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  "text": "Workbody你大概率用過,或者至少聽說過。\n騰訊出的AI助手,裝到電腦上登錄就能幹活。\n寫文檔、讀材料、改方案都能丟給他,說不定你電腦裡現在就裝著。\n而騰訊在Github上還開源了另一個助手,叫Octob。\nGithub就是放開原代碼的那個網站,自家有了一個,幹嘛再造一個?\n很多人以為Octob就是Workbody的開源版。\n第一反應我也是怎麼猜的。\n我把Workbody的官方文檔和Octob的開源頁面都翻了一遍。\n發現猜錯了,兩個是騰訊旗下不同的產品,不是一個東西的兩個版本。\n更意外的是,大家以為的那個差別,也猜錯了。\n那騰訊為什麼還要再做一個,這期分兩段說。\n先把你手裡這個Workbody和那個開源的Octob是什麼關係講清楚。\n再說,我把兩個裝進同一台電腦,跑同一件活,看到了什麼。\n先說你熟悉的這個。\nWorkbody是騰訊做的桌面助手,裝在電腦上,註冊登錄就能用。\n免費體驗版每月有積分,網上還有三檔付費。\n那個開源的Octob呢,也是騰訊出的,掛在Github上。\n授權協議是MIT,就是代碼誰都能拿走,能改的那種。\n再說,大家猜錯的那個差別。\n很多人以為,Workbody只能用騰訊內置的模型,想接自己的模型得找Octob。\nWorkbody的官方文檔不是這麼寫的。\n文檔原文,模型配置允許您自行接入第三方大模型,作為Workbody調用底座。\n配置參數含API Key僅保存在本地Workbody Models JSON中,不上傳雲端。\n換成人話,你可以把別家模型接進來當發動機,密钥只存在你自己電腦的一個文件裡。\n文檔還寫著,使用時,Workbody僅作為通信鏈路,將您的輸入直接轉發至所配置的第三方模型。\n輸出由該模型直接返回。除,未完成請求,必要傳輸,安全審計,故障排查,依法留存所必需外。Workbody,不讀取,不存儲相關內容。\n不過文檔裡有一處自己跟自己打架。\n積分頁寫著,所有對話請求都要消耗積分。\n模型頁寫著,自定義模型的費用是你付給第三方的。\n到底扣不扣?我裝了免費體驗版實測,配好自己的模型,跑完一次任務。\n積分頁顯示,已使用是0。一分積分都沒扣。\n騰訊為什麼還要做兩個?內部怎麼想的我不知道,我只能把實測看到的擺給你。\n先看拿到手這一步,差別從裝完那一刻就開始了。\nWorkbody是510M的安裝包,裝完登入就能幹活。\nOctobus官方給的一行安裝指令,41秒裝完,可它開箱不能用。\n第一瓶就有一個大紅叉,提示,沒配模型。\n你得自己帶模型進來,要么填模型廠商發的密钥,要么在自己電腦上跑本地模型。\nWorkbody這邊,想接自己電腦上跑的本地模型也行。\n官方文檔有專門一節講Olama,就是把模型跑在你自己機器上的工具。\n不過我裝的5.56版里,供應商列表沒有現成的Olama選項,要走自訂一手填地址。\n我實測跑通了。\n也就是說,接自己模型這件事,兩個都行,差別不在這。\n再看看同一件活,同一份材料,CNNIC的第56次報告,78頁的PDF,就是統計中國網民規模的那份官方文件。\n同一句指令,逐字貼給兩邊。讀這份PDF,產出一份代數據的記要,再給我一張表。\n最關鍵的控制項,兩邊接的是同一個模型,都是Deep Seek官方的Flash。\n不這麼幹,交出來的東西有差別,就分不清是產品的差,還是模型的差。\nWorkbody那邊,9分34秒。PDF也讀完了,還現場裝了個解析工具包,可最後沒交東西。\n反過來問我兩個問題。\n記要是要哪種?這份報告不是會議記錄,是統計報告。\n一張表是要哪張表?問完,還給了三個按鈕讓我挑。\n平心而論,Workbody,問的都在裡。\n我那句指令裡,記要確實有其意,一張表也確實沒說清。\nOctop,一分鐘出頭就交卷。\n先檢查電腦裡有什麼現成工具。\n發現系統本來就有讀PDF的,直接拿來用。\n然後交出一份分6個部分的記要,外加一張10行的對照表。\n末尾還付了賬單,輸入269000個詞塊。\n詞塊就是AI算帳時把文字切成的小塊,其中8x3命中緩存,輸出不到7000。\n我把表裡的數字逐條對過原文。\n10個全對。\n所以這不是誰行誰不行。\nOctop的取向是先幹出來再讓你挑。\nWorkbody的取向是先問清楚再動手。\n一個直接給結果,一個先跟你確認。\n到這兒,標題那個問題已經能達了。\n騰訊為什麼還要做兩個?\n因為幹的是兩類需求。\n一個是開箱就能用的服務。\n賬號、額度、計量都在騰訊那邊。\n一個是自己搭起來的東西。\n要自己帶模型,但數據和改動權在你手裡。\n不花錢的話,Workbody能走到哪一步?\n免費版賬上有2000積分。\n500是套餐的。\n1500是平台獎勵的。\n接自己的模型。\n實測,不扣積分。\n用內置模型也不貴。\n便宜的檔只按0.03倍扣。\n還有幾個限時免費。\n一分不扣的。\n積分真用完了。\n簽到能領100。\n邀請一個人最高650。\n不過免費檔買不了積分加量包。\nOctop那邊是另一筆帳。\n軟件本身一分錢不要。\n可模型得自己掏。\n你填哪家的密要,\n就按哪家的價付給哪家。\n換來的是,代碼是MIT。\n建帳號連手機號都不用。\n數據全落在自己電腦的一個文件夾裡。\n所以該怎麼選?\n想裝上就用。\n不想操心模型和密要的。\n選Workbody。\n帳號、額度、默認模型都在騰訊那邊管著。\n你只管幹活。\n想讓數據留在自己電腦上。\n願意自己帶模型的。\n選Octop。\n公司裡要拍板選哪個AI助手的。\n把這條轉給他。\n能省掉自己裝一遍對比的功夫。\n繞回標題那個問題。\n騰訊為什麼還要開源一個Octop?\n騰訊的答案我給不了。\n實測給的答案很清楚。\n兩個根本不是給同一種人準備的。\n差別不在能不能接你的模型。\n在這套東西到底歸誰。\n這類上手實測我每期都做。\n裝一遍,跑一遍,把帳算給你看。\n你手頭那台電腦,會裝開箱即用的那個,還是歸自己的那個。",
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      "text": "Workbody你大概率用過,或者至少聽說過。",
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      "text": "騰訊出的AI助手,裝到電腦上登錄就能幹活。",
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      "text": "寫文檔、讀材料、改方案都能丟給他,說不定你電腦裡現在就裝著。",
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      "text": "而騰訊在Github上還開源了另一個助手,叫Octob。",
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      "text": "Github就是放開原代碼的那個網站,自家有了一個,幹嘛再造一個?",
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      "text": "很多人以為Octob就是Workbody的開源版。",
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      "seek": 2720,
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      "text": "第一反應我也是怎麼猜的。",
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    {
      "id": 7,
      "seek": 2720,
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      "text": "我把Workbody的官方文檔和Octob的開源頁面都翻了一遍。",
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    {
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      "seek": 2720,
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      "text": "發現猜錯了,兩個是騰訊旗下不同的產品,不是一個東西的兩個版本。",
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      "text": "更意外的是,大家以為的那個差別,也猜錯了。",
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      "text": "那騰訊為什麼還要再做一個,這期分兩段說。",
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      "text": "先把你手裡這個Workbody和那個開源的Octob是什麼關係講清楚。",
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    {
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      "seek": 5580,
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      "text": "再說,我把兩個裝進同一台電腦,跑同一件活,看到了什麼。",
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    {
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      "text": "先說你熟悉的這個。",
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    {
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      "end": 68.39999999999999,
      "text": "Workbody是騰訊做的桌面助手,裝在電腦上,註冊登錄就能用。",
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      "text": "免費體驗版每月有積分,網上還有三檔付費。",
