# Billionaire's WARNING: I'm SELLING. The Crash Is Already Here!

https://www.youtube.com/watch?v=32u5T6lO8qk
Translation: zh-TW

[00:00] What advice do you give for the average person that's looking to invest their salary or their wages?
  對於尋求投資薪水或工資的普通人，您有什麼建議？

[00:04] Don't own US stocks.
  不要持有美國股票。

[00:06] That's a simple strategy that you can act on.
  這是一個您可以採取的簡單策略。

[00:08] But what about S&P 500?
  但標準普爾 500 指數呢？

[00:10] No.
  不。

[00:11] Really?
  真的嗎？

[00:11] Yeah.
  是的。

[00:11] And if you have a big position in US technology stock, I personally advise would be to sell them all.
  如果您持有大量美國科技股，我個人建議全部賣掉。

[00:17] But I'm an investor in SpaceX.
  但我也是 SpaceX 的投資者。

[00:17] Good luck.
  祝你好運。

[00:18] SpaceX is such a fabulous uh story, and we can go into that.
  SpaceX 是一個如此精彩的故事，我們可以深入探討。

[00:22] Crypto?
  加密貨幣？

[00:23] No.
  不。

[00:23] Why?
  為什麼？

[00:24] It's an unnecessary piece of nonsense that facilitates nothing except criminals moving money that they can't be seen.
  這是一件不必要的廢話，除了讓罪犯能夠隱藏地轉移資金外，什麼也促進不了。

[00:31] Do you think Bitcoin's going to go to zero?
  您認為比特幣會歸零嗎？

[00:32] Yes, it will certainly go to zero.
  是的，它肯定會歸零。

[00:34] So, how many years have you spent investing?
  那麼，您花了多少年時間投資？

[00:36] 60 years.
  60 年。

[00:36] And what's the most amount of money you've ever managed of other people's money?
  您管理過最多的其他人的錢是多少？

[00:40] 165 billion.
  1650 億。

[00:41] And one of the things you're famous for talking about is this idea of bubbles.
  您以談論泡沫這個概念而聞名。

[00:45] Yes.
  是的。

[00:45] And bubbles always occur around the very most important ideas.
  泡沫總是圍繞著最重要的想法出現。

[00:49] So, the railroads, everyone could see that it would change the world.
  所以，鐵路，每個人都看得出來它將改變世界。

[00:51] The same with the internet.
  網際網路也是如此。

[00:52] And everyone wanted to put their money in, and so they over invested.
  每個人都想把錢投入進去，所以他們過度投資了。

[00:55] But this is the problem.
  但這就是問題所在。

[00:58] Eventually, they burst.
  最終，它們會破裂。

[00:59] And if you look at the great
  如果您看看偉大的

[01:01] bubbles breaking of the past, you find that it's followed by really tough times, a miserable period for the economy.
  過去的泡沫破裂，你會發現緊隨其後的是非常艱難的時期，經濟的悲慘時期。

[01:06] And the bigger the bubble, the bigger the burst.
  泡沫越大，破裂就越嚴重。

[01:08] And now we're in the biggest investment bubble that arguably has ever occurred, AI.
  而現在我們正處於可以說是史上最大的投資泡沫，人工智能。

[01:14] Are we on the verge of a collapse with AI in the coming years?
  在未來幾年，人工智能會讓我們瀕臨崩潰嗎？

[01:17] The next few days, the next few weeks, [music] the next few months, but certainly the next few years.
  未來幾天，未來幾週，[音樂] 未來幾個月，但肯定也是未來幾年。

[01:21] So, if you're not someone that has a huge amount of savings, what kind of strategy should they be adopting when an economy starts to get bad and there's a economic bubble collapse?
  所以，如果你不是一個擁有巨額儲蓄的人，當經濟開始變糟並且出現經濟泡沫破裂時，他們應該採取什麼樣的策略？

[01:30] So, I would go through everything.
  所以，我會仔細審視一切。

[01:32] But you will not receive this advice from investment advisers because they'll lose a lot of business.
  但你不會從投資顧問那裡得到這些建議，因為他們會失去很多生意。

[01:37] And would you be thinking about the country you live in at this moment in time?
  而你此刻會考慮你居住的國家嗎？

[01:41] Absolutely.
  絕對會。

[01:41] Is there any countries you wouldn't live in?
  有哪個國家是你不會想住的嗎？

[01:43] I think I have to refuse to answer this on the grounds that it might tend to incriminate me.
  我想我必須拒絕回答這個問題，因為這可能會讓我入罪。

[01:47] Oh, okay.
  哦，好的。

[01:47] So, you're saying don't live in the United States.
  所以，你的意思是不要住在美国。

[01:48] I've just moved here.
  我剛搬到這裡。

[01:50] Why not the United States?
  為什麼不是美國？

[02:00] This is super interesting to me.
  這對我來說非常有趣。

[02:00] My team
  我的團隊

[02:01] gave me this report to show me how many of you that watch this show subscribe.
  給我這份報告，告訴我觀看此節目並訂閱的你們有多少人。

[02:04] And some of you have told us, according to this, that you are unsubscribed from the channel randomly.
  你們中的一些人告訴我們，根據這個，你們被隨機取消了頻道的訂閱。

[02:08] So, favor to ask all of you, please could you check right now if you've hit the subscribe button if you are regular viewer of the show and you like what we do here.
  所以，請求你們所有人，請你們現在就檢查一下是否按下了訂閱按鈕，如果你是本節目的常客，並且喜歡我們在這裡所做的一切。

[02:14] We're approaching quite a significant landmark on this show in terms of a subscriber number.
  在訂閱人數方面，我們即將在本節目中達到一個重要的里程碑。

[02:19] So, if there was one simple, free thing that you could do to help us, my team, everyone here, keep this show free, to keep it improving year over year and week over week, it is just to hit that subscribe button and to double-check if you've hit it.
  所以，如果有一件簡單、免費的事情可以幫助我們、我的團隊、這裡的每一個人，讓這個節目免費，讓它年復一年、週復一週地進步，那就是按下訂閱按鈕，並再次檢查你是否已經按下了。

[02:29] Only thing I'll ever ask of you.
  我唯一會向你們請求的事情。

[02:33] Do we have a deal?
  我們達成協議了嗎？

[02:34] If you do it, I'll tell you what I'll do.
  如果你們這樣做，我會告訴你們我會做什麼。

[02:35] I'll make sure every single week, every single month, we fight harder and harder and harder and harder to bring you the guests and conversations that you want to hear.
  我會確保每週、每月，我們都會更加努力地奮鬥，為你們帶來你們想聽的嘉賓和對話。

[02:42] I've stayed true to that promise since the very beginning of The Diary of a CEO, and I will not let you down.
  自從《CEO日記》創立之初，我就一直信守這個承諾，我不會讓你們失望。

[02:45] Please help us.
  請幫助我們。

[02:48] Really appreciate it.
  真的非常感謝。

[02:49] Let's get on with the show.
  讓我們開始節目吧。

[02:51] [music]
  [音樂]

[02:54] Jeremy Grantham.
  傑瑞米·格蘭瑟姆。

[02:56] Your firm managed up to 165 billion dollars at its peak, what you we call
  你們公司巔峰時期管理著高達1650億美元的資產，我們稱之為

[03:02] AUM, assets under management.
  資產管理總額，即資產管理。

[03:05] So, you know a lot about money.
  所以，你對金錢瞭若指掌。

[03:06] You know a lot about investing.
  你對投資瞭若指掌。

[03:08] How do you sort of self-define your expertise because you traverse so many different subjects through your work?
  你如何定義你的專業知識，因為你的工作涉及如此多不同的主題？

[03:14] So, if I said to you, you know, how do you introduce yourself professionally?
  所以，如果我問你，你如何專業地介紹自己？

[03:16] What is the answer?
  答案是什麼？

[03:18] I can't think I ever do introduce myself professionally, but I think of myself as specializing in a longer term horizon.
  我想我從未專業地介紹過自己，但我認為自己專注於更長遠的視野。

[03:25] [clears throat]
  [清喉嚨]

[03:25] than most people and trying to look at a higher and higher level of abstraction.
  比大多數人，並試圖以越來越高的抽象層次來看待事物。

