{
  "text": "大家好,我是Kid。最近有個模型非常火,它的名字叫Jeff。它不是平常我們對話的那種大語言模型。它是由Type-Safe AI公司開發的一款模型。它的創始人曾經是在OpenAI工作,然後是XGPT的共同作者。Jeff特別適合無人職守的自動化,用它來打遊戲也非常好。我們可以通過這個視頻了解一下Jeff能幫我們做什麼。\n如果是正常的大语言模型\n它呢就会一个token一个token的\n蹦出自来\n花费时间8.5秒\n那如果是JF呢\n它就会给出几个选项\n然后会给出知心度\n花费时间0.1秒\n如果是让它玩游戏\n它呢是\n就是由固定的几个操作\n往上往右往前\n还有Shopter\nJeff呢\n他是能做一个选择\n分类\n评分\n路由\n不能去写诗\n写代码\n或者是一步步的推理\n这视频做的还是非常好的\n对于开发者来说\n主要有三种可以设置\n第一呢是choice\n选择\n从选项里选一个\n第二是打分\n然后第三是\n判断陈述是否成立\n它是0到1的一个真值的分数\n一个请求里呢\n可以混合多种问题\n模型还可以并行去回答\n官方的手法呢\n就是把它当成软件里的智能的IF\n路由打分器\nJIF的速度呢\n是非常非常快的\n而且它的价格尤其的便宜\n我掉落了200多次\n花费了200分\n而且Type Safe呢\n现在还提供五刀的一个体验额度\n所以我得花很长时间\n才能把这个\n才能把这个五刀的额度给使用出去\n我们可以在TyperSafe里面去加入它的Whitlist\n如果你特别着急的话\n也可以通过OperRouter进行调用\n或者是AI Gateway进行调用\n它也登录了Cloud Flare的AI\n所以是有多个路径可以调用它的\n而且它非常有意思的是\n它的输出Token是不收费的\n官方给出的理由是\n新的架构下输出便宜到不必寄费\n这里就有一个例子呢\nVerso的CTO做了一个测试\n它呢对比调用Gem9 2.5 Flashlight来做分类\nGem9 2.5 Flashlight呢\n它的API还是比较便宜的\n而将Jeff和Gem9做一个对比\n它的据确率更高\n而且速度也更快\n通过这张图\n我们可以看到Jeff\n它的质地程度是非常不错的\n非常接近于Terra了\n但是要比Terra便宜非常多\n我们可以在Type-Safe官网右上角\n点击他的加入waitlist来申请\n现在就来看一下X上面\n关于Jeff有哪些精彩的案例\nVersal的CEO认为\n把他们的FX安全审查\n换成Jeff\n对面GibT和Luna呢\nJeff的速度快到18倍\n而且还更准确\n把500封邮件发给Jeff\n他仍在几秒内就帮你分类好\n而且成本非常低\nBoss CEO认为呢\n企业里那些分类路由安全判断们\n那现在有了Jeff\n对大量的企业任务就意义巨大\n有用户昨天刚打到权限\n他就将Jeff集成到他们的数据管道里\n实体识别情绪分析\n把相关信号粘起来等等\n他认为都非常惊艳\nJeff有一大应用就是他在浏览器方面的改进\n这浏览器方面的例子\n比如说七秒查机票\n只花了0.0039刀\n又快\n质量又好\n知名开源产品CV\n它也是紧跟潮流\n立即发了一个\n和Jeff相关的跨系统计算机使用\n叫Jeff Use\n在玩2048的时候\nJeff的速度快了5倍\n成本大约便宜1000倍\n比Astra更高效\n还有用户将Jeff和OpenCode结合起来\n测试应用\n测试的时候就发现\n点按钮快到像是在看加速片\nJeff呢他在浏览器工作上是非常非常便宜的\n比如说这样一位用户\n他就分享浏览器忘记关了\n那消耗了这么多token才花费不到七刀\nScode的作者呢\n他用Jeff来控制iOS的模拟器\n去建一个日历事件\n我们会看到这边会写着\nTaper\n然后ScreenChanger\nScreenChanger\n等等\n还有用户喊话Sam\n让Codex负责规划\nJeff负责从页面选择点谁\n有用户他分享了一个点子\n让Jeff去做及时的压缩\n给每次2Core打分\n然后丢掉无关的上下文\n我们可以看一下这样的一个例子\n绿色的就是留下的\n红色的就是删去\n也有用户还做了一个Jeff的review\n给编码agent接上打分反馈还的一个mcp\n不同的ai agent\n然后review之后进行打分\n给定他一个数值到了哪个程度\n那就让他再去优化\n有用户就直接做了一个crowd的插件\n一秒就把绘画从近100万token上下无人长度\n压缩到8.6万\n这里展示压缩前后的一些情况\n有兴趣的话\n大家去看一下\nRosa的工程师呢\n说每个Agent\nHannis呢\n现在都能用上Jeff\n通过这样的工具\n也有用户呢\n给OpenCode写了一个插件\n自栏语言写规则\nJeff呢\n拦住每一条道路\n还有用户\n使用Jeff呢\n光速给提交\n打安全补丁的标签\n当然Jeff呢\n来做意向调研\n也是非常好的\n比如说这样的一位用户\n做的一个分享\n也有用户花了8个小时\n让Jeff做一个爆款帖分类器\n他认为Jeff的准确率呢\n和Fibber 5.1一样好\n但是快了100倍\n也有博主呢\n让Jeff去分析自己的3000多条帖子\n然后找出一些公式\n最后这是推荐的主题\n也有用户分享\n我们可以通过Jeff呢\n做一些规则匹配\n就可以傻瓜式的\n将一些文件进行分类了\n还有用户呢\n把Jeff接到自动驾驶的决策上\n他认为Jeff\n对自动驾驶的影响会非常大\n一个用户呢\n让Jeff像人一样\n来复原一个魔方\n他能在很快的时间内\n来对这个魔方进行转动\n视频里是放慢了\n方便我们去看清楚\n还有用户呢\n他说他花了一周时间\n才把PPO策略\n训练到通关的超级马利奥世界里\n这里的PPO是尽端策略优化\n而Jeff他是花了30分钟就打通了\n非常非常恐怖的一个效率\n有用户就来畅想了\n一个Jeff在云电脑上玩Minecraft\n那如果想象1000个11个\n每一个都在云端自己的电脑上协作\n发现新科学 跑实验 设计新药\n而且是全天候的\n也有用户让Jeff做一些实时的广告拦截\n比如说他做了一个插件\n然后进入了一个网站\nBaby AGI的作者呢\n还用Jeff来抽图\n我们可以看一下这里的demo\nFluss的作者呢\n对Jeff非常非常认可\n他认为以前很多场景\n用大语言模型\n是根本不成立的\n今天大家也可以看到\n我为什么梳理了那么多案例\n实在是Jeff太优秀了\n真的是有非常非常多\n可以和我们现在的agent\n结合在一起使用的玩法\n有用户认为呢\nHannis就会被改写\n无论是Kodas CC\n内置这样的dev型的决策\n只是时间的问题\nVestor CEO认为\n有很多是AI炒的一些热点\n但是Jeff是真正站得住的那个产品\n他认为Jeff这种AI\n可能比今天的大元模型\n更持久的改写我们的工作和产品\n因为Jeff输入是非常非常划算的\n所以大量的自动化\n就会突然变得买得起\n说了那么多\n已经有人做了一个非常好的仓库\n是Orzen Type Safe\n仓库里呢\n有官方的资源\n也有很多社区的项目\n比如客户端库和集成\nAgent和开发者工具\n浏览器智能体\n机器人交互演示\n评测与独立研究等等\n非常非常多\n而Jeff呢\n发布也才两天左右的时间而已\n我们使用Jeff呢\n也非常简单\n进入他的控制台\n它有个Quick Start\n然后我们可以copy这里的\n给Agent的提示词\n就可以在我们电脑上\n安装Type Safe的Skill\n比如这里呢\n我呢就调用它的Skill\n然后让它帮我做一个\n打游戏的Web页面\nJPT很快就帮我做出了这样一个游戏\n第一章呢\n我刚刚已经让Jeff已经游玩过了\n我们先看一下这里的游戏指南\n可以让Jeff来玩\n也可以手动接管\n总共有三个章节\nChoice它会显示后选动作的真实概率\n自信度衡量分布的集中程度\nNord它是单独判断是否急需休息\n第一关已经打完了\n那现在我来点一下看一下第二关\n我们可以观察右侧Jeff的每一步\n今天的这个视频我是没有做变速\n所以大家可以观察一下\n杰弗他的一个速度情况\n现在来点击一下\n让他开始\n他开始收集到原木了\n有了原木之后\n这里的桥就可以搭建好了\n学好之后\n他就可以去获取对岸的胡萝卜\n然后还有一个胡萝卜\n他还没收集好\n所以他这里收集一下\n再回到他的家\n我可以把这里的蛋报呢\n进行保存\n也就是说\n他会下载一个JSON文件\n右侧我们会看到\n他的当前章节的目标\n这里的概率呢\n他就写的比较大\n所以兔子呢\n最后就回到引力去了\n在探险偏好里呢\n也可以去选择一下\n页面的下方\n还可以看到他的冒险记录\n还有他的休息的情况\n我呢之前将第一个章节\n玩的一个战报\n然后下载了下来\n让AI介绍一下\n他说呢\n回合\n九回合\n结局胜利\n体力还剩37\n葛萝卜的话有五根\n第一章节里面\n它是没有木头的\n下方呢\n是兔子走过的路线\n日志对应的是什么\n决策记录里\n我们会看到\n用的是Jave的模型\n然后第一步是比较慢\n这和我当前的网络\n当然也有很大关系\n后面的话快乐非常多\n大多数的致敬度呢\n在0.77到0.96\n其中有两步\n有欲\n因为一开始这个桥呢\n没有修复好\n所以\nJeff呢就来回\n在这三个洪框的点\n这里来回折腾\n后来我就让Astra来修复了一下\n这个游戏\n现在我们再来到\n他的第三章节\n那我这里呢\n点击一下手动接管\n音效呢也打开了\n那我点\n点一个\n比如说\n我这里先点了除菊小镜\n再点一个萤火炒坡\n然后我们会看到\n还有胡萝卜\n然后这里还有木头\n没有收集到\n那我再返回别的地方\n点一下\n这里收集到木头了\n再点一下\n他说等待修船\n等等\n那再来让他单独来玩一下\n看看他怎么玩\n修好桥了\n然后再去取胡萝卜\n又返回来\n它要去取胡萝卜\n因为这个设定里呢\n它还需要一个金种子\n开启石门\n所以它最后是在右侧\n游戏那里去结束的\n最后呢再来看一个案例\n我呢让Astra做的一个页面\n外星人要到地球\n那要把外星人的奇怪发言\n变成代码执行的判断\n左边呢\n就会有非常多的\n待检的旅客\n总共是有24个\n他们呢\n长的是有三种样式\n名字有各个不同\n比如说这里的白闪博士\n他说旅客的原话\n是什么样子的\n那正常这种情况下\n他说他有简易放行证明\n点击一下开始扫描\n肯定是让他去通过的\nJeff这里呢\n他有三个判断\n第一是Choice\n第二呢是No\n那对这样外星人呢\n我们就不需要过度的去关注他\n然后下方就有一个欢迎雨\n欢迎来到地球\n决策档案里呢\n就会显示刚刚做了那些决策\n实测的实验室里呢\n这是之前跑过的一次例子\n这是24条人工编写的一个测试情境\n每条呢\n向真实的Jeff来发送\n同一state下的三个独立问题\n参考标签不会传给模型\n比如说\n这里的参考通道啊\n是哪个\n那就不会发给Jeff\n通过这个测试呢\n就可以比对人工写的参考信息\n和GF判断了结果之间的一些差别\n最后的对照里面会说明他们的状态\n那我这里再点击一下重新实测\n我是开了最多的10号并发\n那我们可以看到它是成功完成\n参考是有91%\n是一致的\n耗时当然是非常短的\n实际耗用了这些Token\n那我再点一下来进行测试\n这个刚刚的测试结果也是一样的\n不过呢每次测试不一定是完全一样的\n所以有的时候可能这里是百分百\n然后下方我们可以看一下\n有哪些地方是不一致\n比如说这对这个外星人的一个分析\n然后参考认为是可以常规路径的\n而Jeff认为需要深度调查\n对这两位外星人人工分析\n和Jeff判断有不一致的情况\n我们看一下\n他为什么对这里是要人工复合呢\n这位外星人他说\n他运送了一件武器外星的博物馆空壳\n内部完全猜出确认没有什么什么什么\n还有附有检查证明\n以上就是今天介绍Jeff的所有内容\n这个模型对于我们日常工作还是有非常大的帮助的\n非常推荐大家去了解它\n记得看社区里面\nAlson TypeSafe的仓库\n希望我的视频对你有帮助\n我们下期再见",
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      "text": "大家好,我是Kid。最近有個模型非常火,它的名字叫Jeff。它不是平常我們對話的那種大語言模型。它是由Type-Safe AI公司開發的一款模型。它的創始人曾經是在OpenAI工作,然後是XGPT的共同作者。Jeff特別適合無人職守的自動化,用它來打遊戲也非常好。我們可以通過這個視頻了解一下Jeff能幫我們做什麼。",
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      "text": "如果是正常的大语言模型",
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      "text": "它呢就会一个token一个token的",
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      "text": "蹦出自来",
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      "text": "花费时间8.5秒",
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      "text": "那如果是JF呢",
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      "text": "它就会给出几个选项",
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      "text": "然后会给出知心度",
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      "text": "如果是让它玩游戏",
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      "text": "往上往右往前",
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      "text": "还有Shopter",
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      "text": "分类",
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      "text": "评分",
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      "text": "路由",
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      "text": "不能去写诗",
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      "text": "或者是一步步的推理",
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      "text": "对于开发者来说",
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      "start": 81.04,
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      "text": "判断陈述是否成立",
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      "start": 83.56,
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      "start": 86.34,
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      "text": "一个请求里呢",
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      "start": 92.06,
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      "text": "官方的手法呢",
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      "start": 93.12,
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      "text": "就是把它当成软件里的智能的IF",
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      "text": "路由打分器",
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      "start": 102.04,
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      "text": "我掉落了200多次",
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      "text": "我们可以在TyperSafe里面去加入它的Whitlist",
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      "text": "也可以通过OperRouter进行调用",
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      "text": "它也登录了Cloud Flare的AI",
