{
  "text": "Jeff到處都是,而且是我最近見過最讓人興奮的AI。他真的很像早期的ChagPT。那時候我們面對的是一個特別強大也很原始的東西。大家都在想怎麼把它用到極致。所以今天我想講的不只是Jeff是什麼,還想講怎麼用它。怎麼理解它,它擅長什麼,不擅長什麼。然後我還準備了一堆別人已經用Jeff做出來的演示。\n好 先来说说Jeff是什么\nJeff是几天前刚发布的\n他是一种新的AR\n本质上就是一个非常厉害的决策器\n但不止如此\n真正让他与众不同的是\n他能非常快\n而且非常便宜地做出成千上万\n甚至几十万\n几百万个决策\n如果这些听起来还是很抽象\n那先别走\n我会给你一些具体细节\n讲讲这东西到底能做什么\n好\n这里有一个GIF的最基础例子\n你会把问题整理成GS1\n指令或者说Prompt\n就是热狗算三明治吗\n然后你再给他一些判断标准\n告诉他该怎么想\n怎么判断他到底算不算三明治\n然后这里我们还能继续往下问\n什么是实物\n接着就会得到他的定义\n所以综合这些来看的话\n如果我们运行它\n像热狗算三明治吗\n这样的判断73%结果为致\n也就是说在这里他会判断为致\nJust在你能清楚描述自己想做什么决策\n能提供很明确的上下文和结构化问题时特别好用\n如果这些条件都满足\nJust对你的使用场景会非常强大\n但他也有不擅长的地方\n比如他不是文本生成模型\n你不能随便丢给他一个不结构化的问题\n然后指望他直接给你答案\n比如\n你不会拿他来问我该怎么跟老板谈这件事的建议\n他不是这么工作的\n你不会让他帮你写代码\n因为他写代码没那么强\n但他很适合做一件很酷的事\n如果你有一个很大的前端\nUI素材库\n想动态生成前端\n他其实可以从这个UI库里挑选组件\n帮你拼出整个网页\n前提是你得先有一堆他能选的按钮\n一堆他能选的输入框\n还有字体和其他元素\n这样他就能在不到一秒的时间里\n帮你拼出一个很厉害的网站\n所以如果你让Jeff和Fable下棋\nFable会赢\n不过要是给下棋加上时间限制\nJeff大概率会赢\n因为Fable处理每一步都太慢了\n而Jeff几乎可以立刻做决定\n很可能是这样\n虽然如果没有时间限制\nJeff本来赢不了这局\n因为Fable会先耗尽时间\n但加上时间限制后\nJeff就能赢\n先看第一个例子\n它是个挺好用的AI文案检测器\n如果你觉得某个网站\n或者某种创意写作是AI写的\n可以让Jeff帮你检测\n还有个网站叫MadeWithJV.com\n上面有很多用Jeff做出来的库东西和演示\n我这一次就是从那里找的\n我们看了anthropic.com\n它显示有26%是AI swap\n基本上是手工写的\n主要还是人写的\n但里面确实有点AI味\n这也不奇怪\n至少可以肯定\n他们确实用了Cloud模型来帮忙写一部分内容\n而且他会具体拆解自己在看什么\n以及为什么判断某一部分是\n这又是Jab的一个超棒应用场景\n我真不明白这段为什么没有更火\n他只拿了三\n六万次观看\n不过这是Kissy做的\n叫Unclutter\n是一个和Jab搭配使用的智能广告和弹窗拦截器\n它几乎是瞬间生效\n而且你也能看到它的效果特别好\n你自己接入密钥\n基本上也就是几乎免费\n我得先顺便说一下价格\nJeff的收费是每百万输入\nToken 4.2美分\n输出Token免费\n输出Token数量不限完全免费\n所以当你打开一个网站时\n实际发生的事\n他会把所有元素连同一段说明一起发给Jeff\n告诉他怎么判断什么东西算垃圾信息\n或者烦人的内容\nJeff会做出判断\n然后把这些元素全部移除掉\n所以很简单也很酷\n下一个其实就是这期视频的赞助商\nSapir\n我已经和他们合作有一段时间了\n他们已经把Jeff加进了Zack平台\n所以如果你在做任何类型的自动化\n都可以直接在工作流里用Jeff来帮你做判断\n比如我们来新建一个Workflow\n然后往下到Actions这里\n搜索Jeff就会看到他\nTouch Jeff\n现在你可以把它当成Zapir里的一个APP来用\n这样你就能把它和Zapir\n以集成的九千多个APP里的任意一个连接起来\n用不同方式组合\n让Jeff来决定这些连接怎么执行\n比如我可以说\n每次收到新的日历邀请\n就让Jeff决定我要不要接受\n我会给他一堆判断标准\n然后他就会自动接受或者拒绝\n很明显\n这只是个很简单的例子\n但你可以利用Zepier提供的9000多个APP做得更复杂\n这是我见过Jeff和Zepconnect2026里最酷的一个用法\n那场年度大会刚刚结束\n想看NextGZeph和Jeff能做什么\n可以点下面我的链接\n好了\n下面是Jeff另一个很厉害的例子\n一般邮箱客户端都是按时间顺序排序\n也就是最新收到的邮件会排在前面\n我以前还在Grogbit里做过工具\n帮我优先处理该回复的邮件\n但Jeff基本能瞬间做到\n他可以根据自己判断的回复优先级\n把成千上万封邮件排好去\n这就是他刚做的这个功能\n一百封邮件不到半秒就排完了\n再来一个很实用的例子\n你知道浏览器里的页面查找吧\n比如我随便输入一段文字\n再输入Find\n它就会\n高亮这些词\n我一直在用这个功能\n超级实用\n但它是基于关键词匹配的\n所以如果你输入的内容不在页面上\n就不会显示出来\nGoogle一位产品经理\n做了一个模糊搜索版本\n一般这种东西会很慢\n但现在快得惊人\n你只要输入\n想在页面里找的东西\n不用完全一致\n差不多把你要找的内容打出来\n它不擅长写代码\n但如果你有一套预先配置好的UI元素库\n它其实能很快动态帮你搭出一个网页\n我的意思是左边是页面渲染\n右边是Jazz在实时动态生成\n你看这速度有多快\n它基本会根据用户想找什么\n来决定网站改长什么样\n要不要表单\n需要哪些信息\n要不要登录\n我们这里看到的就是这个过程\n整个过程非常快\n不过\n它不是从零开始搭建的\n只是在一堆不同的UI元素里做选择\n再把它们以正确的方式组合起来\n好\n接下来这个我们可能很快就会用上\n这是一个例子\nJeff把一段90多分钟的视频\n在不到两秒的时间里\n根据你输入的内容\n剪成了多个片段\n看\n这就是个例子\n叫TripFast\n你输入YRL Works\n它就会扫描整段视频\n可能还会看字幕\n然后找出所有对应的片段\n立刻帮你剪好\n之后点一下就能直接下载\n特别方便\n我觉得这种场景正是速度真正带来的价值\n好\n我还剩两个\n而且不一定都得特别有价值\n有时候只要够酷\n看着爽就行\n给你看个例子\n这是Jeff在理解配色方案\n你真的可以随便输入任何东西\n他都会把它认为对应的配色方案拼出来\n比如80sdisco80spopretro\n这是browser像是什么样的\n浏览器看起来就是这样\nBowser看起来是这样\n这里是Morio\n这里是LouisG\nWarrior\n他知道这些知识实体分别对应什么颜色\n这里有蓝屏死机\nMatrix\n海滩\n真的很酷\n就是个超棒的演示\n最后底部有一堆emoji\n你只要开始输入任何内容\n它就会判断哪些emoji和你输入的内容最相关\n比如我这里想减肥\n当然就会出现健康食物的emoji\n再比如组个乐队\n瞧乐器就出来了\n所以这功能有点有趣\n古怪又简单\n但我觉得真的很酷\n去看看Jeff吧\n赶紧用起来吧,几乎是免费的。\n他们一开始会送你五美元额度,而且拿来随便折腾。\n看看能做到什么,真的特别有意思。\n希望这些例子能给你一些启发,去做点自己的东西。\n我还另外做了一期视频,详细讲了Jeff到底能做什么。\n他是什么,也可以去看看。",
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      "end": 23.22,
      "text": "Jeff到處都是,而且是我最近見過最讓人興奮的AI。他真的很像早期的ChagPT。那時候我們面對的是一個特別強大也很原始的東西。大家都在想怎麼把它用到極致。所以今天我想講的不只是Jeff是什麼,還想講怎麼用它。怎麼理解它,它擅長什麼,不擅長什麼。然後我還準備了一堆別人已經用Jeff做出來的演示。",
      "chunk": 0,
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      "end": 31.78,
      "text": "好 先来说说Jeff是什么",
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      "end": 34.3,
      "text": "Jeff是几天前刚发布的",
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      "text": "他是一种新的AR",
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      "text": "本质上就是一个非常厉害的决策器",
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      "text": "但不止如此",
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      "start": 42.42,
      "end": 44.48,
      "text": "真正让他与众不同的是",
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      "start": 44.48,
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      "text": "他能非常快",
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      "start": 45.92,
      "end": 49.56,
      "text": "而且非常便宜地做出成千上万",
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      "start": 49.56,
      "end": 50.84,
      "text": "甚至几十万",
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    {
      "start": 50.84,
      "end": 53.1,
      "text": "几百万个决策",
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      "start": 53.1,
      "end": 55.68,
      "text": "如果这些听起来还是很抽象",
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      "start": 55.68,
      "end": 56.52,
      "text": "那先别走",
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    {
      "start": 56.52,
      "end": 58.8,
      "text": "我会给你一些具体细节",
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      "start": 58.8,
      "end": 60.82,
      "text": "讲讲这东西到底能做什么",
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      "start": 60.82,
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      "text": "好",
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      "start": 61.92,
      "end": 64.44,
      "text": "这里有一个GIF的最基础例子",
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      "start": 64.44,
      "end": 71.16,
      "text": "你会把问题整理成GS1",
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      "start": 71.16,
