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  "text": "大家,這兩天非常熱門的模型是Jer。那這個模型呢,非常有意思。它不能對話,不能寫代碼,也不能識別圖片。它唯一能做的事情就是幫你去做選擇。那本期視頻就給大家來了解一下這一款熱門的決策型模型Jer。其實當我看到這個模型的時候,我也非常詫異。一款不能對話,也不能寫代碼,也不能識別圖片的模型到底有什麼用呢?當我看了官網的例子和外網的一些例子之後,我發現這款模型真的非常有用。\n因為其實不管是你在工作還是生活中,非常非常多的時候是需要決策的。如果我們用其他的模型,比如說CHALEJPT,或者是Cloud模型去做這種決策的話,推理的成本是非常高的。\n反應的時間也不會特別快,相當於你用大炮打了一個蚊子。那麼Jer這個模型呢,就是專門幹決策。那我們先用一個非常通俗的例子來理解一下Jer這個模型的輸入和輸出。\n那麼我們如果要用Jer這個模型的話,需要提供兩個東西。一個叫背景知識。這是我的理解。背景知識就是你要讓他做決定的話,你肯定要提供一些背景知識給他。\n然後就是問題,你的問題是什麼?發個Jer。那Jer就會做出選擇。然後你拿到這個選擇之後,再去走其他的流程。\n所以從這個大的這個流程裡面,我們能知道Jer是一個中間環節。就你可能這是你的一個工作流。那麼Jer只是起到一個中間路由,或者是中間判斷的一個過程。\n那麼他的選擇呢支持三種選擇。那第一種就是啊,我們可以認為叫做yes or no。\n我們用一個例子來解決定。比如說,小明的歲月成績考了60分。小明的父母是比較溫和的。但是如果他分數低於及格線的話,也會很生氣。\n那麼我們的背景知識就是這個。那我們的問題,那第一種回復的方式。問題是,父母會生氣嗎?那發給這個Jer。\n那Jer就會反過一個這樣的概率。會的概率是10%,那麼不會的概率是90%,那麼你就知道父母是不會生氣的。\n那這種就是Jer的第一種選擇方式。那麼你要告訴我,你在,要用這個Jer就是大摩寫生說,你要告訴他用的是哪一種。\n那第二種就是我們應該用的最多的,就是選項。還是一樣。但是問題就變成了,父母最可能如何回應小明這次考試。\n那麼你給出四個選項。A,表揚小明。B,溫和的鼓勵。三,認真的溝通。D,明顯生氣或嚴厲批評。那發給這個Jer。\n那Jer就給每個選項一個評分。那麼你從評分裡面能看到,是0.55。那C這個選項是最有可能的。\n認真溝通學習問題保持冷靜。那麼你就得到了一個最有可能的這個結果。\n最有可能的結果。那這個是第二種。第二種我覺得是在現實場面中用的最多的。\n那最後一個就是評分式的。那這種方式比如說,這個問題就變成了,父母對這次考試成績會有多不高興。\n你看這個問題就變成了一個分數的一個判斷。就是你有多大力度去這個選項。\n比如說A是基本滿意。沒有明顯不高興。B是略有失望。C是明顯不滿意。D呢非常生氣。\n那他的這個生氣的力度是在增加的。那你發給J5,J5會給到一個ABCD的相似投票一樣。\n那麼我們可以看到這個他的回答。B0.6現在得了65票。也就是說。\n那越有失望。讓態度溫和的概率是最高的。那這個時候。\n那你就可以根據他的評分的不同。去做下一步的選項。\n所以通過這三個選項的處理啊。還有這個場景啊。我們大概網上裡面就有一個概念了。\n那J5其實做最大的事情就是。你給他變成知識。你給他問題。給他選項。或者讓他回答yes or no。\n或者讓他去打一個分數。他其實最大的作用就是這個。幫你去做決策的參考。\n那很多人可能到這裡的時候。會覺得為什麼我們不用模型。去做這種決策的參考呢。\n那其實模型也可以做這種決策的參考。但是他Token的推理成本就高。\n那他小型速度可能不會很快。那比如說J5他的小型時間是100毫秒左右。\n成本是100萬Token。只要0.042美元。輸出完全免費。所以呢。\n這也就決定了J5這個模型。只能是成為你眾多工作流的一個部分。\n某些很多細分場景的模型的使用。它是不可能取代像Cloud。\n或JPT這些通用模型的。那麼這裡有一個案例可以讓大家進一步去了解。\nJ5這個模型和其他大模型怎麼配合。比如說。\n你在你的這個A型工具裡面做了一個模型的路由。\n簡單的任務用便宜的模型。复杂的任務用好的模型。\n那怎麼去判斷這個任務的。复杂、簡單。\n那麼這個就可以交給J5去判斷。\n那他的判斷成本是非常低的。\n他判斷完了之後。然後再路由到這個模型裡面去。\n再接著往下走。所以他就成為你A型的裡面的。\n某個環節裡面的一部分了。\n那麼在這裡來我也做了一個。用J5來玩這個。\n然後用J5去做這種選項的判斷。\n因為俄羅斯方塊只要控制方向就行了。\n我們來看一下。\n那這邊的話會接收俄羅斯方塊的這種做標信息。\n然後他這邊會返回。\n應該是怎麼操作。\n返回的指令裡面是包括了他的操作方向。\n那麼J5的這個判斷的準確率。\n也不是說是100%。大概在五六成左右。\n這個可能需要模型去疊代。\n然後你用其他的大模型其實也可以玩。\n但是成本和速度可能是沒有這個J5更快。\n更省成本。\n那這個想像速度是非常快的。\n那官網這邊提供了非常多的案例。\n比如說像這種模型路由啊。\n還有這種客戶的這種處理。\n客戶支持的處理。\n保險理賠。\n法律合規。\n那麼我在外網上也是有一個很多。\n比如說這種去除流氧器廣告。\n把整個流氧器的道路信息發送給J5。\n讓J5去判斷哪個是廣告。\n並且消除。\n還有這種郵件欺詐的。\n就是說把所有的郵件和相關的背景信息發給J5。\n讓J5去判斷哪些郵件的欺詐。\n那還有這個非常有意思的是什麼呢?\n它是用J5做了一個Cloud的插件。\n來判斷一下Cloud有沒有調用不必要的工具。\n那節省這個Token從100萬降到86K。\n這個非常厲害。\n有空的話就可以去試一下。\n然後這裡面其實還有很多很多這種場景。\n也就是你可以想像一下。\n你在生活工作中這些場景是需要判斷的。\n那麼你就可以使用J5來去做這個郵船裡面的替換。\n那麼你如果你想體驗這款模型的話,\n在OpenRot上還有這個官網上都可以去申請使用。\n官網上這邊申請的話很快就通過了。\n而且用起來速度也非常快。\n以上就是我對J5的一些初步看法了。\n那麼大家可以試一下自己的場景。\n真的有很多很多場景可以使用它來去體驗一下。\nOK,那本視頻就到這。\n希望這個視頻給你有所幫助。\n希望這個視頻給你更多。",
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      "text": "大家,這兩天非常熱門的模型是Jer。那這個模型呢,非常有意思。它不能對話,不能寫代碼,也不能識別圖片。它唯一能做的事情就是幫你去做選擇。那本期視頻就給大家來了解一下這一款熱門的決策型模型Jer。其實當我看到這個模型的時候,我也非常詫異。一款不能對話,也不能寫代碼,也不能識別圖片的模型到底有什麼用呢?當我看了官網的例子和外網的一些例子之後,我發現這款模型真的非常有用。",
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      "text": "因為其實不管是你在工作還是生活中,非常非常多的時候是需要決策的。如果我們用其他的模型,比如說CHALEJPT,或者是Cloud模型去做這種決策的話,推理的成本是非常高的。",
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      "text": "反應的時間也不會特別快,相當於你用大炮打了一個蚊子。那麼Jer這個模型呢,就是專門幹決策。那我們先用一個非常通俗的例子來理解一下Jer這個模型的輸入和輸出。",
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      "text": "那麼我們如果要用Jer這個模型的話,需要提供兩個東西。一個叫背景知識。這是我的理解。背景知識就是你要讓他做決定的話,你肯定要提供一些背景知識給他。",
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      "text": "然後就是問題,你的問題是什麼?發個Jer。那Jer就會做出選擇。然後你拿到這個選擇之後,再去走其他的流程。",
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      "text": "所以從這個大的這個流程裡面,我們能知道Jer是一個中間環節。就你可能這是你的一個工作流。那麼Jer只是起到一個中間路由,或者是中間判斷的一個過程。",
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      "text": "那麼他的選擇呢支持三種選擇。那第一種就是啊,我們可以認為叫做yes or no。",
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      "text": "我們用一個例子來解決定。比如說,小明的歲月成績考了60分。小明的父母是比較溫和的。但是如果他分數低於及格線的話,也會很生氣。",
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    {
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      "text": "那麼我們的背景知識就是這個。那我們的問題,那第一種回復的方式。問題是,父母會生氣嗎?那發給這個Jer。",
      "tokens": [
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    {