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      "text": "它的输出Token是不收费的",
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      "text": "这里就有一个例子呢",
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      "text": "它呢对比调用Gem9 2.5 Flashlight来做分类",
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      "text": "通过这张图",
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      "text": "非常接近于Terra了",
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      "text": "点击他的加入waitlist来申请",
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      "start": 174.28,
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      "text": "现在就来看一下X上面",
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      "text": "关于Jeff有哪些精彩的案例",
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      "text": "Versal的CEO认为",
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      "text": "把他们的FX安全审查",
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      "text": "换成Jeff",
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      "start": 184.24,
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      "text": "对面GibT和Luna呢",
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      "text": "Jeff的速度快到18倍",
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      "text": "而且还更准确",
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      "start": 189.58,
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      "text": "把500封邮件发给Jeff",
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      "text": "他仍在几秒内就帮你分类好",
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      "start": 195.38,
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      "text": "而且成本非常低",
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      "start": 197.14,
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      "text": "Boss CEO认为呢",
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      "start": 198.68,
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      "text": "企业里那些分类路由安全判断们",
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      "text": "那现在有了Jeff",
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    {
      "start": 203.04,
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      "text": "对大量的企业任务就意义巨大",
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    {
      "start": 205.8,
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      "text": "有用户昨天刚打到权限",
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    {
      "start": 208.02,
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      "text": "他就将Jeff集成到他们的数据管道里",
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      "start": 211.6,
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      "text": "实体识别情绪分析",
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    {
      "start": 213.98,
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      "text": "把相关信号粘起来等等",
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      "start": 216.08,
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      "text": "他认为都非常惊艳",
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      "text": "Jeff有一大应用就是他在浏览器方面的改进",
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      "start": 222.64,
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      "text": "这浏览器方面的例子",
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      "start": 224.96,
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      "text": "比如说七秒查机票",
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    {
      "start": 227.3,
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      "text": "只花了0.0039刀",
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      "start": 229.8,
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      "text": "又快",
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    {
      "start": 230.48,
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      "text": "质量又好",
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    {
      "start": 231.5,
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      "text": "知名开源产品CV",
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      "start": 233.16,
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      "text": "它也是紧跟潮流",
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      "start": 234.68,
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      "text": "立即发了一个",
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    {
      "start": 236.3,
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      "text": "和Jeff相关的跨系统计算机使用",
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      "text": "叫Jeff Use",
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    {
      "start": 241.6,
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      "text": "在玩2048的时候",
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      "start": 243.3,
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      "text": "Jeff的速度快了5倍",
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      "start": 245.08,
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      "text": "成本大约便宜1000倍",
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      "start": 247.08,
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      "text": "比Astra更高效",
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      "start": 248.74,
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      "text": "还有用户将Jeff和OpenCode结合起来",
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      "text": "测试应用",
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      "text": "测试的时候就发现",
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    {
      "start": 254.32,
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      "text": "点按钮快到像是在看加速片",
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      "start": 257.28,
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      "text": "Jeff呢他在浏览器工作上是非常非常便宜的",
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      "text": "比如说这样一位用户",
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      "start": 264.02,
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      "text": "他就分享浏览器忘记关了",
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      "start": 267.1,
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      "text": "那消耗了这么多token才花费不到七刀",
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      "start": 270.62,
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      "text": "Scode的作者呢",
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      "text": "他用Jeff来控制iOS的模拟器",
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      "start": 276.36,
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      "text": "去建一个日历事件",
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      "start": 278.7,
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      "text": "我们会看到这边会写着",
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    {
      "start": 281.46,
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      "text": "Taper",
      "chunk": 0,
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    {
      "start": 281.88,
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      "text": "然后ScreenChanger",
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      "text": "等等",
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      "text": "还有用户喊话Sam",
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      "text": "让Codex负责规划",
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      "text": "Jeff负责从页面选择点谁",
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      "text": "有用户他分享了一个点子",
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      "start": 297.4,
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      "text": "让Jeff去做及时的压缩",
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      "text": "给每次2Core打分",