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      "text": "指令或者说Prompt",
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    {
      "start": 79.4,
      "end": 81.3,
      "text": "就是热狗算三明治吗",
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    {
      "start": 81.3,
      "end": 84.12,
      "text": "然后你再给他一些判断标准",
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      "no_speech_prob": 6.699206727550644e-12,
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    {
      "start": 84.12,
      "end": 92.62,
      "text": "告诉他该怎么想",
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    {
      "start": 92.62,
      "end": 95.36,
      "text": "怎么判断他到底算不算三明治",
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    {
      "start": 95.36,
      "end": 104.38,
      "text": "然后这里我们还能继续往下问",
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      "no_speech_prob": 6.699206727550644e-12,
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    {
      "start": 104.38,
      "end": 105.28,
      "text": "什么是实物",
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    {
      "start": 105.28,
      "end": 107.28,
      "text": "接着就会得到他的定义",
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    {
      "start": 107.28,
      "end": 109.76,
      "text": "所以综合这些来看的话",
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    {
      "start": 109.76,
      "end": 111.1,
      "text": "如果我们运行它",
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    {
      "start": 111.1,
      "end": 113.22,
      "text": "像热狗算三明治吗",
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      "avg_logprob": -0.1296664084157636,
      "no_speech_prob": 1.2416555630889725e-11,
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    {
      "start": 113.22,
      "end": 115.78,
      "text": "这样的判断73%结果为致",
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      "no_speech_prob": 1.2416555630889725e-11,
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    {
      "start": 115.78,
      "end": 118.74,
      "text": "也就是说在这里他会判断为致",
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    {
      "start": 118.74,
      "end": 122.24,
      "text": "Just在你能清楚描述自己想做什么决策",
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      "no_speech_prob": 1.2416555630889725e-11,
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    {
      "start": 122.24,
      "end": 126.76,
      "text": "能提供很明确的上下文和结构化问题时特别好用",
      "chunk": 0,
      "language": "zh",
      "avg_logprob": -0.1296664084157636,
      "no_speech_prob": 1.2416555630889725e-11,
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    {
      "start": 126.76,
      "end": 128.96,
      "text": "如果这些条件都满足",
      "chunk": 0,
      "language": "zh",
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    {
      "start": 128.96,
      "end": 131.54,
      "text": "Just对你的使用场景会非常强大",
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      "text": "但他也有不擅长的地方",
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      "text": "比如他不是文本生成模型",
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      "text": "你不能随便丢给他一个不结构化的问题",
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      "start": 141.1,
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      "text": "然后指望他直接给你答案",
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      "start": 143.64,
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      "text": "你不会拿他来问我该怎么跟老板谈这件事的建议",
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      "start": 148.36,
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      "text": "他不是这么工作的",
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      "text": "你不会让他帮你写代码",
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      "start": 152.98,
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      "text": "因为他写代码没那么强",
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      "start": 154.98,
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      "text": "但他很适合做一件很酷的事",
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      "text": "如果你有一个很大的前端",
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      "start": 160.54,
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      "text": "UI素材库",
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      "start": 161.68,
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      "text": "想动态生成前端",
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      "text": "他其实可以从这个UI库里挑选组件",
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    {
      "start": 167.12,
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      "text": "帮你拼出整个网页",
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      "start": 168.86,
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      "text": "前提是你得先有一堆他能选的按钮",
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      "text": "一堆他能选的输入框",
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      "start": 174.96,
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      "text": "还有字体和其他元素",
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      "start": 176.94,
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      "text": "这样他就能在不到一秒的时间里",
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      "start": 180.2,
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      "text": "帮你拼出一个很厉害的网站",
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      "text": "所以如果你让Jeff和Fable下棋",
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      "text": "Fable会赢",