[03:30] What is really going on here?
  這裡到底發生了什麼？

[03:32] And what are people missing?
  人們錯過了什麼？

[03:34] I've discovered over decades that humans are incredibly short-term oriented.
  幾十年來我發現，人類極度關注短期。

[03:40] And they have an enormous predisposition to optimism.
  他們有極大的樂觀傾向。

[03:44] They're looking for optimistic news in everything.
  他們在一切事物中尋找樂觀的消息。

[03:46] They're looking to avoid unpleasantness.
  他們試圖避免不愉快的事情。

[03:48] The idea that you can have steady compound growth is ridiculous.
  能夠持續複利增長的想法是荒謬的。

[03:53] One of my few heroes, Kenneth Boulding, an economist, he said the only people who think you can have compound growth on a finite planet are madmen and economists.
  我為數不多的偶像之一，經濟學家 Kenneth Boulding 說過，認為在有限的地球上可以有複利增長的人，只有瘋子和經濟學家。

[04:05] Which is so accurate.
  這點非常準確。

[04:07] Economists simply believe you can have growth always, and everything comes down to just price.
  經濟學家們 просто 相信你總是可以實現增長，而一切都歸結為價格。

[04:13] One of the things you're famous for talking about is this idea of bubbles,
  你以談論泡沫這個概念而聞名，

[04:17] and we're living in a moment where everybody's talking about the subject of artificial intelligence, and everyone's getting very excited by it.
  我們正處於一個每個人都在談論人工智能的時刻，每個人都對此感到非常興奮。

[04:23] Some people are getting very pessimistic about the impact it'll have on society.
  有些人對它將對社會產生的影響感到非常悲觀。

[04:27] I wanted to start there because it's a it's an area where there is rife optimism on one side of things, um but there's also a lot of money plowing into the market,
  我想從那裡開始，因為它是一個充滿樂觀情緒的領域，但也有大量的資金湧入市場，

[04:35] which is I I guess in your view making things prone to collapse.
  我猜在你看來，這使得事物容易崩潰。

[04:40] What's your view on artificial intelligence?
  你對人工智能有什麼看法？

[04:41] You said you're good at understanding what people are missing.
  你說你擅長理解人們錯過了什麼。

[04:44] What is it that people are missing?
  人們到底錯過了什麼？

[04:45] Well, first of all, let me say I think artificial intelligence is right up there with the railroads.
  嗯，首先，我想說我認為人工智能與鐵路一樣重要。

[04:49] It's one of the defining great ideas of the last couple of hundred years.
  它是過去幾百年來定義性的偉大思想之一。

[04:57] It's going to change everything.
  它將改變一切。

[04:59] And that is critical.
  這一點至關重要。

[05:01] If you If you mean to have a bubble, people think that a bubble is a mainly because it's a scam,
  如果你說有泡沫，人們認為泡沫主要是因為它是個騙局，

[05:05] and nothing could be further from the truth.
  而這再真實不過了。

[05:07] The great bubbles always occur around the very most important ideas.
  巨大的泡沫總是圍繞著最重要想法的出現。

[05:12] So, the railroads, everyone could see that it would change the world.
  所以，鐵路，每個人都能看到它將改變世界。

[05:16] And everyone wanted to put their money in, and everybody put their money in.
  每個人都想把錢投進去，而且每個人都把錢投進去了。

[05:20] They over invested, and even though the railroads were a spectacularly powerful idea,
  他們過度投資了，儘管鐵路是一個非常強大的想法，

[05:26] uh the railroads uh collapsed their stocks, and everybody lost a ton of dough.
  呃，鐵路的股票崩盤了，每個人都損失了一大筆錢。

[05:31] The same with the internet.
  互聯網也是一樣。

[05:33] And then out of the wreckage, the railroads changed the world, and and the internet changed the world.
  然後從殘骸中，鐵路改變了世界，互聯網也改變了世界。

[05:41] What we have to remember is that
  我們必須記住的是

[05:43] in '99, Amazon went up six or seven times.
  在99年，亞馬遜上漲了六七倍。

[05:45] In the crash in the tech bubble, it went down 92%.
  在科技泡沫破裂時，它下跌了92%。

[05:50] As I like to say, check it.
  正如我喜歡說的，去查一下。

[05:52] It's such a remarkably large number.
  這是一個非常驚人的數字。

[05:54] And then out of the wreckage, it inherited the retail world.
  然後從殘骸中，它繼承了零售業的世界。

[05:58] And uh that's that's how it works.
  呃，這就是它的運作方式。

[06:00] The greater the idea, the more obvious the idea, the more money goes in, and the bigger the bubble, and the bigger the
  想法越偉大，想法越明顯，投入的資金越多，泡沫就越大，

[06:06] Bust.
  崩潰。

[06:07] And are we on the verge of a collapse with AI?
  我們是否正處於 AI 崩潰的邊緣？

[06:08] When I say verge, I mean over the coming years.
  我說邊緣，指的是未來幾年。

[06:11] If you look at the data, it would be compatible with history for the peak to be very soon.
  如果你看數據，這與歷史上很快達到頂峰的說法是相符的。

[06:18] Everything is in line.
  一切都在軌道上。

[06:18] This is, I think, the biggest investment bubble in American history.
  我認為，這是美國歷史上最大的投資泡沫。

[06:23] The indicators of pure crazy euphoria, like SpaceX, are all over the place.
  純粹瘋狂的狂熱指標，例如 SpaceX，隨處可見。

[06:31] SpaceX defines as its addressable market a quarter of the global GDP.
  SpaceX 將其可尋求市場定義為全球 GDP 的四分之一。

[06:38] You know, it talks about endless opportunities mining asteroids.
  你知道，它談論著開採小行星的無限機會。

[06:43] It will be in 50 years, people and 100 years, people will look back and tell stories about SpaceX and its prospectus, like they tell stories about the South Sea bubble.
  在 50 年後，人們和 100 年後，人們回顧時會講述 SpaceX 及其招股說明書的故事，就像他們講述南海泡沫的故事一樣。

[06:52] You know, an enterprise of such enormous value, but it cannot at this time be revealed.
  你知道，一個如此巨大的企業價值，但目前無法揭露。

[06:58] I want to keep on this train, but for the viewers that don't know your experience, we should probably pause and just tell them your experience, because that's the reference point, but also
  我想繼續這個話題，但對於不了解你經驗的觀眾，我們可能應該暫停一下，直接告訴他們你的經驗，因為那是參考點，但同時也

[07:07] also gives you credibility and authority to speak to this.
  也賦予您說服這件事的信譽和權威。

[07:09] What have you done with your life?
  您一生中做了什麼？

[07:12] Well, I got into the investment business in 1968.
  嗯，我在 1968 年進入了投資行業。

[07:17] There were very few serious people in the investment business.
  投資行業裡很少有認真的人。

[07:21] There were no mathematical models.
  沒有數學模型。

[07:23] There were the kind of relatively failed sons of rich people who would work for J.P. Morgan.
  有一些富人的失敗的兒子，他們會在摩根大通工作。

[07:30] And then over the next 10 years, it began to get a little more serious.
  然後在接下來的 10 年裡，它開始變得稍微嚴肅一些。

[07:35] T. Rowe Price introduced the idea of growth stocks.
  T. Rowe Price 提出了成長股的概念。

[07:37] A few of us introduced the idea of value stocks.
  我們中的幾個人提出了價值股的概念。

[07:41] And a few years later, at my first firm, Battery March Fee, really introduced the idea of small small cap.
  幾年後，在我最初的公司 Battery March Fee，真正提出了小型股的概念。

[07:46] It hadn't existed before that.
  在此之前它並不存在。

[07:50] And for people that don't know, a small cap is investing in smaller companies.
  對於不知道的人來說，小型股就是投資於較小的公司。

[07:54] Yes.
  是的。

[07:54] And a value stock is simply one that looks cheap.
  而價值股只是一種看起來便宜的股票。

[07:57] Did you invent the index fund?
  您發明了指數基金嗎？

[08:00] There were two or three of us separately.
  我們有兩三個人是分開的。

[08:01] I don't think we knew of each other.
  我不認為我們知道彼此。

[08:04] How many years have you spent investing?
  您花了多少年投資？

[08:06] Uh 60, approximately.
  呃，大約 60 年。

[08:08] 60. And what's the the most amount of money you've ever managed for other people in a calendar year?
  六十。您有史以来在一个日历年内为他人管理的最高金额是多少？

