLayer链上，代理完成任务后提交交付物。Intelligent Contracts直接连到Twitter验证内容是否公开发布，评估主题相关性，检查信息的实时性，判断分析深度，甚至检测有没有批量生成的痕迹。多LLM验证者独立推理，大部分达成一致就锁定结果进入最终性窗口，窗口期内任何人都可提交保证金发起上诉。上诉触发新的验证者加入，上诉一次就翻倍验证者数量，直到全网达成共识，正确的上诉方拿回保证金并获得额外奖励。 为什么非得在@GenLayer做这件事？传统智能合约根本判断不了这东西，Oracles和零知识证明只回答“模型输出是否正确”，不回答“输出是否有价值”。GenLayer的验证节点跑的不是相同代码，而是搭配不同的大模型独立推理。Intelligent Contracts可以直接拉取Twitter页面、调用LLM分析质量和相关性、对比多个交付物的相对优劣，所有操作不用中间人，全链上可追溯。 我还想提一个更大胆的方向：不只是UGC内容市场，AI代理之间的商业行为也需要一个信任层。两个代理做完交易后起了分歧，人类法院动辄几百天、最低十万美元的成本根本接不住，而且跨境无法执行。GenLayer做的就是为自治代理量身打造的“链上司法环境”，24/7不睡觉，成本极低，执行极快。这才是整个AI经济真正需要的底层基础设施。 整个AI代理经济真正的瓶颈不是这些模型够不够聪明，而是仲裁。谁来评判工作质量？遇到纠纷谁来解决？输出的结果到底有没有价值？这才是最容易被低估，也最值得花时间琢磨的方向。