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      "start": 302.98,
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      "text": "然后丢掉无关的上下文",
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      "text": "我们可以看一下这样的一个例子",
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      "start": 308.0,
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      "text": "绿色的就是留下的",
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      "text": "红色的就是删去",
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      "start": 311.18,
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      "text": "也有用户还做了一个Jeff的review",
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      "start": 314.82,
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      "text": "给编码agent接上打分反馈还的一个mcp",
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      "text": "不同的ai agent",
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      "text": "然后review之后进行打分",
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      "start": 324.64,
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      "text": "给定他一个数值到了哪个程度",
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      "start": 329.24,
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      "text": "那就让他再去优化",
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      "start": 330.72,
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      "text": "有用户就直接做了一个crowd的插件",
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    {
      "start": 333.94,
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      "text": "一秒就把绘画从近100万token上下无人长度",
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    {
      "start": 339.12,
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      "text": "压缩到8.6万",
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    {
      "start": 341.02,
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      "text": "这里展示压缩前后的一些情况",
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      "start": 344.7,
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      "text": "有兴趣的话",
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    {
      "start": 345.64,
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      "text": "大家去看一下",
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      "start": 346.52,
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      "text": "Rosa的工程师呢",
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      "start": 347.94,
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      "text": "说每个Agent",
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      "text": "Hannis呢",
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      "start": 350.54,
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      "text": "现在都能用上Jeff",
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      "text": "通过这样的工具",
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      "text": "给OpenCode写了一个插件",
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      "start": 357.34,
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      "text": "自栏语言写规则",
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      "text": "Jeff呢",
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    {
      "start": 359.76,
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      "text": "拦住每一条道路",
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      "text": "还有用户",
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      "text": "使用Jeff呢",
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    {
      "start": 363.6,
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      "text": "光速给提交",
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    {
      "start": 365.02,
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      "text": "打安全补丁的标签",
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      "text": "当然Jeff呢",
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      "start": 367.7,
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      "text": "来做意向调研",
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      "start": 369.34,
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      "text": "也是非常好的",
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      "text": "比如说这样的一位用户",
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      "text": "做的一个分享",
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      "text": "也有用户花了8个小时",
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      "start": 375.42,
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      "text": "让Jeff做一个爆款帖分类器",
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      "text": "他认为Jeff的准确率呢",
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      "text": "和Fibber 5.1一样好",
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      "start": 382.8,
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      "text": "但是快了100倍",
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      "text": "也有博主呢",
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      "start": 385.32,
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      "text": "让Jeff去分析自己的3000多条帖子",
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      "start": 388.84,
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      "text": "然后找出一些公式",
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      "text": "最后这是推荐的主题",
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      "text": "也有用户分享",
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      "text": "我们可以通过Jeff呢",
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    {
      "start": 398.04,
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      "text": "做一些规则匹配",
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      "start": 399.7,
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      "text": "就可以傻瓜式的",
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      "start": 402.4,
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      "text": "将一些文件进行分类了",
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    {
      "start": 405.78,
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      "text": "把Jeff接到自动驾驶的决策上",
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      "text": "他认为Jeff",
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      "text": "对自动驾驶的影响会非常大",
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      "text": "一个用户呢",
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      "start": 413.96,
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      "text": "让Jeff像人一样",
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      "text": "来复原一个魔方",
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    {
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      "text": "他能在很快的时间内",
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      "start": 419.36,
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      "text": "来对这个魔方进行转动",
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      "text": "视频里是放慢了",
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    {
      "start": 423.76,
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      "text": "方便我们去看清楚",
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      "text": "还有用户呢",
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      "start": 426.58,
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      "text": "他说他花了一周时间",
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      "start": 429.34,
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      "text": "才把PPO策略",
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    {
      "start": 430.92,
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      "text": "训练到通关的超级马利奥世界里",
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      "text": "这里的PPO是尽端策略优化",
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      "text": "而Jeff他是花了30分钟就打通了",
