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埃隆·馬斯克 CNBC 主持人大衛·費伯采訪
CNBC 實錄：埃隆·馬斯克今日接受 CNBC 主持人大衛·費伯的現場采訪
CNBC Transcript: Elon Musk Sits Down for Secondary Interview with CNBC’s David Faber Live on CNBC Today
May 20, 2025
CNBC 對特斯拉首席執行官埃隆·馬斯克、SpaceX 首席執行官、xAI 首席執行官兼 X 創始人以及 CNBC 主持人大衛·費伯的采訪實錄，采訪於5月20日（星期二）上午10點至下午4點（美國東部時間）播出。這是大衛·費伯今日第二次采訪埃隆·馬斯克。視頻鏈接：
https://www.cnbc.com/video/2025/05/20/tesla-ceo-elon-musk-theres-no-need-for-tesla-to-buy-uber.html
https://www.cnbc.com/video/2025/05/20/tesla-ceo-elon-musk-no-plans-to-merge-tesla-and-xai.html
David Faber 今天首次采訪 Elon Musk 的文字記錄：
大衛·費伯：喬恩，謝謝。是的，能有這麽一個精彩的中場休息真是難得。埃隆·馬斯克再次來到奧斯汀的超級工廠與我見麵。謝謝你回來，我們之前討論過特斯拉，但很多事情都沒談及。顯然，我很少遇到這種空檔期。所以，讓我來回答一下上次談話後一些人開始提出的一個問題。特斯拉為什麽不收購優步？
埃隆·馬斯克：沒必要，因為我們有大量的汽車。我們有數百萬輛能夠自動駕駛的汽車。我應該說，這既包括特斯拉自有車隊，也允許特斯拉車主在車隊中增減車輛，這樣現有的特斯拉車主就可以通過增加或減少車輛數量來賺錢。我認為，特斯拉車主或許可以通過允許車輛加入自動駕駛車隊來賺取更多收益，而不是在租賃中支付費用。這就是為什麽我認為，這有點像Airbnb和Uber的結合體。就像Airbnb一樣，你可以出租閑置的臥室或房子（如果你不使用的話），並從中賺錢。這正是我們期望特斯拉客戶能夠做到的。
費伯：對。隨著規模的擴大，你顯然，你之前說過，你覺得自己擁有了物流能力，也擁有了開發應用程序的能力。當然，還有其他需要改進的地方嗎？
馬斯克：是的，我認為我們沒有遺漏任何東西。特斯拉擁有在一夜之間打造龐大自動駕駛車隊所需的所有要素。
FABER：是的，雖然我談到了交易，但這實際上會讓我去XAI的一些地方，但你知道，我之前在今天早些時候的一次采訪中提到過，不是跟我。你很忙，夥計。你有時白天要麵對很多不同的媒體。
MUSK：是的，有很多事情要做。
FABER：是的，你曾表示希望在特斯拉擁有更多控製權。
MUSK：是的。我的意思是，真的，隻要有足夠的控製權，以免在未來某個時候被激進投資者趕下台就行了。
FABER：是的
MUSK：這就是我所說的，就像某種……
FABER：你之前說過。
MUSK：是的，有些新東西，也就是大約25%的水平，你知道，這意味著如果我發瘋了，我肯定會被趕出去。但這確實需要，你知道，我感覺有點像這個數字，因為這就是我擁有的控製權，但控製權還沒有大到讓我不會被趕走。
FABER：好的，我明白你想要25%的原生控製權。在那個層麵上，你根本不可能擁有。
馬斯克：不，你可以，如果你真的，如果你表現糟糕，並且正在摧毀公司的價值。或者，好吧，或者我已經徹底瘋了。但如果你認為這不是，那不是，那不是真正的控製權。我的意思是，如果你擁有真正的控製權，就像穀歌的拉裏和謝爾蓋那樣，你知道，任何擁有多數投票控製權的人，而我沒有。
FABER：不，明白，紮克伯格擁有它，拉裏和謝爾蓋。我知道有些公司擁有絕對投票權。
馬斯克：即使你犯了謀殺罪，身陷囹圄，你仍然能夠控製公司。
費伯：在這種情況下，你的經濟狀況和你的投票權是一樣的。
馬斯克：在這種情況下
是的，我很樂意把這分開，但我基本上是交易所。他們不被允許這麽做。
FABER：我知道，我知道他們會這麽做。你知道，你提到要毀掉公司，顯然你不會這麽做。但還是回到我們之前討論的話題吧。不過，你不覺得你損害了公司。你知道，我再次回到XAI的問題上。但去年息稅前利潤為140億美元，而2022年的息稅前利潤為76.59億美元，你的營業利潤率顯然下降了，上個季度的銷售額和所有市場都下降了。你看到轉機了嗎？你會不會照照鏡子，然後說，夥計，我得做得更好。我得變得更好。
馬斯克：你看。我認為人們可以看看個別季度的業績，但這無關緊要。正如我之前提到的，我們為了生產Model Y，對全球所有生產線進行了大規模的改造。Model Y幾乎占據了我們汽車銷量的絕大部分，而Model Y是全球最暢銷的車型。所以，顯然，為了改造工廠，
FABER：而且還有一款外觀漂亮的新車型。
MUSK：是的，它實際上看起來像個變形金剛。
FABER：當然，我知道，我們的相機，抱歉，上麵那個，就是鏡頭。就是它，沒錯，擎天柱次貸，沒錯。