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      "text": "那個開源的Octob呢,也是騰訊出的,掛在Github上。",
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      "text": "授權協議是MIT,就是代碼誰都能拿走,能改的那種。",
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      "text": "再說,大家猜錯的那個差別。",
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    {
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      "text": "很多人以為,Workbody只能用騰訊內置的模型,想接自己的模型得找Octob。",
      "tokens": [
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      "text": "Workbody的官方文檔不是這麼寫的。",
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      "text": "文檔原文,模型配置允許您自行接入第三方大模型,作為Workbody調用底座。",
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      "text": "配置參數含API Key僅保存在本地Workbody Models JSON中,不上傳雲端。",
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      "text": "換成人話,你可以把別家模型接進來當發動機,密钥只存在你自己電腦的一個文件裡。",
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      "text": "文檔還寫著,使用時,Workbody僅作為通信鏈路,將您的輸入直接轉發至所配置的第三方模型。",
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    {
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      "text": "輸出由該模型直接返回。除,未完成請求,必要傳輸,安全審計,故障排查,依法留存所必需外。Workbody,不讀取,不存儲相關內容。",
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      "text": "不過文檔裡有一處自己跟自己打架。",
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      "text": "積分頁寫著,所有對話請求都要消耗積分。",
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    {
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      "text": "模型頁寫著,自定義模型的費用是你付給第三方的。",
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    {
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      "text": "到底扣不扣?我裝了免費體驗版實測,配好自己的模型,跑完一次任務。",
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      "text": "積分頁顯示,已使用是0。一分積分都沒扣。",
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      "text": "騰訊為什麼還要做兩個?內部怎麼想的我不知道,我只能把實測看到的擺給你。",
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      "text": "先看拿到手這一步,差別從裝完那一刻就開始了。",
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      "text": "Workbody是510M的安裝包,裝完登入就能幹活。",
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      "text": "Octobus官方給的一行安裝指令,41秒裝完,可它開箱不能用。",
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      "text": "第一瓶就有一個大紅叉,提示,沒配模型。",
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      "text": "你得自己帶模型進來,要么填模型廠商發的密钥,要么在自己電腦上跑本地模型。",
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      "text": "Workbody這邊,想接自己電腦上跑的本地模型也行。",
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      "text": "官方文檔有專門一節講Olama,就是把模型跑在你自己機器上的工具。",
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      "source": "whisper"
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    {
      "id": 39,
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      "text": "不過我裝的5.56版里,供應商列表沒有現成的Olama選項,要走自訂一手填地址。",
      "tokens": [
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    {
      "id": 40,
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      "text": "我實測跑通了。",
      "tokens": [
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      "text": "也就是說,接自己模型這件事,兩個都行,差別不在這。",
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    {
      "id": 42,
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      "text": "再看看同一件活,同一份材料,CNNIC的第56次報告,78頁的PDF,就是統計中國網民規模的那份官方文件。",
      "tokens": [
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    {
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      "text": "同一句指令,逐字貼給兩邊。讀這份PDF,產出一份代數據的記要,再給我一張表。",
      "tokens": [
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      "text": "最關鍵的控制項,兩邊接的是同一個模型,都是Deep Seek官方的Flash。",
      "tokens": [
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      "text": "不這麼幹,交出來的東西有差別,就分不清是產品的差,還是模型的差。",
      "tokens": [
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      "id": 46,
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      "text": "Workbody那邊,9分34秒。PDF也讀完了,還現場裝了個解析工具包,可最後沒交東西。",
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    {
      "id": 47,
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      "end": 257.4,
      "text": "反過來問我兩個問題。",
      "tokens": [
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    {
      "id": 48,
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      "end": 262.0,
      "text": "記要是要哪種?這份報告不是會議記錄,是統計報告。",
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    },
    {
      "id": 49,
      "seek": 25540,
      "start": 262.0,
      "end": 266.4,
      "text": "一張表是要哪張表?問完,還給了三個按鈕讓我挑。",
      "tokens": [
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    {
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      "text": "平心而論,Workbody,問的都在裡。",