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      "text": "不过要是给下棋加上时间限制",
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      "start": 190.76,
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      "text": "Jeff大概率会赢",
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      "text": "因为Fable处理每一步都太慢了",
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      "start": 195.8,
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      "text": "而Jeff几乎可以立刻做决定",
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      "start": 198.96,
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      "text": "很可能是这样",
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      "start": 200.74,
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      "text": "虽然如果没有时间限制",
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      "text": "Jeff本来赢不了这局",
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      "text": "因为Fable会先耗尽时间",
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      "text": "Jeff就能赢",
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      "text": "先看第一个例子",
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      "text": "它是个挺好用的AI文案检测器",
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      "text": "如果你觉得某个网站",
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      "text": "或者某种创意写作是AI写的",
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      "text": "可以让Jeff帮你检测",
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      "text": "还有个网站叫MadeWithJV.com",
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      "text": "上面有很多用Jeff做出来的库东西和演示",
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      "start": 227.28,
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      "text": "我这一次就是从那里找的",
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      "text": "我们看了anthropic.com",
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      "text": "它显示有26%是AI swap",
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      "text": "基本上是手工写的",
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      "text": "主要还是人写的",
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      "start": 238.12,
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      "text": "但里面确实有点AI味",
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      "start": 240.16,
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      "text": "这也不奇怪",
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      "text": "至少可以肯定",
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      "start": 243.26,
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      "text": "他们确实用了Cloud模型来帮忙写一部分内容",
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      "start": 246.68,
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      "text": "而且他会具体拆解自己在看什么",
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      "start": 249.44,
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      "text": "以及为什么判断某一部分是",
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      "start": 251.18,
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      "text": "这又是Jab的一个超棒应用场景",
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      "start": 254.5,
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      "text": "我真不明白这段为什么没有更火",
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      "start": 258.1,
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      "text": "他只拿了三",
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      "start": 259.3,
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      "text": "六万次观看",
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      "text": "不过这是Kissy做的",
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    {
      "start": 263.72,
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      "text": "叫Unclutter",
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    {
      "start": 264.54,
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      "text": "是一个和Jab搭配使用的智能广告和弹窗拦截器",
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      "text": "它几乎是瞬间生效",
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      "start": 271.94,
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      "text": "而且你也能看到它的效果特别好",
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      "text": "你自己接入密钥",
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      "start": 277.26,
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      "text": "基本上也就是几乎免费",
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      "start": 279.16,
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      "text": "我得先顺便说一下价格",
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      "text": "Jeff的收费是每百万输入",
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      "text": "Token 4.2美分",
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    {
      "start": 285.7,
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      "text": "输出Token免费",
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      "avg_logprob": -0.12922888887142706,
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    {
      "start": 287.38,
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      "text": "输出Token数量不限完全免费",
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      "avg_logprob": -0.12922888887142706,
      "no_speech_prob": 1.0743656832234993e-11,
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      "start": 290.16,
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      "text": "所以当你打开一个网站时",
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    {