MUSK：所以，但真正衡量公司未來價值的最佳指標是股價和市值，而目前股價非常強勁。
FABER：不，它的市值已經反彈到超過1萬億美元。顯然，它在過去一年裏大幅上漲。不過，正如我們之前所說，這很大程度上與自動駕駛的Robotaxi有關。我一直指著身後，我們的觀眾看不到它。但是，你最近說擎天柱機器人會發展到數百億個，但這還需要幾十年的時間。
馬斯克：至少十年後。
費伯：肯定不止這些。
馬斯克：它會增長得非常快。
費伯：你為什麽這麽認為？
馬斯克：我認為人形機器人將成為有史以來最熱門的產品。它的需求將是無止境的。基本上每個人都想要一個，誰不想擁有自己的C3PO或R2D2呢？每個人都會想要一個。
費伯：你說過。你知道你的目標是生產一百萬台機器人，我想到2030年，這就是我之前提到的。
馬斯克：我認為這是一個合理的目標。
費伯：然後，開始邁向可持續的富足，這是你可以探討的。你知道，我想知道我們一直在討論自動駕駛，以及需要多長時間，需要訓練汽車才能達到或超過人類的能力。但是這些機器人呢？它們需要多少訓練才能真正完成各種不同類型的任務？這需要很長時間嗎？
馬斯克：是的，需要大量的訓練，這需要大量的計算機資源，而且需要時間。我認為我們可以實現某些門檻上的突破，比如，如果擎天柱可以觀看視頻、YouTube視頻、操作視頻等等。基於那段視頻，就像人類可以學習如何做這件事一樣，那麽你的任務擴展性就會非常顯著，因為它可以非常快速地學習任何東西。所以我認為我們很快就會實現這個目標。
費伯：不過，我們還沒到那一步。
馬斯克：我們還沒到那一步。
費伯：你依賴於學習和訓練方麵的顯著提升。
馬斯克：是的，不，那是——
費伯：還有通勤。
馬斯克：這就是為什麽我稱之為一個非常重要的門檻——
費伯：明白了。
馬斯克：通過觀看視頻學習的能力，就是這樣——
費伯：對。
馬斯克：但就目前而言——
費伯：這與觀看人類視頻，或者讓人類現在用某個任務來訓練它不同。
馬斯克：是的，沒錯。目前，我們正在訓練擎天柱執行一些基本任務，需要人類穿著一種叫做“動作捕捉”（Mocap）的服裝，頭上裝有攝像頭，機器人會像人一樣移動，比如撿起物體、開門，或者做一些基本任務，比如扔球、跳舞等等。我認為我們需要這樣做，才能提升它的智能，讓它具備基本功能。接下來，我覺得它非常有趣，也非常像人類的地方在於，你希望機器人能夠自我遊戲。你會問，孩子是如何學習的？嗯，孩子有玩具，然後玩玩具，玩積木。在某個時候，通過反複練習，弄清楚如何把三角形放進三角形的洞裏，把圓形放進圓形的洞裏。這就是自遊戲。一旦你擁有了很多機器人，你就可以進行這種自遊戲，也就是把機器人放在一個有玩具的房間裏，讓它玩玩具。
費伯：它會學習。
馬斯克：是的。而且你必須有一個獎勵機製。比如說，機器人的目標是，你知道，那種經典的兒童
玩具。你把圓形放進圓形孔裏，正方形放進方形孔裏，三角形放進三角形孔裏，一直重複，直到它起作用，獎勵函數成功為止。
FABER：現在不需要任何進步就能實現這一點嗎？我的意思是，不需要人工智能或計算方麵的進步，或者諸如此類的事情？
馬斯克：需要一些進步，但我認為這些進步並非不可克服。我認為我們可以，我們可以在未來幾年內解決這些問題。
FABER：好的，所以到那時，當數百萬輛這樣的汽車下線時，就像我們剛才看到的汽車一樣，它們將完全自動駕駛，它們將會……
馬斯克：哦，是的。
FABER：我的意思是，就像你所描述的……
馬斯克：當然是五年後。
FABER：來我家吧，我就能說，好了，洗碗了。現在我需要你去遛狗。
馬斯克：當然。
費伯：幫我抱抱孩子。
馬斯克：事實上，你真的不需要它，它會自動知道你可能想要什麽，然後按照你可能想要的方式去做，甚至你都不用開口。
費伯：你需要多少個 GPU？
馬斯克：嗯，相當多的 GPU。我們確實有自己的訓練程序 Dojo，我認為它會很有幫助。
費伯：目前，它對自動駕駛的貢獻大約為 5%，對吧？
馬斯克：是的，所以——
費伯：是在紐約嗎？在紐約州？
馬斯克：是的，在紐約。所以我們預計仍然會從英偉達購買大量 GPU，一些從 AMD 購買，也可能從其他公司購買。隻要英偉達的產品比我們生產的更好，我們就會繼續從英偉達購買。
FABER：現在是這樣嗎？
馬斯克：是的，是的。
FABER：是的。我的意思是，你顯然是為了xAI，孟菲斯——
馬斯克：規模很大。
FABER：規模很大，對吧？
馬斯克：是的。xAI正在構建最強大的，我們擁有最強大的，我認為我們目前擁有世界上最強大的訓練集群，它由超過20萬個GPU組成，用於進行連貫的訓練。
FABER：現在已經有20萬個了。
馬斯克：是的。
FABER：在孟菲斯，那個設施——
馬斯克：是的。
FABER：好的
馬斯克：是的。
FABER：你要去哪裏？
馬斯克：然後，我們將在孟菲斯附近的某個地方部署百萬級 GPU。
費伯：等一下，在新地點部署一百萬個 GPU，或者再部署 80 萬個 GPU。
馬斯克：一百萬，一百萬個下一代 GPU。
費伯：那麽布萊克韋爾。
馬斯克：嗯，是的。
費伯：等等，你現在在建造這個嗎？
馬斯克：是的。
費伯：你是怎麽為它供電的？
馬斯克：這是一個千兆瓦級的係統。