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      "no_speech_prob": 2.1660570906356647e-11,
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      "text": "我那句指令裡,記要確實有其意,一張表也確實沒說清。",
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    },
    {
      "id": 52,
      "seek": 25540,
      "start": 274.6,
      "end": 277.0,
      "text": "Octop,一分鐘出頭就交卷。",
      "tokens": [
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      "temperature": 0,
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    },
    {
      "id": 53,
      "seek": 25540,
      "start": 277.0,
      "end": 279.8,
      "text": "先檢查電腦裡有什麼現成工具。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.1660570906356647e-11,
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    },
    {
      "id": 54,
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      "end": 283.6,
      "text": "發現系統本來就有讀PDF的,直接拿來用。",
      "tokens": [
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    },
    {
      "id": 55,
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      "end": 288.20000000000005,
      "text": "然後交出一份分6個部分的記要,外加一張10行的對照表。",
      "tokens": [
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 56,
      "seek": 28360,
      "start": 288.20000000000005,
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      "text": "末尾還付了賬單,輸入269000個詞塊。",
      "tokens": [
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 57,
      "seek": 28360,
      "start": 292.20000000000005,
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      "text": "詞塊就是AI算帳時把文字切成的小塊,其中8x3命中緩存,輸出不到7000。",
      "tokens": [
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    },
    {
      "id": 58,
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      "text": "我把表裡的數字逐條對過原文。",
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 59,
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      "end": 303.6,
      "text": "10個全對。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.065130878803334e-11,
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    {
      "id": 60,
      "seek": 28360,
      "start": 303.6,
      "end": 306.0,
      "text": "所以這不是誰行誰不行。",
      "tokens": [
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 61,
      "seek": 28360,
      "start": 306.0,
      "end": 309.0,
      "text": "Octop的取向是先幹出來再讓你挑。",
      "tokens": [
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 62,
      "seek": 28360,
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      "text": "Workbody的取向是先問清楚再動手。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.1366113271468725,
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      "no_speech_prob": 2.065130878803334e-11,
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    },
    {
      "id": 63,
      "seek": 31220,
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      "end": 314.8,
      "text": "一個直接給結果,一個先跟你確認。",
      "tokens": [
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    },
    {
      "id": 64,
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      "end": 317.8,
      "text": "到這兒,標題那個問題已經能達了。",
      "tokens": [
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    {
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      "text": "騰訊為什麼還要做兩個?",
      "tokens": [
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      "compression_ratio": 1.25,
      "no_speech_prob": 2.099878430861235e-11,
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    {
      "id": 66,
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      "start": 319.8,
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      "text": "因為幹的是兩類需求。",
      "tokens": [
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      "no_speech_prob": 2.099878430861235e-11,
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    {
      "id": 67,
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      "text": "一個是開箱就能用的服務。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 2.099878430861235e-11,
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    },
    {
      "id": 68,
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      "start": 323.8,
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      "text": "賬號、額度、計量都在騰訊那邊。",
      "tokens": [
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      "no_speech_prob": 2.099878430861235e-11,
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    {
      "id": 69,
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      "start": 326.8,
      "end": 328.8,
      "text": "一個是自己搭起來的東西。",
      "tokens": [
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      "temperature": 0,
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    {
      "id": 70,