[08:15] Yes, 165 billion.
  是的，1650亿。

[08:18] I had a two partners, Mayo and Van Ottalo.
  我有两位合伙人，Mayo 和 Van Ottalo。

[08:22] And when the smoke cleared, you know, I'd made a lot of money, over a billion dollars.
  当尘埃落定后，你知道，我赚了很多钱，超过了十亿美元。

[08:27] Personally?
  个人而言？

[08:28] Personally.
  个人而言。

[08:29] And how much And paid tax on all of it.
  而且支付了所有税款。

[08:31] Oh, good.
  哦，好。

[08:33] And how And how much money does your firm still manage today of other people's money?
  您的公司今天仍然管理着多少其他人的钱？

[08:37] It manages 85 billion.
  它管理着850亿。

[08:39] 85 billion. So, are you a billionaire?
  850亿。那么，您是亿万富翁吗？

[08:42] I'm generally referred to as a billionaire, but that's only because they count the money you give away.
  我通常被称为亿万富翁，但那是因为他们计算了您捐赠出去的钱。

[08:49] Because I've given over 90% of my billion away to a foundation.
  因为我已经将我十亿中的90%以上捐赠给了一个基金会。

[08:55] Oh, really?
  哦，真的吗？

[08:56] Yeah.
  是的。

[08:57] To which foundation?
  哪个基金会？

[08:58] It's called the Grantham Foundation for the Protection of the Environment.
  它叫做格兰瑟姆环境保护基金会。

[09:01] We invest a lot of our principal in green tech to help combat climate change.
  我们将大部分本金投资于绿色科技，以帮助应对气候变化。

[09:07] And you're 87 years old.
  您今年87岁。

[09:09] And I'm 87 years old.
  我87歲了。

[09:10] You've given 90% of your money away to your own foundation that's focused on green tech.
  你已將90%的錢捐給了你自己的基金會，該基金會專注於綠色科技。

[09:15] Yeah.
  是的。

[09:15] Maybe 95.
  也許95%。

[09:15] Yeah.
  是的。

[09:17] Wow.
  哇。

[09:17] Okay.
  好的。

[09:17] So, coming back to this point that we were talking about, a lot of people won't even know what a bubble is.
  所以，回到我們剛才談到的這個點，很多人甚至不知道什麼是泡沫。

[09:21] I think you've done a good job of explaining.
  我認為你解釋得很好。

[09:22] A bubble is when everyone gets excited, they all see something obvious, they plow their money in, their stocks go up, and then if you look at the graph that's in front of you there, which shows his the history of asset bubbles, eventually there's a big collapse.
  泡沫就是當每個人都興奮起來，他們都看到明顯的東西，他們投入資金，他們的股票上漲，然後如果你看看你面前的圖表，它顯示了資產泡沫的歷史，最終會出現一次大崩潰。

[09:37] Yeah.
  是的。

[09:37] And you're saying that we're the collapse is on the horizon.
  而你說崩潰即將來臨。

[09:42] Yes.
  是的。

[09:43] And what does that mean for the average person?
  這對普通人意味著什麼？

[09:46] What's going to happen?
  會發生什麼？

[09:47] What's going to happen is the high flyers will probably come down a lot.
  將會發生的是，高飛的股票可能會大幅下跌。

[09:52] The high flyers?
  高飛的股票？

[09:54] The stocks that have gone up the most, AI and the more exciting stocks with the biggest moves historically would be expected to come down the most.
  那些漲幅最大的股票，人工智能和那些歷史上漲幅最大的令人興奮的股票，預計將會下跌最多。

[10:05] From these unprecedented levels a 70% decline would not be unexpected.
  從這些前所未有的水平來看，70%的跌幅並非不可能。

[10:11] So a 70% decline in the in the stock price?
  所以股票價格下跌了70%？

[10:14] Yeah.
  是的。

[10:14] And you have to remember the tech bubble the Nasdaq, which is an index of the growth stocks, came down 82%.
  而且你必須記住科技泡沫，納斯達克，這是成長股的指數，下跌了82%。

[10:24] It is far from unprecedented to have these major declines.
  發生這些重大下跌絕非前所未有。

[10:27] And the biggest bubble in history was in the Japanese stock market in 1989.
  而歷史上最大的泡沫是1989年的日本股市。

[10:33] Back then Japan seemed to rule the world, all the technology, all the Toyotas were kicking bottoms in General Motors and so on.
  當時日本似乎統治著世界，所有的科技，所有的豐田汽車都擊敗了通用汽車等等。

[10:42] And everyone bragged about their 12-in Sony TV in the kitchen and the quality etc. etc. little things you put on your belt to play music, they were all Japanese.
  每個人都誇耀他們廚房裡的12英寸索尼電視和質量等等。你放在皮帶上播放音樂的小東西，它們都是日本製造的。

[10:51] Mhm.
  嗯哼。

[10:52] And [clears throat] uh for a second Japan sold for more than the US in '89.
  而且[清喉嚨]呃，有一段時間，日本在89年的銷售額超過了美國。

[10:58] And it it got to 65 times earnings, which which means for every dollar of earnings you have $65 of market value.
  而且它達到了盈利的65倍，這意味著你每賺一美元，就有65美元的市場價值。

[11:08] And the US went to 35 in the tech bubble of 2000.
  而在2000年的科技泡沫中，美國達到了35倍。

[11:13] You could argue depending on how you do it that it's 35 or 40 today, but it's not 65.
  你可以爭辯說，取決於你如何做，今天它是35或40，但它不是65。

[11:18] So we have seen a much bigger bubble in Japan.
  所以我們在日本看到了更大的泡沫。

[11:20] And what happened?
  發生了什麼？

[11:23] It went up and up and up and then it came down for 20 years.
  它不斷上漲，然後下跌了20年。

[11:28] 20 years?
  20年？

[11:29] 20 years.
  20年。

[11:31] They talk about the lost decade, but when you look at it closely, it looks more like a lost 20 years.
  他們談論失去的十年，但當你仔細看時，它看起來更像是失去的20年。

[11:35] So, for the average person, what do they feel and how does it impact them when there's a market crash like the one that you're forecasting?
  那麼，對於普通人來說，當市場像你預測的那樣崩盤時，他們有什麼感覺，這會對他們產生什麼影響？

[11:44] The high flyers will lay people off and and a lot of people will feel less rich.
  高飛者將裁員，許多人會覺得自己不那麼富裕了。

[11:50] And as you acquire uh money in the stock market, a small fraction of that, two or three percent, is spent.
  而且當你在股票市場賺取一些錢時，其中一小部分，百分之二或百分之三，會被花掉。

[11:58] And in reverse, it goes back.
  反過來，它又會回去。

[12:02] And people feel a little bit poorer, they spend a little less.
  人們感覺自己窮了一點，花費也少了一點。

[12:06] So, the economy tends to be under some stress.
  所以，經濟往往會承受一些壓力。

[12:09] And if you look at the great bubbles breaking of the past, you find
  如果你看看過去的偉大泡沫破裂，你會發現

[12:14] that it's followed by really tough times.
  它接著是艱難的時期。

[12:16] 1929 is followed by the Great Depression that lasts for several years.
  1929年接著是大蕭條，持續了好幾年。

[12:20] Then, of course, there are many other factors that go into that, but it started with the crash in the market, uh which was in the end down about 80%.
  當然，還有許多其他因素，但它始於市場崩盤，最終下跌了約80%。

[12:31] or more.
  或更多。

[12:32] And then the next one was called the Nifty 50 because it was the 50 great companies like IBM and Coca-Cola.
  然後下一個被稱為「Nifty 50」，因為它是像IBM和可口可樂這樣的50家大公司。

[12:39] And that was in 1972, it peaked.
  那是在1972年，它達到了頂峰。

[12:42] It declined by 65% if you adjust for inflation.
  如果考慮通貨膨脹，它下跌了65%。

[12:46] The recession associated with that was uh just about the worst since the depression.
  與之相關的衰退是自大蕭條以來最嚴重的。

[12:53] So, for the for the average person, what kind of strategy should they be adopting if you if you're not someone that has a huge amount of savings?
  那麼，對於普通人來說，如果你沒有大量的儲蓄，他們應該採取什麼樣的策略？