費伯：什麽，你為它準備了電力嗎？
馬斯克：是的。
費伯：有。天然氣還是——
馬斯克：是的。這是一個難題。
費伯：這是一個難題。找到電力？
馬斯克：獲取千兆瓦的電力，將千兆瓦的電力投入使用，並確保這些千兆瓦的電力可靠運行，因為電網中存在電力波動等等。因此，實際上，我今天剛在網上發布了一些信息，其中提到了一堆特斯拉超級電池組（megapack），這些電池對於調節電網的電力至關重要，這樣 GPU 就不會受到電力波動的影響。它們需要穩定的電力，所以，如果偶爾出現輕微的電壓下降，或者像這次停電一樣，你需要一個不間斷電源來應對這種情況。所以我們準備了很多超級電池組來支持——
費伯：為了支持這一點。你明白嗎——
馬斯克：這將是世界上第一個千兆瓦級的訓練集群，也是最強大的訓練集群。
費伯：什麽時候能建成？
馬斯克：希望在六個月或九個月左右。
FABER：這主要是為 Grok 提供動力嗎？
MUSK：是的。
FABER：是的。
MUSK：這隻是為 Grok 提供動力。
FABER：對。Grok 還在不斷進步。我的意思是，我經常使用它。
MUSK：是的。
FABER：我看到你在 Joe 身上用過這個模式，是和 Rogan 一起用那個模式嗎？那個模式是什麽？就是那種總是調皮搗蛋、滿嘴髒話的模式。
MUSK：嗯，我的意思是，如果你想在派對上找點樂子，Grok 的瘋狂模式會很有趣。
FABER：是的。
MUSK：這是下一個層次。
FABER：是的。功耗會成為我們繼續推進人工智能的門檻嗎？
馬斯克：是的，我想幾年前我就做過一個非常明顯的預測，那就是人工智能的限製因素將是芯片。現在仍然是芯片，某種程度上是芯片，然後是電氣設備，因為你需要將電壓從30萬伏降到400伏，供計算機使用。所以，你需要降壓變壓器，大量的變壓器，大量的電纜、線路和保險絲。你知道，本質上就是大量的變壓器。而電力變壓器行業並不習慣需求的大幅變化。
費伯：現在變壓器短缺。
馬斯克：字麵意思是變壓器短缺。然後，有趣的是，人工智能算法被稱為變壓器。
我們的擎天柱機器人是以擎天柱命名的。那是一個變形金剛機器人。
費伯：數量很多。
馬斯克：所以我們是變形金剛的變形金剛，變形金剛的變形金剛。
費伯：對，對，但這台變壓器，就是其他變壓器都需要的，而這台變壓器短缺。
馬斯克：當我們解決變壓器短缺問題時，就會出現根本性的電力短缺。
費伯：我們到了嗎？或者說我們很快就會到達？
馬斯克：我們很快就要到了。
費伯：我們正在。
馬斯克：我猜人們可能會在發電方麵開始麵臨挑戰，大概在明年年中或年底。
費伯：即使放鬆管製，並努力加快步伐，情況也可能如此。
馬斯克：有多少發電廠正在建設中？一座發電廠能建多久？
費伯：對，對。中國似乎正在快速建設這些設施。
馬斯克：中國正在建設——中國已經建成和正在建設的發電廠數量非常多。我認為人們並沒有完全意識到這一點。我在我的X賬戶上發布了一張美國發電量與中國發電量的對比圖。中國的發電量看起來就像一枚火箭升空，而美國的發電量則持平。
費伯：對。
馬斯克：所以我認為到今年年底，中國的發電量將達到美國的2.5倍左右，並且有望達到美國的3到4倍。
費伯：有趣的是，當你想到中國時，我的意思是，電動汽車、自動駕駛汽車，我們談到了電池、太陽能、發電——順便說一下，甚至最近還談到了生物技術。我不知道你是否看到了輝瑞公司授權的抗癌藥物。
馬斯克：是的。
費伯：他們似乎是，我不知道。我來問你個問題。他們在某些重要領域領先於我們嗎？
馬斯克：美國在突破性創新方麵仍然占有優勢，但——所以是美國——我認為這在某種程度上是一種文化因素，也就是說，要想實現突破性創新，你必須質疑權威。從根本上說，當你進行突破性創新時，你就是在質疑傳統觀念。
費伯：對。
馬斯克：你知道，中國通常不喜歡質疑自己的權威，或者說，在質疑權威方麵，中國不像美國那樣鼓勵這種做法。
費伯：不。但他們似乎確實擅長發現一些東西，然後使其變得更好，並不斷擴大規模。
馬斯克：是的，我確實想強調的是，中國擁有如此多聰明、才華橫溢、努力工作的人才，數量之多令人驚歎。人才的數量之多，簡直是驚人的。我的意思是，我欽佩中國的實力。我認為，我認為大多數中國以外的人並不了解中國的實力。它確實很特別，很特別。
費伯：是的，是的。你知道，在我們剩下的時間裏，我想繼續關注xAI。首先，你知道，你之前提到希望在特斯拉擁有更多控製權。你會考慮將xAI並入特斯拉嗎？顯然，這是一種他們可以向你發行股票的方式，而且可以想象這會提升你的整體經濟效益。有可能嗎？
馬斯克：嗯，我想一切皆有可能，但很難去猜測——你知道，特斯拉是上市公司，所以——
費伯：是的，我認為要獲得少數股東的多數票，或者任何你可能需要的票數，可能並不容易。
馬斯克：是的。這並非不可能，但這必須是特斯拉股東會投票讚成的——他們願意投票支持的，所以——
費伯：明白了。所以，但這不是你正在考慮做的事情？
馬斯克：目前還沒有。目前還沒有——沒有計劃這麽做。
費伯：對。
馬斯克：這並非不可能，但顯然需要特斯拉股東的支持。
費伯：另一個你顯然可以增強控製權的方法是讓那項薪酬計劃在特拉華州或特拉華州最高法院獲得通過。或者製定一個新的方案。我相信你從2018年起就沒領過工資了。