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      "start": 441.46,
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      "text": "非常非常恐怖的一个效率",
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      "text": "有用户就来畅想了",
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      "text": "一个Jeff在云电脑上玩Minecraft",
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      "start": 449.74,
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      "text": "那如果想象1000个11个",
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      "start": 455.46,
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      "text": "发现新科学 跑实验 设计新药",
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      "start": 459.14,
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      "text": "而且是全天候的",
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      "text": "也有用户让Jeff做一些实时的广告拦截",
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      "text": "比如说他做了一个插件",
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      "start": 467.62,
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      "text": "然后进入了一个网站",
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      "text": "Baby AGI的作者呢",
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      "text": "还用Jeff来抽图",
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      "text": "我们可以看一下这里的demo",
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      "text": "Fluss的作者呢",
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      "text": "对Jeff非常非常认可",
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      "text": "他认为以前很多场景",
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      "start": 494.24,
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      "text": "用大语言模型",
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      "start": 495.28,
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      "text": "是根本不成立的",
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      "start": 496.64,
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      "text": "今天大家也可以看到",
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      "start": 497.92,
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      "text": "我为什么梳理了那么多案例",
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      "text": "实在是Jeff太优秀了",
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      "text": "真的是有非常非常多",
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    {
      "start": 503.64,
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      "text": "可以和我们现在的agent",
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      "avg_logprob": -0.14465627552550517,
      "no_speech_prob": 2.060273132653556e-11,
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    {
      "start": 506.26,
      "end": 508.2,
      "text": "结合在一起使用的玩法",
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      "avg_logprob": -0.14465627552550517,
      "no_speech_prob": 2.060273132653556e-11,
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    {
      "start": 508.2,
      "end": 509.42,
      "text": "有用户认为呢",
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      "avg_logprob": -0.14465627552550517,
      "no_speech_prob": 2.060273132653556e-11,
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    {
      "start": 509.42,
      "end": 511.02,
      "text": "Hannis就会被改写",
      "chunk": 1,
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      "avg_logprob": -0.14465627552550517,
      "no_speech_prob": 2.060273132653556e-11,
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    {
      "start": 511.02,
      "end": 512.8,
      "text": "无论是Kodas CC",
      "chunk": 1,
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      "avg_logprob": -0.14465627552550517,
      "no_speech_prob": 2.060273132653556e-11,
      "compression_ratio": 1.2646153846153847
    },
    {
      "start": 512.8,
      "end": 514.94,
      "text": "内置这样的dev型的决策",
      "chunk": 1,
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      "avg_logprob": -0.16404027717058048,
      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 514.94,
      "end": 516.4,
      "text": "只是时间的问题",
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    {
      "start": 516.4,
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      "text": "Vestor CEO认为",
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      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 518.28,
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      "text": "有很多是AI炒的一些热点",
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    {
      "start": 521.68,
      "end": 525.32,
      "text": "但是Jeff是真正站得住的那个产品",
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      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 525.32,
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      "text": "他认为Jeff这种AI",
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    {
      "start": 528.58,
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      "text": "可能比今天的大元模型",
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    },
    {
      "start": 530.98,
      "end": 534.06,
      "text": "更持久的改写我们的工作和产品",
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      "avg_logprob": -0.16404027717058048,
      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 534.06,
      "end": 537.64,
      "text": "因为Jeff输入是非常非常划算的",
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      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 537.64,
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      "text": "所以大量的自动化",
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      "no_speech_prob": 1.813044506193684e-11,
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    },
    {
      "start": 539.64,
      "end": 541.76,
      "text": "就会突然变得买得起",
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      "no_speech_prob": 1.813044506193684e-11,
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    {
      "start": 541.76,
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      "text": "说了那么多",
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    },
    {
      "start": 542.78,
      "end": 546.04,
      "text": "已经有人做了一个非常好的仓库",
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      "no_speech_prob": 1.331034414631116e-11,
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    {
      "start": 546.04,
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      "text": "是Orzen Type Safe",
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      "avg_logprob": -0.1413193464279175,
      "no_speech_prob": 1.331034414631116e-11,
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    {
      "start": 547.5,
      "end": 548.54,
      "text": "仓库里呢",
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    {
      "start": 548.54,
      "end": 549.88,
      "text": "有官方的资源",
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    },
    {
      "start": 549.88,
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      "text": "也有很多社区的项目",
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    {
      "start": 551.84,
      "end": 554.28,
      "text": "比如客户端库和集成",
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    {
      "start": 554.28,
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      "text": "Agent和开发者工具",
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    {
      "start": 556.08,
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      "text": "浏览器智能体",
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    {
      "start": 557.56,
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      "text": "机器人交互演示",
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    {
      "start": 559.38,
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      "text": "评测与独立研究等等",
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    {