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      "text": "那Jer就會反過一個這樣的概率。會的概率是10%,那麼不會的概率是90%,那麼你就知道父母是不會生氣的。",
      "tokens": [
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    {
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      "text": "那這種就是Jer的第一種選擇方式。那麼你要告訴我,你在,要用這個Jer就是大摩寫生說,你要告訴他用的是哪一種。",
      "tokens": [
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    {
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      "text": "那第二種就是我們應該用的最多的,就是選項。還是一樣。但是問題就變成了,父母最可能如何回應小明這次考試。",
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    {
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      "text": "那麼你給出四個選項。A,表揚小明。B,溫和的鼓勵。三,認真的溝通。D,明顯生氣或嚴厲批評。那發給這個Jer。",
      "tokens": [
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    {
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      "text": "那Jer就給每個選項一個評分。那麼你從評分裡面能看到,是0.55。那C這個選項是最有可能的。",
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    {
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      "text": "認真溝通學習問題保持冷靜。那麼你就得到了一個最有可能的這個結果。",
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    {
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      "text": "最有可能的結果。那這個是第二種。第二種我覺得是在現實場面中用的最多的。",
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    {
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      "text": "那最後一個就是評分式的。那這種方式比如說,這個問題就變成了,父母對這次考試成績會有多不高興。",
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    {
      "id": 17,
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      "text": "你看這個問題就變成了一個分數的一個判斷。就是你有多大力度去這個選項。",
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    {
      "id": 18,
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      "text": "比如說A是基本滿意。沒有明顯不高興。B是略有失望。C是明顯不滿意。D呢非常生氣。",
      "tokens": [
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    {
      "id": 19,
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      "text": "那他的這個生氣的力度是在增加的。那你發給J5,J5會給到一個ABCD的相似投票一樣。",
      "tokens": [
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    {
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      "text": "那麼我們可以看到這個他的回答。B0.6現在得了65票。也就是說。",
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    {
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      "text": "那越有失望。讓態度溫和的概率是最高的。那這個時候。",
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    {
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      "text": "那你就可以根據他的評分的不同。去做下一步的選項。",
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    {
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      "text": "所以通過這三個選項的處理啊。還有這個場景啊。我們大概網上裡面就有一個概念了。",
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      "text": "那J5其實做最大的事情就是。你給他變成知識。你給他問題。給他選項。或者讓他回答yes or no。",
      "tokens": [
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    {
      "id": 25,
      "seek": 21616,
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      "text": "或者讓他去打一個分數。他其實最大的作用就是這個。幫你去做決策的參考。",
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    {
      "id": 26,
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      "text": "那很多人可能到這裡的時候。會覺得為什麼我們不用模型。去做這種決策的參考呢。",
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      "text": "那其實模型也可以做這種決策的參考。但是他Token的推理成本就高。",
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    {
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      "text": "那他小型速度可能不會很快。那比如說J5他的小型時間是100毫秒左右。",
      "tokens": [
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    {
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      "text": "成本是100萬Token。只要0.042美元。輸出完全免費。所以呢。",
      "tokens": [
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      "text": "這也就決定了J5這個模型。只能是成為你眾多工作流的一個部分。",
      "tokens": [
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    {
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      "text": "某些很多細分場景的模型的使用。它是不可能取代像Cloud。",
      "tokens": [
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    {
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      "text": "或JPT這些通用模型的。那麼這裡有一個案例可以讓大家進一步去了解。",
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    {