馬斯克：是的。
費伯：那麽你現在在哪裏——
馬斯克：七年了。
費伯：是的。你現在在哪裏——
馬斯克：七年零工資。
費伯：不過，公平地說，如果交易成功，你會賺得盆滿缽滿。
馬斯克：是的，沒問題。當然。
費伯：沒問題？你會賺得比任何人都多的錢。
馬斯克：是的，我想是的。但我的意思是，如果任何一位財富500強企業的CEO同意像我同意的這樣的計劃，你應該立即購買該公司的股票。
費伯：是的。不，我記得當時，公平地說，股價遠高於目標價，而且顯然已經達到了。
馬斯克：是的。
費伯：據你所知，董事會是否正在製定另一個潛在計劃，如果那個計劃最終無法通過特拉華州，最高法院裁定反對州長的裁決？
馬斯克：我的意思是，我不想……
我代表董事會發言，但你知道，我相信他們正在考慮這個問題。不過，你知道，我無法評論特斯拉董事會的討論。
費伯：你之前說過。我的意思是，你想繼續擔任首席執行官。為什麽不——你知道，埃隆，考慮到你在很多方麵都承受著巨大的壓力，我不禁想，為什麽不在特斯拉成為像埃裏森那樣的人物呢？顯然，你年輕得多，但他在甲骨文仍然很有影響力。但你知道，他不是首席執行官，而且他沒有得到應有的關注。
馬斯克：他不是首席執行官？
費伯：不，他不是。薩弗拉才是首席執行官。
馬斯克：哦，好的。
費伯：是的。至少在頭銜上不是。你提得好。
馬斯克：不，不，我想也許更貼切的說法是——我是拉裏·埃裏森的超級粉絲，我的好朋友。老板。
費伯：再說一遍？
馬斯克：老板，我想應該是——他是甲骨文的老板。
費伯：是的，是的，他是。而且他有很多股份。最後，我想——
馬斯克：他不是CEO，他隻是老板。
費伯：他是老板。是的，他的股份比例很高，比你在特斯拉的股份比例高得多。
馬斯克：是的——甲骨文的價格和比例。
費伯：最後，我想說，我的意思是，有很多事情我們還沒談到，但我們盡量不耽誤你的時間。我們準備好迎接人工智能將給社會帶來的變化了嗎？你知道，我每天都在努力工作，關注這些變化。顯然，我們——他們在某種程度上——被當今的議題推到了一邊。但這一切來得很快。
馬斯克：是的，來得非常快。我的意思是，我感覺我們正處於智能爆炸的大爆炸之中。就像我們身處其中——我們正在觀看。我們坐在場邊，見證著智能爆炸的大爆炸。有一點是肯定的，它不會無聊，所以——
費伯：不。你似乎不再像以前那樣頻繁地談論毀滅的可能性是20%了。
馬斯克：嗯，我認為我們應該始終考慮到可能存在一些不好的結果，並努力避免這種不好的結果。我們不想自滿，說一切都會好起來。不可能出現不好的結果。你知道，你知道，我有點用電影術語來思考這個問題，比如，我們是在《星際迷航》電影裏，還是在吉恩·羅登貝裏的電影裏，或者詹姆斯·卡梅隆的電影裏？我們究竟是哪一部電影？結果可能是羅登貝裏式的，也可能是卡梅隆式的。我認為在這種情況下，我們想要羅登貝裏式的結果。
費伯：是的。至於隨之而來的豐厚回報，埃隆，我們就到此為止吧。非常感謝你的再次采訪。顯然，我們還有很多話要說，所以我希望很快能再見到你。
馬斯克：很高興。
費伯：謝謝你抽出時間。
馬斯克：謝謝，非常感謝。
費伯：當然，特斯拉的首席執行官埃隆·馬斯克——他仍然想繼續擔任首席執行官。
馬斯克：插入公司名稱的首席執行官。
費伯：你現在會更頻繁地來這裏嗎？
馬斯克：我的意思是，這裏主要是——奧斯汀，特斯拉總部，也是我的主要住所。
費伯：你會完全想念白宮嗎？
馬斯克：我——我大致的計劃是每隔幾周去白宮待幾天。盡我所能提供幫助。
費伯：謝謝。好的，奧斯汀超級工廠的報道就到這裏。
CNBC Transcript: Elon Musk Sits Down for Secondary Interview with CNBC’s David Faber Live on CNBC Today
May 20, 2025
CNBC's “Closing Bell: Overtime”
Following is the unofficial transcript of a CNBC interview with Elon Musk, Tesla CEO, SpaceX CEO, xAI CEO & X Owner, and CNBC’s David Faber on “Closing Bell: Overtime” (M-F, 4PM-5PM ET) today, Tuesday, May 20. This is David Faber’s second interview with Elon Musk today. Following are links to video on CNBC.com:
https://www.cnbc.com/video/2025/05/20/tesla-ceo-elon-musk-theres-no-need-for-tesla-to-buy-uber.html,
https://www.cnbc.com/video/2025/05/20/tesla-ceo-elon-musk-no-plans-to-merge-tesla-and-xai.html.