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      "text": "要自己帶模型,但數據和改動權在你手裡。",
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      "no_speech_prob": 2.099878430861235e-11,
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    },
    {
      "id": 71,
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      "start": 332.8,
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      "text": "不花錢的話,Workbody能走到哪一步?",
      "tokens": [
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 72,
      "seek": 33280,
      "start": 336.40000000000003,
      "end": 338.40000000000003,
      "text": "免費版賬上有2000積分。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 73,
      "seek": 33280,
      "start": 338.40000000000003,
      "end": 340.40000000000003,
      "text": "500是套餐的。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 74,
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      "start": 340.40000000000003,
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      "text": "1500是平台獎勵的。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.2276119402985075,
      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 75,
      "seek": 33280,
      "start": 342.40000000000003,
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      "text": "接自己的模型。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.2276119402985075,
      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 76,
      "seek": 33280,
      "start": 343.40000000000003,
      "end": 345.40000000000003,
      "text": "實測,不扣積分。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 77,
      "seek": 33280,
      "start": 345.40000000000003,
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      "text": "用內置模型也不貴。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.2276119402985075,
      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 78,
      "seek": 33280,
      "start": 347.40000000000003,
      "end": 349.40000000000003,
      "text": "便宜的檔只按0.03倍扣。",
      "tokens": [
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 79,
      "seek": 33280,
      "start": 349.40000000000003,
      "end": 351.40000000000003,
      "text": "還有幾個限時免費。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 80,
      "seek": 33280,
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      "text": "一分不扣的。",
      "tokens": [
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      "temperature": 0,
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      "compression_ratio": 1.2276119402985075,
      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 81,
      "seek": 33280,
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      "text": "積分真用完了。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.12156648089171974,
      "compression_ratio": 1.2276119402985075,
      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 82,
      "seek": 33280,
      "start": 353.40000000000003,
      "end": 354.40000000000003,
      "text": "簽到能領100。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.12156648089171974,
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 83,
      "seek": 33280,
      "start": 354.40000000000003,
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      "text": "邀請一個人最高650。",
      "tokens": [
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      "no_speech_prob": 1.9982605847790325e-11,
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    },
    {
      "id": 84,
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      "text": "不過免費檔買不了積分加量包。",
      "tokens": [
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      "no_speech_prob": 1.383279688710326e-11,
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    {
      "id": 85,
      "seek": 35640,
      "start": 360.0,
      "end": 362.0,
      "text": "Octop那邊是另一筆帳。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.383279688710326e-11,
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    },
    {
      "id": 86,
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      "start": 362.0,
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      "text": "軟件本身一分錢不要。",
      "tokens": [
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    {
      "id": 87,
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      "text": "可模型得自己掏。",
      "tokens": [
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      "no_speech_prob": 1.383279688710326e-11,
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    {
      "id": 88,
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      "start": 365.4,
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      "text": "你填哪家的密要,",
      "tokens": [
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      "temperature": 0,