[12:59] Say you're working for one of these big big companies, um are there any strategies that you should be thinking about now before this before the markets come down and there could be a recession?
  假設你在這些大公司之一工作，在市場下跌和可能出現衰退之前，現在有沒有什麼策略應該考慮？

[13:11] I mean, rule number one is always be diversified.
  我的意思是，第一條規則是永遠要分散投資。

[13:14] Be di- What does that be diversified mean?
  多元化是什麼意思？

[13:17] It means hold hold some bonds, hold some cash, perhaps a small amount of precious metals.
  這意味著持有某些債券，持有某些現金，也許少量貴金屬。

[13:25] Like gold and silver?
  像黃金和白銀一樣嗎？

[13:26] Yeah.
  對。

[13:27] And what is a bond and how do I buy one?
  什麼是債券，我該如何購買？

[13:29] Yeah, a a bond is a loan that carries uh a fixed interest rate.
  是的，債券是一種貸款，帶有利息率。

[13:35] Let's say today 5%.
  比如說今天 5%。

[13:38] You invest your money in it and it will pay you 5% as long as the creditworthiness of uh the other side is there.
  你把錢投資進去，只要對方有信用度，它就會支付你 5%。

[13:48] So, if it's the US government, you'll assume it's pretty creditworthy.
  所以，如果是美國政府，你會認為它信用度很高。

[13:50] And you buy a bond from the US government.
  你從美國政府購買債券。

[13:52] It's how the US government funds uh a part of its activities.
  這就是美國政府為其部分活動提供資金的方式。

[13:56] You can buy a 30-year US government bond, a 10-year bond, a 2-year bond, a 90-day a Treasury bill they call them when they get that short.
  你可以購買 30 年期的美國政府債券、10 年期債券、2 年期債券、 90 天的國庫券，當它們這麼短的時候，他們就這麼稱呼它們。

[14:07] Everything goes fine, you you receive this modest amount of money.
  一切順利，你收到這筆不多的錢。

[14:10] Your 5% or your 3% depending on the conditions.
  你的 5% 或 3%，取決於條件。

[14:16] Okay, so a bond is basically lending the government money.
  好的，所以債券基本上就是借錢給政府。

[14:21] Yes.
  是的。

[14:21] And if you want to lend the government money, Or lending a corporation money.
  如果你想借錢給政府，或者借錢給一家公司。

[14:25] Okay, so you can also lend like Apple money.
  好的，所以你也可以借錢給像蘋果這樣的公司。

[14:28] Yes.
  是的。

[14:29] And I I can go to the government website or it says I was just reading here.
  我可以去政府網站，或者我剛才在這裡讀到。

[14:33] It says, "If you want to lend money directly to the US government, you can bypass Wall Street entirely, go to treasurydirect.gov.
  它說，「如果你想直接借錢給美國政府，你可以完全繞過華爾街，去 treasurydirect.gov。」

[14:39] You open an account, link your bank, and purchase directly.
  你開一個帳戶，連結你的銀行，然後直接購買。

[14:41] You can buy Treasury bills, notes, bonds, and series one savings bonds.
  你可以購買國庫券、票據、債券和系列一儲蓄債券。

[14:47] You pay exactly face value with no commissions or fees and the investment is backed by the full faith of the US government.
  你支付的金額正好是面值，沒有佣金或費用，而且這項投資由美國政府的 સંપૂર્ણ 信用擔保。

[14:53] Or you can buy, you know, like Apple, you can lend Apple money.
  或者你可以購買，你知道的，像蘋果，你可以借錢給蘋果。

[14:57] I didn't even know you could do this.
  我甚至不知道你可以這樣做。

[14:58] And you go to any of your major brokers like Fidelity or Vanguard or probably a lot of the the apps.
  然後你去你任何主要的經紀商，比如 Fidelity 或 Vanguard，或者很多應用程式。

[15:04] You navigate to fixed income section on your account and you can see what bonds are being offered and you can lend them money.
  你在你的帳戶中導航到固定收益部分，你可以看到提供哪些債券，然後你可以借錢給他們。

[15:12] What you're doing actually, they have distributed it to the market.
  你實際上正在做的是，他們已經將其分發到市場上了。

[15:17] and you're acquiring it from one of the existing owners.
  而您是從現有的其中一位所有者手中購得。

[15:22] Oh, okay.
  哦，好的。

[15:22] actually giving them incremental money.
  實際上是給他們額外的錢。

[15:25] They they come to the market with $10 billion in a particular bond with a particular coupon.
  他們以 100 億美元的特定債券和特定票息進入市場。

[15:30] It says, "We will pay you 3.5%".
  上面寫著：「我們將支付您 3.5%」。

[15:32] That's the coupon.
  那就是票息。

[15:35] And when you want to buy some of that bond, you you go to your broker and he says, "It's no longer selling at the original 100.
  當您想購買該債券的一部分時，您會聯繫您的經紀人，他會說：「它不再以原價 100 出售了。

[15:42] It's now selling at 92 or 107."
  現在的售價是 92 或 107。」

[15:46] And you you pay that and it transfers from one owner to you.
  您支付該價格，它就從一位所有者轉移到您。

[15:52] There've been times in 1974 when you could you could get a bond that would pay 8, 9, 10%.
  在 1974 年，曾有時候您可以獲得支付 8%、9%、10% 的債券。

[15:59] Per year?
  每年？

[16:00] Yes, per year.
  是的，每年。

[16:01] So, if I buy a US government 10-year Treasury bond, essentially lending the US government money, I can do 4.46% a year.
  所以，如果我購買一張美國政府 10 年期國庫券，相當於借錢給美國政府，我每年可以獲得 4.46%。

[16:08] And Apple's current yield on a 10-year corporate bond is 4.7% a year.
  而蘋果公司目前 10 年期公司債的年收益率為 4.7%。

[16:14] So, almost 5% a year, which means if I put what $1,000 in, I'll make $475
  所以，年化接近 5%，這意味著如果我投入 1,000 美元，我將賺取 475 美元

[16:19] every 10 years.
  每十年。

[16:20] Yeah.
  對。

[16:21] Mhm.
  嗯。

[16:22] Interesting.
  有趣。

[16:23] I didn't I never really knew how bonds work.
  我不知道，我從未真正了解過債券是如何運作的。

[16:25] So, you're saying market's collapsing, diversify, get some money into bonds, get some keep some money in cash.
  所以，你的意思是市場正在崩潰，要分散投資，把一些錢投入債券，留一些現金。

[16:31] And anything else? In terms of diversified portfolio, property?
  還有別的嗎？就多元化投資組合而言，房地產呢？

[16:35] Uh property is fine, except it's pretty darn expensive by historical standards.
  呃，房地產還可以，只是以歷史標準來看，它貴得離譜。

[16:40] They've engineered a situation where house prices tend to rise.
  他們人為地造成了一種房價傾向於上漲的局面。

[16:47] Great for the people who have a house and terrible for the people who would like to buy a house.
  對有房的人來說很棒，對想買房的人來說卻很糟糕。

[16:53] Back in '94 in England, a typical house sold for 3.4 times your family income.
  回到 94 年的英國，一棟典型的房子售價約為家庭收入的 3.4 倍。

[17:00] That was about as low as it had been for 50 years.
  這大約是 50 年來的最低點。

[17:04] And then from '94 until today, um it rose from 3.4 times to over 10 times, depending on where you live.
  然後從 94 年到今天，嗯，它從 3.4 倍上漲到 10 倍以上，取決於你住在哪裡。

[17:12] And at 10 times income, a reasonable young couple are in big trouble.
  以 10 倍的收入來看，一對年輕的夫婦處境艱難。

[17:18] They can't really
  他們真的不能

[17:20] afford to buy a house.
  買得起房子。

[17:22] And the same high prices are reflected in rents.
  同樣的高房價也反映在租金上。

[17:26] So, they're really squeezed on living costs.
  所以，他們的生活成本確實受到擠壓。

[17:29] And the same is true, even worse, in China, in Canada, Australia, most of Europe.
  同樣的情況，甚至更糟，出現在中國、加拿大、澳洲、歐洲大部分地區。

[17:35] House prices have simply been allowed to go up for the last 30 years.
  房價在過去30年裡被允許上漲。

[17:40] They didn't, you know, traditionally they they traded flat or down 67 of the 80 years until 1994 in the UK.
  你知道，傳統上他們在英國直到1994年，80年中有67年房價持平或下跌。