Transcript of David Faber's first interview with Elon Musk today:
MANDATORY CREDIT: “CNBC”
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2. The onscreen “CNBC” logo must be clearly visible and unobstructed at all times in any image, video clip or other form of media.
3. Embedded web video must stream from the CNBC.com media player with the unobstructed credit as described above.
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DAVID FABER: Jon, thank you. And yes, it is a rarity to have sort of a twofer a nice little intermission. Elon Musk joining me again here at the Gigafactory in Austin. Thank you for coming back so many things we didn’t get to we were discussing Tesla. Obviously, it’s rare that I get this sort of interregnum. So let me just come to a question some people started to have after our last conversation seemed to come up. Why doesn’t Tesla buy Uber?
ELON MUSK: There’s no need, because we have a large number of cars. We have millions of cars that will be able to operate autonomously. And I should say that it’s a combination of a Tesla owned fleet and also enabling Tesla owners to be able to add or subtract their car to the fleet, so that existing Tesla owners will be able to earn money by adding their car to the fleet for autonomous use. And I think it’s maybe possible for Tesla owners to make more in how that in allowing the car to be added use the self driving fleet that then they then they cost them in the lease. And that’s why, I’d say, consider it sort of, sort of a business model that’s similar to some combination of of Airbnb and Uber. Just like Airbnb, you can rent out your spare bedroom or your your house if you’re not using it, and make money on it. And that’s what we expect Tesla customers to be able to do
FABER: Right And as this scales up, you obviously, you said earlier, you feel like you have the logistics ability and the ability to create the app as well. Of course, anything else around that that needs to occur?
MUSK: Yeah, I don’t think we’re missing anything. Tesla has all the ingredients necessary to offer a vast self driving fleet overnight.
FABER: Yeah, while I’m on the subject of deals, and this will take me actually, to XAI go a few places, but you know, I did note earlier in an interview you did earlier today, not with me. You’re busy, man. You do a lot of different media during the day sometimes.
MUSK: Yeah, a lot going on.
FABER: Yeah, you had indicated that you would like more control at Tesla,
MUSK: Yes. I mean, really, just enough control to not get ousted by activist investors at some point in the future
FABER: Yeah
MUSK: So that’s what I’ve said, is like some something
FABER: You’ve said that before
MUSK: Yeah something new, which is that around the sort of 25% level, you know, that means I, I can certainly be thrown out if I go crazy. But it really requires, you know, that’s the number that I that I feel kind of, you know, because it’s that that’s, that’s where I have, I have some control, but not so much control that I can’t be thrown out,
FABER: Right I understand you want 25 like, native control. There’s no real way at that level that you could be.
MUSK: No you can, if you, if you’re really, if you’re terrible, and, destroying the value of the company. And, well, or I’ve just gone flat, flat out crazy. But if you say it’s not, it’s not, it’s not real control. I mean, if you real control, would be like, say, you know Larry and Sergey at Google, but they, you know, anyone who has a majority voting control, which I wouldn’t have.
FABER: No understood, Zuckerberg has got it, Larry and Sergey. I know there are these companies where there is an absolute voting.
MUSK: You can commit murder and be in prison and still control the company.
FABER: Your economics are the same as your vote level, in this case.
MUSK: In this case yes, but I’d be happy to separate that, but I’m basically the exchanges. They’re not allowed to.
FABER: I know, I know they do. You know, you mentioned destroying the company, and obviously you’re not doing that. But sort of finish where we were talking about earlier. You don’t feel like you’ve damaged the company, though. You know, again, I come back to I want to move on to XAI as well. But 14 billion in EBIT in 2022 last year was 7.659 in EBIT, your gap operating margins, obviously are down, sales and all the markets last quarter were down. Do you see a turnaround coming? Do you look at yourself in the mirror and go, Man, you know, I got to do better. I got to be better.