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    {
      "id": 89,
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      "text": "就按哪家的價付給哪家。",
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    },
    {
      "id": 90,
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      "start": 368.79999999999995,
      "end": 371.4,
      "text": "換來的是,代碼是MIT。",
      "tokens": [
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    {
      "id": 91,
      "seek": 35640,
      "start": 371.4,
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      "text": "建帳號連手機號都不用。",
      "tokens": [
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      "no_speech_prob": 1.383279688710326e-11,
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    {
      "id": 92,
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      "start": 373.4,
      "end": 376.2,
      "text": "數據全落在自己電腦的一個文件夾裡。",
      "tokens": [
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    {
      "id": 93,
      "seek": 35640,
      "start": 376.2,
      "end": 377.4,
      "text": "所以該怎麼選?",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.15226055420551105,
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      "no_speech_prob": 1.383279688710326e-11,
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    {
      "id": 94,
      "seek": 35640,
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      "end": 378.4,
      "text": "想裝上就用。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.383279688710326e-11,
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    },
    {
      "id": 95,
      "seek": 35640,
      "start": 378.4,
      "end": 380.2,
      "text": "不想操心模型和密要的。",
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      "temperature": 0,
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      "no_speech_prob": 1.383279688710326e-11,
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    },
    {
      "id": 96,
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      "end": 381.4,
      "text": "選Workbody。",
      "tokens": [
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      "temperature": 0,
      "avg_logprob": -0.15226055420551105,
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      "no_speech_prob": 1.383279688710326e-11,
      "source": "whisper"
    },
    {
      "id": 97,
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      "start": 381.4,
      "end": 384.79999999999995,
      "text": "帳號、額度、默認模型都在騰訊那邊管著。",
      "tokens": [
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      "no_speech_prob": 1.383279688710326e-11,
      "source": "whisper"
    },
    {
      "id": 98,
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      "start": 384.79999999999995,
      "end": 386.2,
      "text": "你只管幹活。",
      "tokens": [
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      "temperature": 0,
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      "no_speech_prob": 1.383279688710326e-11,
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    },
    {
      "id": 99,
      "seek": 38620,
      "start": 386.2,
      "end": 388.2,
      "text": "想讓數據留在自己電腦上。",
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      "temperature": 0,
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      "no_speech_prob": 1.3792493189224153e-11,
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    },
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      "id": 100,
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      "text": "願意自己帶模型的。",
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      "text": "選Octop。",
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      "text": "公司裡要拍板選哪個AI助手的。",
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      "text": "把這條轉給他。",
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      "text": "能省掉自己裝一遍對比的功夫。",
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      "text": "繞回標題那個問題。",
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      "text": "騰訊為什麼還要開源一個Octop?",
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      "text": "騰訊的答案我給不了。",
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      "text": "實測給的答案很清楚。",
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      "text": "兩個根本不是給同一種人準備的。",
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      "text": "差別不在能不能接你的模型。",
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      "text": "在這套東西到底歸誰。",
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      "text": "裝一遍,跑一遍,把帳算給你看。",
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      "text": "你手頭那台電腦,會裝開箱即用的那個,還是歸自己的那個。",
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