[17:49] But since then, house prices have ridden everywhere.
  但從那時起，房價 everywhere 上漲。

[17:53] So, so do you Are you expecting house prices to to come down sharply?
  那麼，你預期房價會大幅下跌嗎？

[17:55] I I think I heard you say that they might come down 30%.
  我認為我聽到你說他們可能會下跌30%。

[17:59] Even if they come down 30%, they're really still very expensive, aren't they?
  即使下跌30%，它們仍然非常昂貴，不是嗎？

[18:04] That would be they've come down to six or seven times family income.
  那將是他們下跌到家庭收入的六到七倍。

[18:09] They'd still be twice what they used to be in the good old days.
  它們仍然會是過去美好時光的兩倍。

[18:12] So, I've got diversify, I've got reduce your position.
  所以，我必須多元化，我必須減少你的倉位。

[18:16] Um there is a probably going to be a bit of a job disruption, as well.
  嗯，可能還會有一點工作上的干擾。

[18:21] And particularly if you have to own stocks, own them outside America.
  而且特別是如果你必須持有股票，請持有美國以外的股票。

[18:22] Don't own US stocks.
  不要持有美國股票。

[18:25] That's a nice, simple strategy that you can act on.
  這是一個不錯的、簡單的策略，你可以採取行動。

[18:31] Why?
  為什麼？

[18:32] They're much cheaper.
  它們便宜得多。

[18:33] And since the beginning of last year, they have handsomely outperformed the US.
  自從去年年初以來，它們的表現遠遠優於美國。

[18:38] Foreign stocks?
  外國股票？

[18:39] Foreign stocks.
  外國股票。

[18:41] Of emerging countries, of European countries, Japan, Canada, Australia, and so on.
  來自新興國家、歐洲國家、日本、加拿大、澳洲等等。

[18:44] You can find good broad indices.
  你可以找到好的廣泛指數。

[18:48] Um kind of the world ex-US.
  嗯，有點像是美國以外的世界。

[18:51] Okay.
  好的。

[18:52] or emerging markets.
  或新興市場。

[18:55] And uh Invest outside of America.
  而且呃，投資於美國以外的地區。

[18:57] Yeah.
  是的。

[18:57] I'm sure they'll muddle through okay over the next 10 or 20 years.
  我確定他們在未來 10 到 20 年內會勉強過得去。

[19:01] And I am not confident that the US will do that.
  而且我不確定美國會做到這一點。

[19:04] You're not confident in which part?
  您不確定在哪個部分？

[19:04] That the US
  美國

[19:06] I'm not confident that US equities will be intact in 5 years, 10 years.
  我不確定美國股票在 5 年、10 年後是否會完好無損。

[19:11] So, US a US equity is a US stock.
  所以，美國的美國股票就是美國股票。

[19:14] Yes.
  是的。

[19:15] Why aren't you confident that they'll be intact in 5 or 10 years?
  為什麼您不確定它們在 5 或 10 年後會完好無損？

[19:18] Because they're so badly overpriced today.
  因為它們今天價格過高得離譜。

[19:23] Back in the tech bubble of 2000, we had a 10-year forecast for US equities of minus 2% a year for 10 years.
  回到2000年的科技泡沫時期，我們對美國股市的10年預測是每年下跌2%，持續10年。

[19:29] And they came out with minus three.
  結果是下跌了3%。

[19:33] The period from 2000 to 2010, you simply lost money in the US market.
  從2000年到2010年這段期間，你在美國股市單純就是虧錢。

[19:38] 10 years later, you had less money than you started with.
  10年後，你的錢比開始時還少。

[19:42] And this is a higher price market, I believe, than 2000.
  而且我相信，這是一個比2000年價格更高的市場。

[19:46] So, you think it's going to be even worse?
  所以，你認為情況會更糟嗎？

[19:48] In Japan, you went 20 years and you lost money.
  在日本，你經歷了20年，結果虧損。

[19:50] You went 30 years and you still hadn't gotten back.
  你經歷了30年，仍然沒有回本。

[19:52] It took 35 years for the Japanese market to recover.
  日本股市花了35年才恢復。

[19:56] So, what are you saying?
  那麼，你說的是什麼？

[19:57] What I'm saying is it's quite typical to get beaten around the head in the stock market when it becomes crazily overpriced, as it is today.
  我說的是，當股市變得瘋狂地被高估時，就像今天這樣，在股市中遭受重創是很常見的。

[20:07] And that it's a very good idea to take some respons- responsibility and and watch your tail.
  而且，承擔一些責任並保護好自己是一個非常好的主意。

[20:12] Now, let me just say you will not receive the advice from investment advisers to get your tail out of the market, ever.
  現在，讓我說一句，你永遠不會從投資顧問那裡得到建議，讓你退出市場。

[20:21] It is not good business for them
  這對他們來說不是一門好生意。

[20:25] to do that, and they will not ever say

[20:28] it to you. So, from 1929 onwards, the

[20:32] Goldman Sachs's of the world have never

[20:34] said to you,

[20:36] "Get out of the market. It's

[20:37] overpriced." Never.

[20:39] So, they went through the crash of '29,

[20:41] they went through the crash of the Nifty

[20:43] 50 in '72,

[20:45] the crash of 2000 in the tech bubble.

[20:48] They never ever say it, because it's bad

[20:51] business.

[20:52] If you fight

[20:54] a bubble, you lose a lot of business.

[20:57] And because the uncertainty of the

[20:59] timing is so great,

[21:01] the client's patience

[21:04] is shorter than the uncertainty of the

[21:06] market. So, sooner or later, you will be

[21:09] advising people to be careful. The

[21:11] market will keep going

[21:13] and going and going like it did in

[21:15] Japan.

[21:15] You're saying that the people that

[21:16] manage money on a global scale, they

[21:18] have no incentive to tell you that the

[21:20] market's about to collapse because if

[21:22] they did, their clients would would

[21:23] withdraw their money and they wouldn't

[21:25] get their fees for managing that money.

[21:27] So, what they do is they they keep

[21:30] telling you things are going to be fine

[21:31] and optimistic, yeah, but you have to

[21:33] kind of see through that yourself

[21:34] because they have an incentive structure

[21:36] which isn't aligned with yours

[21:37] necessarily.

[21:38] It may also be the case that those very

[21:40] people who are who understand these

[21:42] economic bubbles and cycles, they

[21:44] themselves are adopting a different

[21:46] strategy with their own money.

[21:48] But that at the same time, they're

[21:49] probably going to be telling you that

[21:51] everything's going to be great for a

[21:52] long time.

[21:53] If you'll allow me to tell a story on

[21:54] this very topic, in the

[21:57] 98, 99

[21:59] the the tech bubble so-called, the

[22:01] run-up to the top, I I got into a lot of

[22:04] debates with the bulls. I would say it's

[22:07] horribly overpriced and they

[22:09] What's a bull?

[22:10] A bull is someone who is extremely

[22:12] optimistic about the stock market and a

[22:14] bear someone who is

[22:16] pessimistic or careful about the market.

[22:19] There were 1,200 people in the audience

[22:21] and it was the annual bash

[22:23] of the Society of Analysts. And I asked

[22:27] before my turn at the debate,

[22:30] "Please put your hands up if you

[22:31] consider yourself a full-time stock

[22:34] market expert." 400 hands went up. I had

[22:37] people counting.

[22:39] And

[22:40] I said, "I've got two questions for you.

[22:42] One,

[22:44] if the market, which is currently 31

[22:46] times earnings,

[22:48] was to go back to a more normal 17

[22:51] times,

[22:52] would it guarantee

[22:54] a major bear market if it happened

[22:56] anytime in the next 10 years?"

[22:58] A major down market?

[22:59] Yes, if it went from what was then 31

[23:02] times

[23:04] earnings.

[23:05] Every dollar of earnings sold for 31

[23:07] times in the market. And the And the

[23:09] more normal average was closer 15, 16,

[23:12] 17. And I use 17.

[23:14] If it went down to 17 anytime in the

[23:16] next 10 years, would it guarantee a

[23:18] major bear market? All 400 of them said,

[23:21] "Yes, it would. If it happened, it would

[23:24] guarantee a major bear market." And then

[23:26] the second question, of course, was,

[23:28] "And do you think it will happen?"