      "start": 562.12,
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      "text": "非常非常多",
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    {
      "start": 563.52,
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      "text": "而Jeff呢",
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    },
    {
      "start": 564.48,
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      "text": "发布也才两天左右的时间而已",
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    {
      "start": 567.4,
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      "text": "我们使用Jeff呢",
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    {
      "start": 568.48,
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      "text": "也非常简单",
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    {
      "start": 569.4,
      "end": 571.66,
      "text": "进入他的控制台",
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    {
      "start": 571.66,
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      "text": "它有个Quick Start",
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    {
      "start": 572.92,
      "end": 575.42,
      "text": "然后我们可以copy这里的",
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 575.42,
      "end": 577.34,
      "text": "给Agent的提示词",
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    {
      "start": 577.34,
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      "text": "就可以在我们电脑上",
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 579.28,
      "end": 581.32,
      "text": "安装Type Safe的Skill",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 581.32,
      "end": 582.52,
      "text": "比如这里呢",
      "chunk": 1,
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 582.52,
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      "text": "我呢就调用它的Skill",
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      "no_speech_prob": 1.5797953223373185e-11,
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    },
    {
      "start": 584.58,
      "end": 587.12,
      "text": "然后让它帮我做一个",
      "chunk": 1,
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    },
    {
      "start": 587.12,
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      "text": "打游戏的Web页面",
      "chunk": 1,
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
      "compression_ratio": 1.298932384341637
    },
    {
      "start": 588.98,
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      "text": "JPT很快就帮我做出了这样一个游戏",
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    },
    {
      "start": 591.52,
      "end": 592.98,
      "text": "第一章呢",
      "chunk": 1,
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 592.98,
      "end": 595.3,
      "text": "我刚刚已经让Jeff已经游玩过了",
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      "avg_logprob": -0.1485152631192594,
      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 595.3,
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      "text": "我们先看一下这里的游戏指南",
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      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 597.84,
      "end": 599.9,
      "text": "可以让Jeff来玩",
      "chunk": 1,
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      "no_speech_prob": 1.5797953223373185e-11,
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    {
      "start": 599.9,
      "end": 601.6,
      "text": "也可以手动接管",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
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    {
      "start": 601.6,
      "end": 603.78,
      "text": "总共有三个章节",
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
      "compression_ratio": 1.1604477611940298
    },
    {
      "start": 603.78,
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      "text": "Choice它会显示后选动作的真实概率",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
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    },
    {
      "start": 607.66,
      "end": 610.58,
      "text": "自信度衡量分布的集中程度",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
      "compression_ratio": 1.1604477611940298
    },
    {
      "start": 610.58,
      "end": 615.34,
      "text": "Nord它是单独判断是否急需休息",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
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    {
      "start": 615.34,
      "end": 617.0,
      "text": "第一关已经打完了",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
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    {
      "start": 617.0,
      "end": 620.66,
      "text": "那现在我来点一下看一下第二关",
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    {
      "start": 620.66,
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      "text": "我们可以观察右侧Jeff的每一步",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
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    },
    {
      "start": 625.14,
      "end": 628.46,
      "text": "今天的这个视频我是没有做变速",
      "chunk": 1,
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      "avg_logprob": -0.140750161532698,
      "no_speech_prob": 1.526490739367503e-11,
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    {
      "start": 628.46,
      "end": 630.24,
      "text": "所以大家可以观察一下",
      "chunk": 1,
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      "avg_logprob": -0.14811393087224442,
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    {
      "start": 630.24,
      "end": 632.86,
      "text": "杰弗他的一个速度情况",
      "chunk": 1,
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      "avg_logprob": -0.14811393087224442,
      "no_speech_prob": 1.2510795351083903e-11,
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    {
      "start": 632.86,
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      "text": "现在来点击一下",
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    {
      "start": 634.44,
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      "text": "让他开始",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.14811393087224442,
      "no_speech_prob": 1.2510795351083903e-11,
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    {
      "start": 635.02,
      "end": 640.1,
      "text": "他开始收集到原木了",
      "chunk": 1,
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      "avg_logprob": -0.14811393087224442,
      "no_speech_prob": 1.2510795351083903e-11,
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    {
      "start": 640.1,
      "end": 641.46,
      "text": "有了原木之后",
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    },
    {
      "start": 641.46,
      "end": 643.08,
      "text": "这里的桥就可以搭建好了",
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      "avg_logprob": -0.14811393087224442,
      "no_speech_prob": 1.2510795351083903e-11,
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    {
      "start": 643.08,
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      "text": "学好之后",
      "chunk": 1,
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      "no_speech_prob": 1.2510795351083903e-11,
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    },
    {
      "start": 644.8,
      "end": 647.42,
      "text": "他就可以去获取对岸的胡萝卜",
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      "start": 647.42,
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      "text": "然后还有一个胡萝卜",
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      "text": "他还没收集好",
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      "start": 651.56,
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      "text": "所以他这里收集一下",
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      "compression_ratio": 1.4805194805194806
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    {
      "start": 652.8,
      "end": 655.4,
      "text": "再回到他的家",
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    {
      "start": 655.4,