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      "text": "J5這個模型和其他大模型怎麼配合。比如說。",
      "tokens": [
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    {
      "id": 34,
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      "text": "你在你的這個A型工具裡面做了一個模型的路由。",
      "tokens": [
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    {
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      "text": "簡單的任務用便宜的模型。复杂的任務用好的模型。",
      "tokens": [
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    {
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      "text": "那怎麼去判斷這個任務的。复杂、簡單。",
      "tokens": [
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    {
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      "text": "那麼這個就可以交給J5去判斷。",
      "tokens": [
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    {
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      "text": "那他的判斷成本是非常低的。",
      "tokens": [
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    {
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      "text": "他判斷完了之後。然後再路由到這個模型裡面去。",
      "tokens": [
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    {
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      "text": "再接著往下走。所以他就成為你A型的裡面的。",
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    },
    {
      "id": 41,
      "seek": 27216,
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      "end": 295.16,
      "text": "某個環節裡面的一部分了。",
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    {
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      "text": "那麼在這裡來我也做了一個。用J5來玩這個。",
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    {
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      "text": "然後用J5去做這種選項的判斷。",
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    {
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      "text": "因為俄羅斯方塊只要控制方向就行了。",
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    {
      "id": 45,
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      "start": 305.16,
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      "text": "我們來看一下。",
      "tokens": [
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      "no_speech_prob": 2.4122894654032834e-11,
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    {
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      "text": "那這邊的話會接收俄羅斯方塊的這種做標信息。",
      "tokens": [
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    {
      "id": 47,
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      "text": "然後他這邊會返回。",
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      "no_speech_prob": 2.4122894654032834e-11,
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    {
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      "text": "應該是怎麼操作。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.3291666666666666,
      "no_speech_prob": 2.4122894654032834e-11,
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    {
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      "text": "返回的指令裡面是包括了他的操作方向。",
      "tokens": [
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      "no_speech_prob": 2.4122894654032834e-11,
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    },
    {
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      "end": 318.16,
      "text": "那麼J5的這個判斷的準確率。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.4122894654032834e-11,
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    },
    {
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      "text": "也不是說是100%。大概在五六成左右。",
      "tokens": [
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      "temperature": 0,
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    {
      "id": 52,
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      "text": "這個可能需要模型去疊代。",
      "tokens": [
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    {
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      "text": "然後你用其他的大模型其實也可以玩。",
      "tokens": [
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
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      "text": "但是成本和速度可能是沒有這個J5更快。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.243719966765756e-11,