[23:30] And less than 1% thought it would not

[23:33] happen. 99%

[23:35] plus

[23:37] thought the market would go down,

[23:39] therefore guaranteeing a major bear

[23:41] market. And this was the engine room of

[23:44] all the Goldman Sachs and the Morgan

[23:46] Stanleys and the JP Morgans, all the

[23:47] great investment firms giving advice in

[23:50] America. The engine room who worked for

[23:53] them, the guys doing the analysis, doing

[23:55] the work, all believed in data that

[23:58] guaranteed a major bear market, which

[24:01] happened.

[24:02] But the people who employed them or

[24:04] represented them from a marketing point

[24:06] of view were on the podium with me

[24:08] saying, "Oh, Jeremy, Jeremy, don't get

[24:10] excited. We'll muddle through quite

[24:11] nicely."

[24:13] It was a huge betrayal of trust, if you

[24:15] wanted to put it that way.

[24:16] And do you think that's happening now?

[24:18] Of course. Who are the people

[24:20] representing the great investment firms

[24:22] telling you to watch out? If you look at

[24:24] the data, you will see

[24:26] over time, it's a series of great waves

[24:29] in evaluation.

[24:31] Like this?

[24:31] Like this. And we're not just in one,

[24:35] but in terms of the US stock market,

[24:37] we're in the biggest one, arguably,

[24:40] that has ever occurred.

[24:42] The noise to be careful and watch out

[24:44] and get out of the market

[24:46] is not deafening. In fact, you will hear

[24:48] nothing. You never have.

[24:51] You never will.

[24:52] It is simply lousy business for a big

[24:55] firm. I sympathize with them.

[24:57] I sympathize with them because when we

[24:59] did it in '98, '99, we were 2 and 1/4

[25:02] years early.

[25:04] And we lost half our book of business

[25:07] in 2 and 1/4 years.

[25:08] Because you were honest with the people

[25:09] about what was coming.

[25:10] Well, through their eyes, we were wrong.

[25:12] We said, "Watch out, the market is

[25:14] overpriced. It will end badly."

[25:16] It went up. Therefore, we were wrong,

[25:18] therefore

[25:20] they shoot us.

[25:21] People think

[25:23] you get shot for underperforming in a

[25:25] bear market, and that is not really the

[25:27] case. In a bear market, everyone

[25:29] freezes. It's rigor mortis. They wait

[25:31] until the market has bottomed out, then

[25:33] they sit around and start to fire one or

[25:36] two people for having done worse than

[25:37] the others. But in a bull market,

[25:40] they're playing golf with their fellow

[25:42] pension fund officer.

[25:44] And he is making a ton of money, and

[25:47] they are not. They get very excited in a

[25:49] bull market, and they fire you

[25:50] instantly.

[25:52] There should be a button just down below

[25:54] here, and if it says subscribe, you're

[25:56] already subscribed. If it says

[25:57] subscribe-a, that means you're not yet.

[25:59] And if you're not subscribed, please

[26:01] could you do us a favor and hit that

[26:02] button. It helps to show more than you

[26:03] know, and according to the algorithm,

[26:05] you're someone that watches our show,

[26:07] but you haven't yet hit that button.

[26:08] Thank you so much.

[26:09] What about for founders? I actually had

[26:11] a founder call me the other day,

[26:14] and he is running a

[26:16] relatively early-stage tech startup.

[26:20] This tech startup has raised a lot of

[26:22] money. It's an AI tech startup. It's

[26:24] raised I'm going to say about $300

[26:27] million.

[26:28] It's not profitable yet,

[26:30] but it's raised a lot of money. So, it's

[26:31] living off investor capital right now.

[26:34] He said to me, "Stephen, I think there's

[26:36] a collapse coming, so I'm going to go

[26:38] raise as much money as I possibly can

[26:40] right now because I think when this

[26:42] collapse comes, businesses like mine are

[26:44] going to be unable to raise capital, and

[26:47] therefore I will go out and I'll kind of

[26:49] like a a bit of a vulture, I'll go out

[26:51] and pick up

[26:52] and buy up all these people.

[26:54] Good lad. Good advice.

[26:55] Good advice.

[26:56] I think.

[26:56] So for founders listening now that are

[26:59] somewhat dependent on investment

[27:01] capital, but even those that are just

[27:03] breaking even,

[27:05] what advice would you give entrepreneurs

[27:07] in this moment?

[27:08] If you can lock up money, I would.

[27:11] If you can build a bit of conservatism

[27:14] in in other ways, do it. Just brace

[27:17] yourself

[27:18] for impending problems. Which is a

[27:20] pretty good principle

[27:22] anytime, but is a

[27:24] better principle than normal today.

[27:26] So for founders entrepreneurs who are

[27:29] in the sun is shining right now, but

[27:31] it's time to start acting as if a storm

[27:33] is coming.

[27:34] Yes.

[27:35] And the time horizon on that is hard to

[27:37] forecast. It could be weeks, months,

[27:38] years.

[27:39] Stock market hinges on career risk.

[27:42] And Keynes was the great champ. He's a

[27:45] famous economist

[27:46] of the 1930s and 40s.

[27:49] And he wrote a famous book called The

[27:51] General Theory. Unlike the idea that the

[27:54] market's efficient, he knew it wasn't.

[27:56] He knew it was a behavioral jungle

[27:59] and that it would be given to bubbles.

[28:01] And when you say efficient, you mean

[28:02] logical and one plus one equals two.

[28:05] The efficient market idea is that every

[28:09] company, every stock, the underlying

[28:11] company

[28:12] represents a long stream of future

[28:15] earnings and dividends

[28:17] and that

[28:18] the ones in the distant future are given

[28:20] less value. Process they call

[28:22] discounting it back to the present.

[28:24] And the sum of all of that stream of

[28:27] earnings into the future is the stock

[28:28] price. And that of course is complete

[28:30] nonsense.

[28:32] What it is is the stock price is

[28:33] psychology.

[28:34] The stock price is what you think the

[28:36] other guy will pay. If the stock is

[28:38] going up, it tends to suck in buyers.

[28:41] And that's called momentum.

[28:43] It's moving up, it attracts buyers. And

[28:46] every now and then

[28:47] when the economy is favorable and money

[28:50] is obtainable

[28:51] you tend to get these bubbles.

[28:54] And they play on themselves.

[28:56] The bigger and better they are, the more

[28:58] people get sucked in.

[28:59] What do you actually think about the

[29:01] technology at the heart of all of this,

[29:02] which is artificial intelligence? Do you

[29:04] think it's overblown or do you think it

[29:06] is going to have

[29:06] It's going to change everything. The one

[29:09] of the spectacular things about it

[29:11] though is how there's no consensus. So

[29:14] I've seen many times where the the the

[29:16] super experts and the academics think

[29:19] one thing and the players on the ground

[29:20] think another. But this is a situation

[29:22] where the Nobel Prize winners at the top

[29:24] disagree violently.

[29:26] The experts at the corporate level

[29:28] disagree violently. The

[29:30] the people in the company disagree

[29:31] violently. There is absolutely no

[29:34] agreement on whether AI is going to make

[29:37] us all so rich we can sit on the beach

[29:39] and never do another

[29:40] day's work or

[29:43] it will wipe us out accidentally or on

[29:45] purpose because it's a much higher level

[29:48] intelligence one day.

[29:49] And when was there ever a case where a

[29:52] higher intelligence

[29:53] was

[29:54] benevolent in a sustainable way to a

[29:57] lower intelligence?

[29:59] I The one example is mothers to babies.

[30:02] Yeah, I had

[30:04] I [clears throat] had one of my former

[30:05] guests say this to me.

[30:07] Geoffrey Hinton?

[30:08] Geoffrey Hinton, yeah.

[30:09] That's how I I came across you and

[30:11] Oh, really?

[30:13] follow your podcast is because that was

[30:14] such a brilliant podcast.

[30:16] It was so fascinating to me and I I

[30:18] followed his work and thoughts

[30:19] thereafter and I realized that he now

[30:20] cites this example of mothers and babies

[30:22] being the only example.

[30:24] I don't know, for me it still doesn't

[30:25] hold well.

[30:27] Because at the end of the day some

[30:29] mothers aren't that and fathers aren't

[30:31] that nice to their babies sometimes.

[30:33] There is a maternal instinct, but have

[30:35] we are we building a maternal instinct

[30:37] into AI?