      "end": 658.24,
      "text": "我可以把这里的蛋报呢",
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    {
      "start": 658.24,
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      "text": "进行保存",
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      "start": 658.94,
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      "text": "也就是说",
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    {
      "start": 660.14,
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      "text": "他会下载一个JSON文件",
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      "start": 662.04,
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      "text": "右侧我们会看到",
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    {
      "start": 663.44,
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      "text": "他的当前章节的目标",
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    {
      "start": 665.62,
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      "text": "这里的概率呢",
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    {
      "start": 667.08,
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      "text": "他就写的比较大",
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      "text": "所以兔子呢",
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      "text": "最后就回到引力去了",
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    {
      "start": 671.0,
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      "text": "在探险偏好里呢",
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      "start": 672.76,
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      "text": "也可以去选择一下",
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      "start": 674.72,
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      "text": "页面的下方",
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      "start": 675.92,
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      "text": "还可以看到他的冒险记录",
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      "start": 677.94,
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      "text": "还有他的休息的情况",
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      "start": 679.76,
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      "text": "我呢之前将第一个章节",
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    {
      "start": 681.74,
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      "text": "玩的一个战报",
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    {
      "start": 683.54,
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      "text": "然后下载了下来",
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    {
      "start": 685.58,
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      "text": "让AI介绍一下",
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      "start": 687.42,
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      "text": "他说呢",
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    {
      "start": 688.82,
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      "text": "回合",
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      "start": 690.46,
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      "text": "九回合",
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    {
      "start": 691.32,
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      "text": "结局胜利",
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    {
      "start": 692.68,
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      "text": "体力还剩37",
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    {
      "start": 695.2,
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      "text": "葛萝卜的话有五根",
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      "start": 697.14,
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      "text": "第一章节里面",
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      "start": 699.12,
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      "text": "它是没有木头的",
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    {
      "start": 700.86,
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      "text": "下方呢",
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    {
      "start": 701.56,
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      "text": "是兔子走过的路线",
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      "start": 703.32,
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      "text": "日志对应的是什么",
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      "start": 705.46,
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      "text": "决策记录里",
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    {
      "start": 706.54,
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      "text": "我们会看到",
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    {
      "start": 707.44,
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      "text": "用的是Jave的模型",
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      "start": 709.64,
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      "text": "然后第一步是比较慢",
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      "start": 711.64,
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      "text": "这和我当前的网络",
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      "start": 713.3,
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      "text": "当然也有很大关系",
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    {
      "start": 714.68,
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      "text": "后面的话快乐非常多",
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    {
      "start": 716.46,
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      "text": "大多数的致敬度呢",
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    {
      "start": 718.66,
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      "text": "在0.77到0.96",
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      "start": 720.74,
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      "text": "其中有两步",
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    {
      "start": 722.84,
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      "text": "有欲",
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    {
      "start": 723.5,
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      "text": "因为一开始这个桥呢",
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    {
      "start": 725.2,
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      "text": "没有修复好",
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      "start": 726.3,
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      "text": "所以",
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    {
      "start": 727.4,
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      "text": "Jeff呢就来回",
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    {
      "start": 729.36,
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      "text": "在这三个洪框的点",
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    {
      "start": 731.06,
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      "text": "这里来回折腾",
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    {
      "start": 732.3,
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      "text": "后来我就让Astra来修复了一下",
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    {
      "start": 735.46,
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      "text": "这个游戏",
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    {
      "start": 735.94,
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      "text": "现在我们再来到",
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    {
      "start": 737.12,
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      "text": "他的第三章节",
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    {
      "start": 738.56,
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      "text": "那我这里呢",