      "start": 292.88,
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      "text": "实际发生的事",
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    {
      "start": 293.8,
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      "text": "他会把所有元素连同一段说明一起发给Jeff",
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    {
      "start": 297.08,
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      "text": "告诉他怎么判断什么东西算垃圾信息",
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    {
      "start": 299.88,
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      "text": "或者烦人的内容",
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      "start": 300.94,
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      "text": "Jeff会做出判断",
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    {
      "start": 303.12,
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      "text": "然后把这些元素全部移除掉",
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      "start": 305.68,
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      "text": "所以很简单也很酷",
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    {
      "start": 308.56,
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      "text": "下一个其实就是这期视频的赞助商",
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      "start": 312.2,
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      "text": "Sapir",
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      "start": 313.48,
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      "text": "我已经和他们合作有一段时间了",
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      "start": 317.24,
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      "text": "他们已经把Jeff加进了Zack平台",
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      "start": 320.28,
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      "text": "所以如果你在做任何类型的自动化",
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      "start": 324.04,
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      "text": "都可以直接在工作流里用Jeff来帮你做判断",
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      "start": 328.34,
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      "text": "比如我们来新建一个Workflow",
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      "start": 331.68,
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      "text": "然后往下到Actions这里",
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    {
      "start": 334.32,
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      "text": "搜索Jeff就会看到他",
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    {
      "start": 336.54,
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      "text": "Touch Jeff",
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      "start": 338.08,
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      "text": "现在你可以把它当成Zapir里的一个APP来用",
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      "start": 342.36,
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      "text": "这样你就能把它和Zapir",
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    {
      "start": 344.92,
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      "text": "以集成的九千多个APP里的任意一个连接起来",
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    {
      "start": 348.38,
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      "text": "用不同方式组合",
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    {
      "start": 350.46,
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      "text": "让Jeff来决定这些连接怎么执行",
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    {
      "start": 355.08,
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      "text": "每次收到新的日历邀请",
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      "start": 357.24,
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      "text": "就让Jeff决定我要不要接受",
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    {
      "start": 359.96,
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      "text": "我会给他一堆判断标准",
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    {
      "start": 362.32,
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      "text": "然后他就会自动接受或者拒绝",
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      "start": 366.96,
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      "text": "很明显",
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    {
      "start": 367.84,
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      "text": "这只是个很简单的例子",
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      "start": 370.06,
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      "text": "但你可以利用Zepier提供的9000多个APP做得更复杂",
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      "start": 373.68,
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      "text": "这是我见过Jeff和Zepconnect2026里最酷的一个用法",
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    {
      "start": 378.72,
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      "text": "那场年度大会刚刚结束",
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      "start": 381.38,
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      "text": "想看NextGZeph和Jeff能做什么",
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    {
      "start": 384.7,
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      "text": "可以点下面我的链接",
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    {
      "start": 386.32,
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      "text": "好了",
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    {