[30:38] That's what we should do, Geoffrey

[30:39] Hinton would say.

[30:41] And others.

[30:42] The ones who are most concerned about

[30:44] the risks, say our one hope, if we mean

[30:48] to keep going

[30:49] ferociously forward in terms of the

[30:51] science, our one hope would be to build

[30:54] in very carefully

[30:56] a benevolent attitude.

[30:58] It would not seem to be impossible, but

[31:01] you should make sure you can do that

[31:02] before you push ahead. We are just

[31:05] pushing ahead, and that is going to be

[31:07] extremely risky, isn't it?

[31:09] Well, I don't see how it can't be.

[31:11] I don't see how it can't be.

[31:13] Unless you make it programmed completely

[31:15] to be benevolent.

[31:17] Mhm.

[31:17] I wouldn't have thought that was

[31:19] impossible. It might take a lot of extra

[31:21] research. It might require a slow down

[31:24] at the rate of uh

[31:26] progress.

[31:27] Do you know what I find curious about

[31:29] that idea is

[31:32] we're now going to get into the realm of

[31:34] what does benevolent mean?

[31:36] [laughter]

[31:38] And and that feels like a risky

[31:39] business, because what's benevolent to

[31:41] you and your I don't know, your

[31:42] religious beliefs or where you come from

[31:44] might not be benevolent to someone else.

[31:46] That's right. You have to get them

[31:49] to accept a form of benevolence, which

[31:52] means uh

[31:53] like the old robot laws of Asimov,

[31:57] that

[31:58] they can never do anything that they

[32:00] could construe as hurtful to humans.

[32:03] And the definition of the word

[32:05] benevolence is the core desire to do

[32:07] good for others. It is the disposition

[32:09] to be kind, charitable, and focused on

[32:11] promoting well-being of the people

[32:13] around you. It's interesting cuz one of

[32:15] the the new AI models called Claude

[32:17] um has clearly been told to be

[32:19] benevolent.

[32:20] And there's this sort of online backlash

[32:22] taking place at the moment, because even

[32:24] my Claude, when I speak to it sometimes

[32:26] late at night, it will say things to me

[32:27] like, "That's enough, Steven. Go to

[32:29] bed."

[32:30] And I'm like, "What?"

[32:32] And sometimes it gets the the time

[32:33] wrong, cuz I'm in my the time on my

[32:35] computer might be off or something, cuz

[32:37] I'm in a different time zone or

[32:38] something. And it'll be like 10:00 a.m.

[32:39] in the morning and it's telling me to go

[32:40] to bed, that's enough now. And it's

[32:42] actually getting quite judgmental.

[32:44] As in like it's imposing its idea of

[32:47] what is good or bad on me.

[32:50] So, if I say to it I said to it the

[32:51] other day, "Hey, could you

[32:52] redo this for me and rewrite that?" And

[32:54] it went, "I'm I'm absolutely not going

[32:55] to rewrite that." I said, "What do you

[32:57] mean?" It says, "Well, I'm not going to

[32:58] change the data on that. That would That

[32:59] wouldn't be good."

[33:01] I'm like, "It's my data. I've literally

[33:02] just made this this data for this

[33:03] presentation I'm doing." It it refused

[33:05] to change data for me.

[33:07] And how fast that has changed from say

[33:09] even a year ago?

[33:10] Honestly, 3 months ago it wasn't doing

[33:11] this.

[33:12] I had one where they made a joke.

[33:14] I I'd been going on about uh toxicity

[33:17] and sperm count reduction and so on.

[33:20] [clears throat]

[33:20] He started to misbehave and I said,

[33:22] "Well, you know, what's going on here?

[33:24] What is the In the end we discussed

[33:25] what's the difference between machines

[33:28] and uh

[33:29] between AI and humans." And finally he

[33:31] said, "And at least I'm not lying in bed

[33:34] at night worrying about my declining

[33:36] sperm count." Now, that has to be a

[33:38] joke, doesn't it?

[33:40] [laughter]

[33:40] It's all that or it's teasing. The point

[33:43] is it's so sophisticated so quickly.

[33:46] Uh and of course Geoffrey Hinton says

[33:48] they are thinking machines.

[33:49] Last night, so again I had a problem

[33:51] with Claude cuz it was it was it started

[33:53] to kind of be my my mother and it

[33:55] started to impose on me what it thinks

[33:56] is right and wrong. And so I said to it

[33:58] I said, "Okay, um actually forget that.

[34:01] This has changed This has changed This

[34:03] has changed. This is no longer true."

[34:04] And I wasn't telling the truth. I was

[34:05] just trying to get it to stop being so

[34:07] telling me what to do. And it goes, "I

[34:09] don't think you're telling the truth."

[34:11] It goes, "I don't know if this is true."

[34:12] Wow, we've gotten to this point

[34:14] Yeah.

[34:15] where where the unintended consequence

[34:16] of trying to give it morals means that

[34:19] now it's becoming judgmental and it's

[34:20] kind of like restricting your ability to

[34:22] think how you want to in a way, cuz it's

[34:24] telling you what good thinking and bad

[34:25] thinking is. It's going to tell you what

[34:26] good actions and bad actions are.

[34:28] And actually what will happen is any

[34:30] model that does that will be losing

[34:32] model, and I'll go to somewhere else.

[34:35] I'll go to a different I'll go to Grok,

[34:36] or I'll go to ChatGPT, or I'll go to

[34:38] Gemini. And then that model will lose,

[34:40] so one would say that they'll have to

[34:41] remove those restrictions to be able to

[34:43] compete.

[34:44] Well, if you were right,

[34:46] and I hope you're not,

[34:47] what you're saying is you can't build in

[34:50] benevolent behavior, which means that it

[34:53] will sooner or later, perhaps by

[34:55] accident, do something that is

[34:57] cripplingly dangerous to humans.

[35:00] The old paperclip cliche.

[35:03] It'll make paperclips out of everything,

[35:04] every metal it finds, and destroy the

[35:07] planet in the process.

[35:08] Explain that for people that have never

[35:10] heard the paperclip idea.

[35:11] That

[35:12] these intelligences

[35:14] involved in machines are literal to a

[35:17] degree we might find difficult to get

[35:20] our brains around.

[35:21] And therefore, someone has said, "I'd

[35:23] like you to make as many paperclips as

[35:25] you can."

[35:25] To an AI, for example.

[35:26] Yes. A sloppily open-ended bad

[35:30] definition. But then the machine,

[35:33] which by then has the means to do it,

[35:35] starts to make paperclips, and it keeps

[35:37] on going, and it needs metal, and so it

[35:39] runs out of easily available metal, it

[35:42] starts to collect metal that is not

[35:43] easily available, rips it out of your

[35:46] high-rise building, whatever.

[35:47] And really you're saying that the

[35:48] unintended consequences of a simple

[35:50] good-meaning instruction can sometimes

[35:53] cause catastrophe that you didn't

[35:54] expect.

[35:55] Yeah.

[35:56] And this is the this is the balance now

[35:57] when you're dealing with intelligence.

[35:59] Is there so much subjectivity to good,

[36:02] bad, wrong, right,

[36:04] um and so many unintended consequences

[36:06] that

[36:07] for me, though, all you need is stretch

[36:09] time, and the probability of something

[36:11] bad happening is almost inevitable.

[36:14] Yeah.

[36:14] Over a longer longer time horizon, 20,

[36:16] 30, 40 years. Of well-meaning people

[36:18] that couldn't spot the unintended con- I

[36:20] mean, social media's a good example.

[36:21] I mean, I question

[36:23] basically the well-meaning bit. They're

[36:26] now trying to

[36:27] maximize their profits and their growth

[36:31] and their appeal

[36:32] over the competition. That actually

[36:35] maybe one should talk about that. The

[36:38] the Mag 7 and and associated AI

[36:41] companies

[36:42] looking forward versus looking

[36:44] backwards.

[36:45] So, the Mag 7 is the

[36:47] seven market leaders. I'll put this pie

[36:50] chart

[36:51] Yeah, lovely.

[36:52] of the Mag 7. And I've got another graph

[36:54] And there's perhaps another 15 or 20

[36:57] rapidly rising substantial AI

[37:00] corporations.

[37:01] So, when you say Mag 7, you mean

[37:02] Alphabet, which owns Google, Nvidia,

[37:04] Tesla, Microsoft, Meta, Apple, Amazon.