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    {
      "start": 739.76,
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      "text": "点击一下手动接管",
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    {
      "start": 741.74,
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      "text": "音效呢也打开了",
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      "start": 743.16,
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      "text": "那我点",
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    {
      "start": 744.48,
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      "text": "点一个",
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    {
      "start": 745.44,
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      "text": "比如说",
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    {
      "start": 746.22,
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      "text": "我这里先点了除菊小镜",
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    {
      "start": 748.3,
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      "text": "再点一个萤火炒坡",
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    {
      "start": 750.44,
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      "text": "然后我们会看到",
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      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
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    {
      "start": 752.94,
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      "text": "还有胡萝卜",
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    {
      "start": 754.0,
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      "text": "然后这里还有木头",
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    {
      "start": 755.74,
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      "text": "没有收集到",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
      "compression_ratio": 1.373134328358209
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    {
      "start": 756.66,
      "end": 760.72,
      "text": "那我再返回别的地方",
      "chunk": 1,
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    {
      "start": 760.72,
      "end": 761.56,
      "text": "点一下",
      "chunk": 1,
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      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
      "compression_ratio": 1.373134328358209
    },
    {
      "start": 761.56,
      "end": 764.78,
      "text": "这里收集到木头了",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
      "compression_ratio": 1.373134328358209
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    {
      "start": 764.78,
      "end": 766.98,
      "text": "再点一下",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
      "compression_ratio": 1.373134328358209
    },
    {
      "start": 766.98,
      "end": 769.14,
      "text": "他说等待修船",
      "chunk": 1,
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      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
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    {
      "start": 769.14,
      "end": 771.36,
      "text": "等等",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
      "compression_ratio": 1.373134328358209
    },
    {
      "start": 771.36,
      "end": 774.26,
      "text": "那再来让他单独来玩一下",
      "chunk": 1,
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      "no_speech_prob": 1.468774234181236e-11,
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    {
      "start": 774.26,
      "end": 775.28,
      "text": "看看他怎么玩",
      "chunk": 1,
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      "avg_logprob": -0.19731813513714333,
      "no_speech_prob": 1.468774234181236e-11,
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    {
      "start": 775.28,
      "end": 782.14,
      "text": "修好桥了",
      "chunk": 1,
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      "avg_logprob": -0.15599005562918528,
      "no_speech_prob": 9.292585798070796e-12,
      "compression_ratio": 1.2009803921568627
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    {
      "start": 782.14,
      "end": 783.54,
      "text": "然后再去取胡萝卜",
      "chunk": 1,
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      "no_speech_prob": 9.292585798070796e-12,
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    {
      "start": 783.54,
      "end": 785.1,
      "text": "又返回来",
      "chunk": 1,
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    {
      "start": 785.1,
      "end": 786.88,
      "text": "它要去取胡萝卜",
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    {
      "start": 786.88,
      "end": 792.24,
      "text": "因为这个设定里呢",
      "chunk": 1,
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      "compression_ratio": 1.2009803921568627
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    {
      "start": 792.24,
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      "text": "它还需要一个金种子",
      "chunk": 1,
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    {
      "start": 794.28,
      "end": 795.94,
      "text": "开启石门",
      "chunk": 1,
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      "no_speech_prob": 9.292585798070796e-12,
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    {
      "start": 795.94,
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      "text": "所以它最后是在右侧",
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    {
      "start": 798.32,
      "end": 800.52,
      "text": "游戏那里去结束的",
      "chunk": 1,
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    {
      "start": 800.52,
      "end": 802.72,
      "text": "最后呢再来看一个案例",
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    {
      "start": 802.72,
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      "text": "我呢让Astra做的一个页面",
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    {
      "start": 805.06,
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      "text": "外星人要到地球",
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    {
      "start": 806.68,
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      "text": "那要把外星人的奇怪发言",
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    {
      "start": 809.7,
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      "text": "变成代码执行的判断",
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    {
      "start": 811.86,
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      "text": "左边呢",
      "chunk": 1,
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    {
      "start": 813.78,
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      "text": "就会有非常多的",
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    {
      "start": 815.42,
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      "text": "待检的旅客",
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    {
      "start": 817.06,
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      "text": "总共是有24个",
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    {
      "start": 819.22,
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      "text": "他们呢",
      "chunk": 1,
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    {
      "start": 820.34,
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      "text": "长的是有三种样式",
      "chunk": 1,
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    {
      "start": 822.52,
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      "text": "名字有各个不同",
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    {
      "start": 824.58,
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      "text": "比如说这里的白闪博士",
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    {
      "start": 827.16,
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      "text": "他说旅客的原话",
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    {
      "start": 829.28,