MUSK: Look. I think the one can sort of look at individual quarterly results, and that’s neither here nor there. As I mentioned earlier, we did a massive global retooling of all the factory lines for the model Y, which is almost it’s majority of our vehicle sales is the model Y, and model Y is the best selling car on Earth any kind. So obviously, you know, for retooling the factory,
FABER: And a nice looking new, new model here too.
MUSK: Yeah, it looks like a transformer actually.
FABER: I know, of course, our camera, sorry, up there, that’s the shot. There it is, yeah, Optimus subprime, yeah.
MUSK: So, but the really, the best indicator of the forward value the company is the share price of the market cap, and that’s very strong right now.
FABER: No, and it’s and it’s rebounded to over a trillion dollars. Obviously, it’s up sharply over the last year. A lot of it has to do, though, as we said earlier, with autonomous the Robotaxi, and I keep pointing behind me, our viewers can’t see it, but, but Optimus, the robot, you said recently 10s of billions of robots, but that’s decades away,
MUSK: At least one decade away.
FABER: It’s got to be more than that.
MUSK: It’s going to grow very fast.
FABER: Why do you think that?
MUSK: I think, I think humanoid robots will be the biggest product ever. The demand will be insatiable. Everyone’s gonna want one, basically, who wouldn’t want their own personal C3PO or R2D2. Everyone’s going to want one.
FABER: You’ve said that. And you know your your goal, you’ve also said is to produce a million robots, I think by 2030 that’s what I had you on the record as saying,
MUSK: I think that’s a reasonable target.
FABER: And then, and then start towards sustainable abundance, which you can get into. You know, I wonder we’ve been talking about autonomous and how long it takes, it takes to train the automobile to be able to be the equivalent of or exceed human capabilities. But what about these robots, to the extent that how much training are they going to need to actually be able to do various different types of tasks? Is that something that is going to take a long time.
MUSK: A lot of training yes, it’s going to take a lot of computer resources, and it’ll take, it’ll take time. I think there’s certain threshold breakthroughs that that we think we can achieve, where, if, if optimus can watch videos, YouTube videos, or how to videos, or whatever. And based on that video, just like a human can learn how to do that thing, then you really have task extensibility that is dramatic, because then it can learn anything very quickly. So I think we’ll get there in the next.
FABER: We’re not there yet, though.
MUSK: We’re not there yet
FABER: You’re relying on a significant uptick in terms of learning and training.
MUSK: Yeah, no, that’s—
FABER: And commute.
MUSK: That’s why I’m calling it a very significant threshold would be—
FABER: Understood.
MUSK: The ability to learn from watching a video, just so—
FABER: Right.
MUSK: But at the point we’re—
FABER: As opposed to watching a human right, which is, or having a human sort of train it right now with a task.
MUSK: Yeah, right. Right now, we’re really, we’re training an Optimus to do like primitive tasks where a human in a kind of a, what’s called a Mocap suit is and sort of cameras on the head is moving in the way that the robot would move to, say, pick up an object or open a door, or the basic tasks, throw a ball, dance, and we need to that I think that’s needed to sort of bootstrap the intelligence so you can have the basic functions. Then where I think it gets very interesting, and very much like humans, is that you want the robot to self-play. So you say, how does a child learn? Well, a child has toys and a child plays with the toys. Plays with the blocks. At some point, figures how to put the triangle in the triangle hole and the circle in the circle hole by doing it over and over again. And this the self-play. Once you have a lot of robots, you can do this self-play, which is that you just put the robot in a room with toys and have the robot, literally have the robot play with toys.
FABER: And it will learn.
MUSK: Yeah. And you have to have a reward function. Say, like, okay, the goal of the robot is to put, you know, that classic child’s toy. You put the circle in the circle hole, the square in the square hole, triangle in the triangle hole, and keep doing it until it works and the reward function is succeeding.
FABER: And there are no advances needed to accomplish that now? I mean, no advances in AI or just compute and things of that nature that can happen?
MUSK: There are some advances needed, but I don’t think these are insurmountable. I think we I think we can, we can solve these things in the next few years.
FABER: Okay, so at that time when millions of these things are coming off a line like we just, you know, saw with cars, they’re going to be fully autonomous, they’re going to come off and—
MUSK: Oh yeah.
FABER: I mean, what you’ve described—
MUSK: In five years, of course.
FABER: Come in my house, and I’m gonna be able to say, alright, do the dishes. Now I need you to walk the dog.
MUSK: Absolutely.
FABER: Hold the baby.
MUSK: In fact, you really won’t even need to it’ll it’ll figure out what you probably want and and do what you probably want without you even having to ask.
FABER: How many GPUs are you going to need for that?
MUSK: Well, quite a few GPUs. We do have our own program called Dojo for training, which I think will be helpful.
FABER: Right now, it’s contributing about 5% towards self-driving, right?
MUSK: Yeah, so—
FABER: Is that the one in New York? In New York State?
MUSK: Yeah, yes, in New York. So we expect to still buy a lot of GPUs from Nvidia, some from AMD, and maybe from others. And as long as Nvidia is better than what we make, we’ll keep buying from Nvidia.
FABER: Is that the case right now?
MUSK: It is, yeah.
FABER: Yeah. I mean, you’re obviously buying them for xAI, the Memphis—
MUSK: Big time.