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    {
      "id": 55,
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      "end": 331.16,
      "text": "更省成本。",
      "tokens": [
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    {
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      "text": "那這個想像速度是非常快的。",
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 57,
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      "start": 333.16,
      "end": 335.16,
      "text": "那官網這邊提供了非常多的案例。",
      "tokens": [
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 58,
      "seek": 31816,
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      "end": 337.16,
      "text": "比如說像這種模型路由啊。",
      "tokens": [
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 59,
      "seek": 31816,
      "start": 337.16,
      "end": 339.16,
      "text": "還有這種客戶的這種處理。",
      "tokens": [
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 60,
      "seek": 31816,
      "start": 339.16,
      "end": 341.16,
      "text": "客戶支持的處理。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 61,
      "seek": 31816,
      "start": 341.16,
      "end": 342.16,
      "text": "保險理賠。",
      "tokens": [
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      ],
      "temperature": 0,
      "avg_logprob": -0.2111447731160229,
      "compression_ratio": 1.4123076923076923,
      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 62,
      "seek": 31816,
      "start": 342.16,
      "end": 343.16,
      "text": "法律合規。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.2111447731160229,
      "compression_ratio": 1.4123076923076923,
      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 63,
      "seek": 31816,
      "start": 343.16,
      "end": 345.16,
      "text": "那麼我在外網上也是有一個很多。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.2111447731160229,
      "compression_ratio": 1.4123076923076923,
      "no_speech_prob": 2.243719966765756e-11,
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    },
    {
      "id": 64,
      "seek": 34516,
      "start": 345.16,
      "end": 347.16,
      "text": "比如說這種去除流氧器廣告。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.13146500408968187,
      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 65,
      "seek": 34516,
      "start": 347.16,
      "end": 350.16,
      "text": "把整個流氧器的道路信息發送給J5。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.13146500408968187,
      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
      "source": "whisper"
    },
    {
      "id": 66,
      "seek": 34516,
      "start": 350.16,
      "end": 351.16,
      "text": "讓J5去判斷哪個是廣告。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 67,
      "seek": 34516,
      "start": 351.16,
      "end": 352.16,
      "text": "並且消除。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.13146500408968187,
      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 68,
      "seek": 34516,
      "start": 352.16,
      "end": 354.16,
      "text": "還有這種郵件欺詐的。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 69,
      "seek": 34516,
      "start": 354.16,
      "end": 357.16,
      "text": "就是說把所有的郵件和相關的背景信息發給J5。",
      "tokens": [
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      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 70,
      "seek": 34516,
      "start": 357.16,
      "end": 360.16,
      "text": "讓J5去判斷哪些郵件的欺詐。",
      "tokens": [
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    },
    {
      "id": 71,
      "seek": 34516,
      "start": 360.16,
      "end": 362.16,
      "text": "那還有這個非常有意思的是什麼呢?",
      "tokens": [
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    },
    {
      "id": 72,
      "seek": 34516,
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      "text": "它是用J5做了一個Cloud的插件。",
      "tokens": [
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    },
    {
      "id": 73,
      "seek": 34516,
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      "text": "來判斷一下Cloud有沒有調用不必要的工具。",
      "tokens": [