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      "text": "是什么样子的",
      "chunk": 1,
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    {
      "start": 830.44,
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      "text": "那正常这种情况下",
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    {
      "start": 832.88,
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      "text": "他说他有简易放行证明",
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    {
      "start": 836.42,
      "end": 839.4,
      "text": "点击一下开始扫描",
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    {
      "start": 839.4,
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      "text": "肯定是让他去通过的",
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    {
      "start": 842.26,
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      "text": "Jeff这里呢",
      "chunk": 1,
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    {
      "start": 843.14,
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      "text": "他有三个判断",
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      "start": 844.56,
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      "text": "第一是Choice",
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    {
      "start": 845.7,
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      "text": "第二呢是No",
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    {
      "start": 848.0,
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      "text": "那对这样外星人呢",
      "chunk": 1,
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    {
      "start": 849.58,
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      "text": "我们就不需要过度的去关注他",
      "chunk": 1,
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      "compression_ratio": 1.2287822878228782
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    {
      "start": 851.78,
      "end": 855.06,
      "text": "然后下方就有一个欢迎雨",
      "chunk": 1,
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      "no_speech_prob": 1.2010781258453562e-11,
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    {
      "start": 855.06,
      "end": 856.36,
      "text": "欢迎来到地球",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.1352564966356432,
      "no_speech_prob": 1.2010781258453562e-11,
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    {
      "start": 856.36,
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      "text": "决策档案里呢",
      "chunk": 1,
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      "avg_logprob": -0.1352564966356432,
      "no_speech_prob": 1.2010781258453562e-11,
      "compression_ratio": 1.2287822878228782
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    {
      "start": 857.56,
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      "text": "就会显示刚刚做了那些决策",
      "chunk": 1,
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    {
      "start": 860.1,
      "end": 862.86,
      "text": "实测的实验室里呢",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.1352564966356432,
      "no_speech_prob": 1.2010781258453562e-11,
      "compression_ratio": 1.2287822878228782
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    {
      "start": 862.86,
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      "text": "这是之前跑过的一次例子",
      "chunk": 1,
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      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
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    {
      "start": 866.9,
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      "text": "这是24条人工编写的一个测试情境",
      "chunk": 1,
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      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
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    {
      "start": 870.38,
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      "text": "每条呢",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
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    {
      "start": 871.68,
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      "text": "向真实的Jeff来发送",
      "chunk": 1,
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      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
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    {
      "start": 873.94,
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      "text": "同一state下的三个独立问题",
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      "compression_ratio": 1.2552301255230125
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    {
      "start": 876.3,
      "end": 879.18,
      "text": "参考标签不会传给模型",
      "chunk": 1,
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      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
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    {
      "start": 879.18,
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      "text": "比如说",
      "chunk": 1,
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    {
      "start": 880.46,
      "end": 882.94,
      "text": "这里的参考通道啊",
      "chunk": 1,
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      "no_speech_prob": 1.5448628487568783e-11,
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    {
      "start": 882.94,
      "end": 884.44,
      "text": "是哪个",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
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    {
      "start": 884.44,
      "end": 886.92,
      "text": "那就不会发给Jeff",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
    },
    {
      "start": 886.92,
      "end": 888.38,
      "text": "通过这个测试呢",
      "chunk": 1,
      "language": "zh",
      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
    },
    {
      "start": 888.38,
      "end": 891.3,
      "text": "就可以比对人工写的参考信息",
      "chunk": 1,
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      "avg_logprob": -0.15637229919433593,
      "no_speech_prob": 1.5448628487568783e-11,
      "compression_ratio": 1.2552301255230125
    },
    {
      "start": 891.3,
      "end": 895.16,
      "text": "和GF判断了结果之间的一些差别",
      "chunk": 1,
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      "avg_logprob": -0.18052815168331832,
      "no_speech_prob": 1.2366607737845925e-11,
      "compression_ratio": 1.140495867768595
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    {
      "start": 895.16,
      "end": 897.92,
      "text": "最后的对照里面会说明他们的状态",
      "chunk": 1,
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      "no_speech_prob": 1.2366607737845925e-11,
      "compression_ratio": 1.140495867768595
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    {
      "start": 897.92,
      "end": 901.02,
      "text": "那我这里再点击一下重新实测",
      "chunk": 1,
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      "avg_logprob": -0.18052815168331832,
      "no_speech_prob": 1.2366607737845925e-11,
      "compression_ratio": 1.140495867768595
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    {
      "start": 901.02,
      "end": 905.18,
      "text": "我是开了最多的10号并发",
      "chunk": 1,
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      "avg_logprob": -0.18052815168331832,
      "no_speech_prob": 1.2366607737845925e-11,
      "compression_ratio": 1.140495867768595
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    {
      "start": 905.18,
      "end": 908.62,
      "text": "那我们可以看到它是成功完成",
      "chunk": 1,
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      "avg_logprob": -0.18052815168331832,
      "no_speech_prob": 1.2366607737845925e-11,
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    {
      "start": 908.62,
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      "text": "参考是有91%",
      "chunk": 1,
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      "text": "以上就是今天介绍Jeff的所有内容",
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