FABER: Big time, right?
MUSK: Yeah. xAI is building the most powerful, we have the, we have the most powerful, I think we have the most powerful training cluster in the world right now, which is over 200,000 GPUs, training coherently.
FABER: You’re at 200,000 already now.
MUSK: Yes.
FABER: There in Memphis, that facility that—
MUSK: Yes.
FABER: Okay
MUSK: Yes.
FABER: And where are you going?
MUSK: And the, we’ll be at the million GPU level in a location just near Memphis.
FABER: Wait a million GPUs for a new location, or 800,000 additional GPUs.
MUSK: A million, a million of the next generation GPUs.
FABER: So Blackwell.
MUSK: Well, yeah.
FABER: Wait, are you building that now?
MUSK: Yeah.
FABER: How are you powering that?
MUSK: It’s a gigawatt class system.
FABER: What, do you have the power lined up for that?
MUSK: Yeah.
FABER: You do. Natural gas or—
MUSK : It is. It is a hard problem.
FABER: It’s a, which is the hard problem. Finding the power?
MUSK: Getting the gigawatts, bringing, bringing a gigawatt online and actually having the gigawatts of power be reliable, because you get the power fluctuations in the grid and whatnot. So we’re using, actually, I just posted something online today which is a whole bunch of Tesla megapacks, batteries that are important for power conditioning the grid so that GPUs do not like power fluctuations. They’re like, they like a power steady so and then, if there are sometimes there’s slight brownouts, or for this blackout, you want to have be able to carry through that like an uninterruptible power supply. So, so we got a lot of megapacks there to support—
FABER: To support that. Do you see—
MUSK: It’ll be, it’ll be the first gigawatt class training cluster in the world, and the most powerful training cluster.
FABER: When is that going to be done?
MUSK: Hopefully, in about six months, maybe nine months.
FABER: And that’s largely powering Grok?
MUSK: Yes.
FABER: Yeah.
MUSK: It’s just powering Grok.
FABER: Right. Which continues to advance. I mean, I use it frequently.
MUSK: Yeah.
FABER: I saw you using that on the Joe, was it with Rogan when you were using that mode? What is that mode? Where it’s all sassy and curses all the time.
MUSK: Well there’s, I mean, if you want to have fun at parties, Grok unhinged mode is pretty funny.
FABER: Yeah.
MUSK: It’s next level.
FABER: Yeah. Is power going to be the gating issue for our ability to continue to advance in AI?
MUSK: Yeah, I think we’re, I mean, a few years ago, I made a very obvious prediction which is that the limitation on AI will be chips. And it’s still chips, kind of chips today, then it will be electrical equipment for the because you need to take power at that might be at 300,000 volts, all the way down to 400 volts for the for the computer. So it’s, you need to step down transformers, and a lot of them, and a lot of, you know, cabling and wiring and fuses. And I, you know, it’s a lot of transformers, essentially. And the electrical transformer industry is not used to big changes in demand.
FABER: Now there’s a shortage of transformers today.
MUSK: Literally the shortage of transformers. And then, funnily enough, the the the AI algorithm, is called a transformer. And then our Optimus robot is named after Optimus Prime. That’s a transformer robot.
FABER: It’s a lot.
MUSK: So we’re transformers for transformers for transformers.
FABER: Right, right, but it’s the one, the one transformer is the one in shortage that the others need.
MUSK: And then as we solve the transformer shortage, there’ll be the fundamental electricity generation shortage.
FABER: And are we there yet? Or are we going to be there soon?
MUSK: We’re getting there soon.
FABER: We are.
MUSK: My guess is people are going to start getting challenges with power generation, maybe by middle of next year, end of next year.
FABER: Even with deregulation and an effort being made to perhaps move -- along more quickly.
MUSK: How many power plants are getting built and how fast can you build a power plant?
FABER: Right, right. China seems to be building them pretty quickly.
MUSK: China is building – China has so many power plants that have been built and are being built. I don’t think people quite realize this. I posted on my X account just the graph of U.S. power generation versus China power generation. China power generation is like, looks like a rocket going to orbit, and U.S. power generation is flat.
FABER: Right.
MUSK: So I think by the end of this year, China will have about two and a half times the power output of the United States, and it’s headed towards maybe three or four times the power output of the United States.
FABER: It’s funny, when you think about China, I mean, EVs, autonomous, we talked about batteries, solar, power generation – by the way, even biotechnology recently. I don’t know if you saw Pfizer’s licensing cancer drugs.
MUSK: Yeah.
FABER: They seem to be, I don’t know. I’ll ask you the question. Are they ahead of us in certain areas that are important?
MUSK: The United States still has an advantage in breakthrough innovation, but – so it’s the United – and I think it’s somewhat of a cultural thing, which is that to have breakthrough innovation, you have to question authority. That fundamentally your breakthrough, you’re questioning the conventional wisdom when you do a breakthrough innovation.
FABER: Right.
MUSK: And you know, China, they don’t generally like to question their authority, or that’s just not as encouraged as it is in the U.S. on questioning authority.
FABER: No. But they do seem to be good at finding something and then making it better. And scaling.
MUSK: Yeah, I do want to emphasize that the sheer number of smart, talented people in China who work very hard is amazing. The amount of – there’s just the sheer quantity of talent. I mean, I’m an admirer of China’s capabilities. I think, I think most people outside of China do not understand the power of China. It really is something, something special.