      "start": 387.5,
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      "text": "下面是Jeff另一个很厉害的例子",
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    {
      "start": 389.92,
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      "text": "一般邮箱客户端都是按时间顺序排序",
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    {
      "start": 393.26,
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      "text": "也就是最新收到的邮件会排在前面",
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    {
      "start": 396.64,
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      "text": "我以前还在Grogbit里做过工具",
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    {
      "start": 399.78,
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      "text": "帮我优先处理该回复的邮件",
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      "start": 404.9,
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    {
      "start": 408.22,
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      "text": "把成千上万封邮件排好去",
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    {
      "start": 410.88,
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      "text": "这就是他刚做的这个功能",
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    {
      "start": 413.22,
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      "text": "一百封邮件不到半秒就排完了",
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    {
      "start": 416.18,
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      "text": "再来一个很实用的例子",
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      "text": "你知道浏览器里的页面查找吧",
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    {
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      "text": "比如我随便输入一段文字",
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      "start": 425.42,
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      "text": "再输入Find",
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      "start": 426.44,
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      "text": "它就会",
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    {
      "start": 427.22,
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      "text": "高亮这些词",
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      "start": 428.98,
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      "text": "我一直在用这个功能",
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      "start": 430.86,
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      "text": "超级实用",
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    {
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      "text": "但它是基于关键词匹配的",
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    {
      "start": 434.52,
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      "text": "所以如果你输入的内容不在页面上",
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    {
      "start": 437.88,
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      "text": "就不会显示出来",
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    {
      "start": 439.3,
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      "text": "Google一位产品经理",
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    {
      "start": 441.66,
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      "text": "做了一个模糊搜索版本",
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      "start": 443.6,
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      "text": "一般这种东西会很慢",
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    {
      "start": 446.22,
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      "text": "但现在快得惊人",
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      "start": 447.78,
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      "text": "你只要输入",
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      "start": 449.62,
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      "text": "想在页面里找的东西",
      "chunk": 0,
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      "avg_logprob": -0.1272521424137689,
      "no_speech_prob": 1.3265208376189719e-11,
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    {
      "start": 451.3,
      "end": 452.7,
      "text": "不用完全一致",
      "chunk": 0,
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      "avg_logprob": -0.1272521424137689,
      "no_speech_prob": 1.3265208376189719e-11,
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    {
      "start": 452.7,
      "end": 455.76,
      "text": "差不多把你要找的内容打出来",
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      "language": "zh",
      "avg_logprob": -0.1272521424137689,
      "no_speech_prob": 1.3265208376189719e-11,
      "compression_ratio": 1.2872340425531914
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    {
      "start": 469.33,
      "end": 471.27,
      "text": "它不擅长写代码",
      "chunk": 1,
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      "avg_logprob": -0.1281320737755817,
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      "compression_ratio": 1.2201492537313432
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    {
      "start": 471.27,
      "end": 475.59,
      "text": "但如果你有一套预先配置好的UI元素库",
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      "avg_logprob": -0.1281320737755817,
      "no_speech_prob": 1.1039151363856359e-11,
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    {
      "start": 475.59,
      "end": 479.49,
      "text": "它其实能很快动态帮你搭出一个网页",
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      "avg_logprob": -0.1281320737755817,