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      "temperature": 0,
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    },
    {
      "id": 74,
      "seek": 34516,
      "start": 368.16,
      "end": 371.16,
      "text": "那節省這個Token從100萬降到86K。",
      "tokens": [
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    {
      "id": 75,
      "seek": 34516,
      "start": 371.16,
      "end": 372.16,
      "text": "這個非常厲害。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.13146500408968187,
      "compression_ratio": 1.450310559006211,
      "no_speech_prob": 1.9990285468618474e-11,
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    },
    {
      "id": 76,
      "seek": 37216,
      "start": 372.16,
      "end": 375.16,
      "text": "有空的話就可以去試一下。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
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    },
    {
      "id": 77,
      "seek": 37216,
      "start": 375.16,
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      "text": "然後這裡面其實還有很多很多這種場景。",
      "tokens": [
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      "temperature": 0,
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    },
    {
      "id": 78,
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      "start": 377.16,
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      "text": "也就是你可以想像一下。",
      "tokens": [
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      "no_speech_prob": 2.2355646847604937e-11,
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    },
    {
      "id": 79,
      "seek": 37216,
      "start": 378.16,
      "end": 381.16,
      "text": "你在生活工作中這些場景是需要判斷的。",
      "tokens": [
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      "no_speech_prob": 2.2355646847604937e-11,
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    },
    {
      "id": 80,
      "seek": 37216,
      "start": 381.16,
      "end": 385.16,
      "text": "那麼你就可以使用J5來去做這個郵船裡面的替換。",
      "tokens": [
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    },
    {
      "id": 81,
      "seek": 37216,
      "start": 385.16,
      "end": 387.16,
      "text": "那麼你如果你想體驗這款模型的話,",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
      "source": "whisper"
    },
    {
      "id": 82,
      "seek": 37216,
      "start": 387.16,
      "end": 390.16,
      "text": "在OpenRot上還有這個官網上都可以去申請使用。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
      "source": "whisper"
    },
    {
      "id": 83,
      "seek": 37216,
      "start": 390.16,
      "end": 392.16,
      "text": "官網上這邊申請的話很快就通過了。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
      "source": "whisper"
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    {
      "id": 84,
      "seek": 37216,
      "start": 392.16,
      "end": 394.16,
      "text": "而且用起來速度也非常快。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
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    },
    {
      "id": 85,
      "seek": 37216,
      "start": 394.16,
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      "text": "以上就是我對J5的一些初步看法了。",
      "tokens": [
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      "temperature": 0,
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      "source": "whisper"
    },
    {
      "id": 86,
      "seek": 37216,
      "start": 397.16,
      "end": 399.16,
      "text": "那麼大家可以試一下自己的場景。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.2355646847604937e-11,
      "source": "whisper"
    },
    {
      "id": 87,
      "seek": 39916,
      "start": 399.16,
      "end": 402.16,
      "text": "真的有很多很多場景可以使用它來去體驗一下。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 0.9923076923076923,
      "no_speech_prob": 2.097524237631987e-11,
      "source": "whisper"
    },
    {
      "id": 88,
      "seek": 39916,
      "start": 402.16,
      "end": 403.16,
      "text": "OK,那本視頻就到這。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.097524237631987e-11,
      "source": "whisper"
    },
    {
      "id": 89,
      "seek": 39916,
      "start": 403.16,
      "end": 404.16,
      "text": "希望這個視頻給你有所幫助。",
      "tokens": [
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