FABER: Yeah, yeah. You know, in the time we have left, I would like to sort of keep the focus on xAI. First of all, you know, you spoke earlier about wanting more control at Tesla. Would you ever consider merging xAI into Tesla? It would be a way, obviously, that they could issue shares to you and conceivably would increase your overall economics. Is that a possibility?
MUSK: Well, I guess anything’s possible, but it would be difficult to speculate about something – you know, Tesla’s a publicly traded stock so –
FABER: Yes, I would think to get a majority of the minority vote, or whatever you might need, might be not easy.
MUSK: Yeah. It’s not out of the question, but that would have to be something that the Tesla shareholders would vote – would want to vote for, so –
FABER: Understood So, but it’s not something you’re thinking about doing?
MUSK: It’s not currently. It’s not currently – there are no plans to do so.
FABER: Right.
MUSK: It’s not out of the question, but obviously would require Tesla shareholders support for them.
FABER: Another way you could obviously increase your control would be to get that comp plan passed in Delaware or through the Delaware Supreme Court. Or a new one. You haven’t been paid, I believe, since 2018.
MUSK: Yeah.
FABER: So where are you on –
MUSK: Seven years.
FABER: Yeah. Where are you on –
MUSK: Seven years with zero pay.
FABER: Although, to be fair, if it goes through, you’re gonna have an enormous, enormous pay day.
MUSK: Yeah it will be fine. Sure.
FABER: It will be fine? You’ll have more money than everybody’s ever made.
MUSK: Yeah, I suppose so. But I mean, I would, let’s just say that if any CEO of the Fortune 500 were to agree to a plan like the one that I agreed to, you should buy the stock in that company immediately.
FABER: Yeah. No, I remembered at the time, to be fair, the stock was so far – the targets were so far above where the stock was, and obviously they were met.
MUSK: Yes.
FABER: Is the board working to your knowledge, on another potential plan if, in fact, that one never gets out of Delaware, the Supreme Court rules against the Chancellor’s ruling?
MUSK: I mean, I don’t want to speak on behalf of the board, but, you know, I’m sure it’s on their mind. But you know this, I can’t comment on Tesla board deliberations.
FABER: You said earlier. I mean, you want to stay as CEO. Why not – you know, I wonder, Elon, given all the heat you’ve gotten in a lot of ways, why not sort of become like an Ellison-like figure at Tesla? Obviously, you’re a lot younger, but still, he’s very influential at Oracle. But you know, he’s not CEO, and he doesn’t get the attention.
MUSK: He isn’t the CEO?
FABER: No, he’s not. Safra’s the CEO.
MUSK: Oh, okay.
FABER: Yeah. At least not in title. That’s a good point.
MUSK: No, no I think maybe a better term for – I’m a huge fan of Larry Ellison’s, good friend of mine. Owner.
FABER: Say it again?
MUSK: Owner, I think would be – he’s the owner of Oracle.
FABER: Yes, yes, he is. And he has a lot of it. Finally, I want to –
MUSK: He’s not the CEO, he’s just the owner.
FABER: He’s the owner. Yeah, it’s a big percentage, a lot higher than yours, actually at Tesla.
MUSK: Yes – price and percentage at Oracle.
FABER: Finally, I want to, I mean, so many things we haven’t gotten to, but we’re trying to keep to your time. Are we ready for the changes that AI is going to bring to this society? You know, I try in my job every day to sort of follow them. Obviously, we’ve been pushed – they’ve been pushed aside to a certain extent by issues of the day. But it’s coming fast.
MUSK: Yeah. It’s coming very fast. I mean, I feel like we’re, you know, we’re in the big bang of the intelligence explosion. Like we’re in – we’re watching. We have courtside seats to the big bang of intelligence explosion. One thing’s for sure, it won’t be boring, so –
FABER: No. You don’t seem to be saying there’s a 20% chance of annihilation as often anymore.
MUSK: Well, I think we should always consider that there’s some chance of a bad outcome, to try to protect against the bad outcome. We don’t want to be complacent and say that everything’s just going to be fine. There’s no chance of a bad outcome. You know, you know, I sort of think of this maybe in movie terms, as like, are we in a Star Trek movie or like are we in a Gene Roddenberry movie or a James Cameron movie? Which movie are we in here? And you could either have a Roddenberry or a Cameron outcome. And let’s, I think in this case, we want the Roddenberry outcome.
FABER: Yeah. And the abundance that may come with it, Elon, we got to stop there. I certainly appreciate your coming back. Obviously, there’s so much more we can talk about so I hope we’ll see you again soon.
MUSK: Pleasure.
FABER: Thank you for your time.
MUSK: Thank you appreciate it.
FABER: Elon Musk, CEO, of course, of Tesla – still the CEO, wants to be.
MUSK: CEO of insert company name.
FABER: You going to be back here more often now?
MUSK: I mean, this is mainly – Austin, Tesla headquarters, is where –is my main residence.
FABER: Are you going to miss the White House at all or no?
MUSK: I’ll – my rough plan on the White House is to be there for a couple days every, every, every few weeks. And to be helpful where I can be helpful.
FABER: Thank you. All right, that does it from the Gigafactory in Austin back to you guys.