      "no_speech_prob": 1.1039151363856359e-11,
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    {
      "start": 479.49,
      "end": 482.63,
      "text": "我的意思是左边是页面渲染",
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      "no_speech_prob": 1.1039151363856359e-11,
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    {
      "start": 482.63,
      "end": 485.71,
      "text": "右边是Jazz在实时动态生成",
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      "avg_logprob": -0.1281320737755817,
      "no_speech_prob": 1.1039151363856359e-11,
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    {
      "start": 485.71,
      "end": 487.77,
      "text": "你看这速度有多快",
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    {
      "start": 487.77,
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      "text": "它基本会根据用户想找什么",
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      "no_speech_prob": 1.1039151363856359e-11,
      "compression_ratio": 1.2201492537313432
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    {
      "start": 490.81,
      "end": 492.85,
      "text": "来决定网站改长什么样",
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      "avg_logprob": -0.1281320737755817,
      "no_speech_prob": 1.1039151363856359e-11,
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    {
      "start": 492.85,
      "end": 494.65,
      "text": "要不要表单",
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    {
      "start": 494.65,
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      "text": "需要哪些信息",
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    {
      "start": 496.23,
      "end": 497.57,
      "text": "要不要登录",
      "chunk": 1,
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    {
      "start": 497.57,
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      "text": "我们这里看到的就是这个过程",
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      "start": 500.43,
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      "text": "整个过程非常快",
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    {
      "start": 502.15,
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      "text": "不过",
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    {
      "start": 502.95,
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      "text": "它不是从零开始搭建的",
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    {
      "start": 505.59,
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      "text": "只是在一堆不同的UI元素里做选择",
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    {
      "start": 509.09,
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      "text": "再把它们以正确的方式组合起来",
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    {
      "start": 512.61,
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      "text": "好",
      "chunk": 1,
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      "avg_logprob": -0.17458342208343297,
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    {
      "start": 513.65,
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      "text": "接下来这个我们可能很快就会用上",
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    {
      "start": 516.07,
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      "text": "这是一个例子",
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      "text": "Jeff把一段90多分钟的视频",
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      "start": 520.53,
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      "text": "在不到两秒的时间里",
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    {
      "start": 522.37,
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      "text": "根据你输入的内容",
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    {
      "start": 524.37,
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      "text": "剪成了多个片段",
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    {
      "start": 525.65,
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      "text": "看",
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    {
      "start": 526.23,
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      "text": "这就是个例子",
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    {
      "start": 527.57,
      "end": 529.11,
      "text": "叫TripFast",
      "chunk": 1,
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      "start": 529.11,
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      "text": "你输入YRL Works",
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      "start": 530.83,
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      "text": "它就会扫描整段视频",
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    {
      "start": 532.45,
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      "text": "可能还会看字幕",
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    {
      "start": 534.43,
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      "text": "然后找出所有对应的片段",
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    {
      "start": 536.33,
      "end": 538.19,
      "text": "立刻帮你剪好",
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    {
      "start": 538.19,
      "end": 540.37,
      "text": "之后点一下就能直接下载",
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    {
      "start": 540.37,
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      "text": "特别方便",
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    {
      "start": 541.33,
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      "text": "我觉得这种场景正是速度真正带来的价值",
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      "start": 545.51,
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      "text": "好",
      "chunk": 1,
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      "avg_logprob": -0.14121736454058298,
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    {
      "start": 546.51,
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      "text": "我还剩两个",
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    {
      "start": 547.53,
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      "text": "而且不一定都得特别有价值",
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    {
      "start": 549.59,
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      "text": "有时候只要够酷",
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    {
      "start": 551.31,
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      "text": "看着爽就行",
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    {
      "start": 552.35,
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      "text": "给你看个例子",
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      "start": 553.61,
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      "text": "这是Jeff在理解配色方案",
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    {
      "start": 555.79,
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      "text": "你真的可以随便输入任何东西",
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      "start": 558.17,
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      "text": "他都会把它认为对应的配色方案拼出来",
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    {
      "start": 561.03,
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      "text": "比如80sdisco80spopretro",
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    {
      "start": 564.57,
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      "text": "这是browser像是什么样的",
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    {
      "start": 567.51,
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      "text": "浏览器看起来就是这样",
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    {
      "start": 569.97,
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      "text": "Bowser看起来是这样",
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    {
      "start": 572.17,
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      "text": "这里是Morio",
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    {
      "start": 574.13,
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      "text": "这里是LouisG",
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    {
      "start": 575.59,
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      "text": "Warrior",
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    {
      "start": 576.17,
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      "text": "他知道这些知识实体分别对应什么颜色",
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    {
      "start": 580.47,
      "end": 582.51,
      "text": "这里有蓝屏死机",
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    {
      "start": 582.51,
      "end": 583.27,
      "text": "Matrix",
      "chunk": 1,
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    {
      "start": 583.27,
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      "text": "海滩",
      "chunk": 1,
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    {
      "start": 583.95,
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      "text": "真的很酷",
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    {
      "start": 585.37,
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      "text": "就是个超棒的演示",
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    {
      "start": 587.77,
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      "text": "最后底部有一堆emoji",
      "chunk": 1,
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      "avg_logprob": -0.11413778577532087,
      "no_speech_prob": 1.090698972111559e-11,
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    {
      "start": 590.71,
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      "text": "你只要开始输入任何内容",
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    {
      "start": 593.31,
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      "text": "它就会判断哪些emoji和你输入的内容最相关",
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      "avg_logprob": -0.11413778577532087,
      "no_speech_prob": 1.090698972111559e-11,
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    {
      "start": 597.93,
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      "text": "比如我这里想减肥",
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    {
      "start": 600.33,
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      "text": "当然就会出现健康食物的emoji",
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      "no_speech_prob": 1.090698972111559e-11,
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    {
      "start": 603.13,
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      "text": "再比如组个乐队",
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      "text": "去看看Jeff吧",
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      "text": "赶紧用起来吧,几乎是免费的。",
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      "text": "他们一开始会送你五美元额度,而且拿来随便折腾。",
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      "text": "希望这些例子能给你一些启发,去做点自己的东西。",
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    "global_repeat_text": "Jeff到處都是,而且是我最近見過最讓人興奮的AI。他真的很像早期的ChagPT。那時候我們面對的是一個特別強大也很原始的東西。大家都在想怎麼把它用到極致。所以今天我想講的不只是Jeff是什麼,還想講怎麼用它。怎麼理解它,它擅長什麼,不擅長什麼。然後我還準備了一堆別人已經用Jeff做出來的演示。",
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