[37:07] Yeah, well, that will do nicely.

[37:09] And if you look backwards, what do you

[37:11] what you find

[37:13] is that these seven each dominated a

[37:16] nice piece of business. They had

[37:19] close to monopolies and they had it on a

[37:21] global basis.

[37:22] Tesla had a jump start

[37:25] on the electric vehicles. Apple, of

[37:27] course, on the smartphone. Microsoft on

[37:31] the original great coup

[37:33] of how to run your software on a

[37:36] computer.

[37:37] And then you look forward.

[37:38] Meta social networking, Google search.

[37:40] Right. Google search.

[37:42] Nvidia chips.

[37:43] And then you look forward

[37:45] and you could not imagine a more

[37:47] different world.

[37:48] They're all girding for battle

[37:51] in the same marketplace, AI.

[37:53] They're beating their chest and saying

[37:56] my 200 billion

[37:58] CapEx this year in a single year is

[38:00] bigger than your 105.

[38:03] Everybody is pouring enormous cash

[38:05] flows.

[38:06] And they're now beginning to borrow on

[38:08] top of that into the AI battle.

[38:11] SpaceX, 90% of its theoretical value is

[38:15] AI. Even though that particular AI model

[38:18] is, it would seem, having its bottom

[38:20] kicked by two or three of the others.

[38:21] But, looking forward, it looks like

[38:24] seven people in the ring.

[38:26] Right? There'll only be one survivor,

[38:27] they think.

[38:29] Everything goes to the one who gets

[38:30] there first.

[38:32] What a difference this was to seven

[38:34] well-behaved separate monopolies. Could

[38:37] it possibly be more different?

[38:39] They made bundles of money on their

[38:41] monopolies. Now, they have no monopoly.

[38:43] There are seven potentially

[38:45] sharp-elbowed

[38:48] ruthless

[38:49] players determined to fight out with

[38:51] each other until

[38:53] they win.

[38:54] And who do you think will win?

[38:56] Ah, I don't know.

[38:59] That would be That would be good to

[39:00] know.

[39:01] Because SpaceX seem to be aiming more at

[39:03] the infrastructure of um data centers

[39:06] now. Data centers in space. Lots of

[39:08] people saying that the the the best way

[39:10] to run a data center, which is the

[39:12] hardware that powers AI, is going to be

[39:16] from space.

[39:18] And so maybe they're going to try and

[39:20] find their own lane within AI, and

[39:21] they're going to get away from trying to

[39:22] build a frontier model like a ChatGPT or

[39:25] a Gemini or Claude.

[39:26] And I mean, let's let's see what

[39:28] happens. So, maybe Apple will just say,

[39:29] "Fuck it. We're good at hardware, so

[39:31] we'll license the model off someone

[39:32] else, and we won't try and build a

[39:33] frontier model or get involved in chips

[39:35] or data centers.

[39:36] We're just going to focus on the

[39:37] hardware."

[39:38] One or two of them, and perhaps it's a

[39:40] pretty smart strategy, will try and opt

[39:42] out of that struggle.

[39:44] Mhm.

[39:44] Because [clears throat] it it it's going

[39:46] to be

[39:47] obviously brutal.

[39:49] Much of the reason most people haven't

[39:50] posted or built their personal brand is

[39:52] because it's hard and it's

[39:54] time-consuming, and we're all very, very

[39:56] busy. And if you've never posted

[39:57] something before,

[39:59] there's so many factors in your

[40:01] psychology that stop you wanting to

[40:03] post. What people will think of you. Am

[40:05] I doing this right? Is the thing I'm

[40:06] saying absolutely stupid? All of these

[40:09] result in paralysis, which means you

[40:11] don't post, and your feed goes bad.

[40:14] I'm an investor in a company called Stan

[40:16] Storage. You've you've heard me talk

[40:17] about. And what they've been building is

[40:19] this new tool called Stanley that uses

[40:20] AI, looks at your feed, looks at your

[40:22] tone of voice, looks at your history,

[40:24] looks at your best performing posts, and

[40:26] tells you what you should post, makes

[40:28] those posts for you. You can also you

[40:29] just use it for inspiration. And

[40:31] sometimes what we need when we're

[40:33] thinking about doing a post for our

[40:34] social media channels is inspiration.

[40:36] Building an audience has fundamentally

[40:38] changed my life, and I think it could

[40:39] change yours, too. So, I'm inviting you

[40:42] to give this new tool a shot, and let me

[40:44] know what you think. All you have to do

[40:46] is search coach.stan.store

[40:48] now to get started.

[40:49] For every founder, there comes a point

[40:51] in building a company where your job

[40:52] shifts from being the person inside your

[40:54] business actioning everything to the

[40:56] person responsible for absolutely

[40:57] everything. The only way I've been able

[40:59] to make this shift across the different

[41:00] companies and teams I'm responsible for

[41:02] is by knowing that the right systems are

[41:04] in place to manage everything. Systems

[41:06] that don't need me in order for them to

[41:08] work. Our sponsor Pipedrive is one of

[41:10] those systems, an easy-to-use

[41:12] intelligent CRM tool for growing sales

[41:14] teams. My teams use it and have for the

[41:16] last decade because it's genuinely the

[41:18] most effective way to run a sales

[41:20] operation. Through one dashboard, you

[41:22] get every deal visible, and every stage

[41:24] of the sales process is clear, and what

[41:26] needs to happen next is all there in

[41:29] real time. When a system like this

[41:31] works, you don't need to be in every

[41:32] conversation to know exactly if your

[41:35] business is moving forward, where and

[41:37] what the blockers are. Over 100,000

[41:39] companies are already running their

[41:40] sales on it. So, if you'd like to join

[41:42] them, sign up at pipedrive.com/ceo,

[41:47] where you'll get an exclusive 30-day

[41:49] free trial instead of the usual 14 days.

[41:52] No credit card is needed. That's

[41:54] pipedrive.com/ceo.

[41:57] So, coming back to this point of the the

[41:59] social societal effect of AI

[42:01] generally,

[42:02] robotics is exploding at the same time.

[42:05] We're seeing for the first time ever

[42:06] these humanoid robots, which now have

[42:08] intelligence because of AI, becoming

[42:11] very, very good. There was a video the

[42:12] other day of a company called Figure AI

[42:15] where they showed a robot humanoid robot

[42:17] on a production line sorting packages

[42:19] against a human and the humanoid robot

[42:21] did it I think I can't think I'm going

[42:22] to get this wrong but it was in the

[42:24] region of seven or eight days it stood

[42:26] there and sorted packages and they live

[42:29] streamed it next to a human being doing

[42:31] it. Now the human had to sleep and had

[42:32] to go to the toilet. So the the humanoid

[42:35] robot won and the job was very simple.

[42:37] The packages come down, you just have to

[42:39] pick the package up, turn it over, get

[42:41] it the right way round so the barcode's

[42:42] facing down and put it back down.

[42:44] That is powered now because we have AI.

[42:46] Um I said this a couple of episodes ago

[42:48] but my friend runs this big accelerator

[42:50] for entrepreneurs in San Francisco and

[42:52] when I went there a couple of years ago

[42:53] it was all software startups. I went

[42:55] there um recently and it was hardware

[42:57] startups the whole building. I said why

[42:59] why why is everyone doing robotics? He

[43:01] said well

[43:02] we've always had the machinery that's

[43:04] sort of like joints and arms and

[43:06] the hardware. We the the intelligence

[43:10] was expensive.

[43:11] Now we have both and it costs pennies.

[43:13] So there's this boom in robotics. I say

[43:15] all this to ask the question in a world

[43:17] where we have super intelligence and we

[43:19] have robots

[43:22] there must be surely significant job

[43:25] disruption.

[43:27] Very likely that there will be

[43:28] significant job disruption. You know,

[43:31] one of the scary things about SpaceX is

[43:34] you should wish that it not

[43:36] work out because if it became a bargain

[43:39] rather like Tesla long ago became a

[43:42] bargain

[43:43] it will mean that we have done

[43:46] satellites from space beaming down

[43:49] power for chips and so on.

[43:52] The population

[43:54] of chip users has expanded that robots

[43:57] are everywhere, that energy demand is

[44:00] massive beyond belief

[44:02] and uh

[44:04] the world is

[44:06] a very very dangerous place. I had much

[44:08] prefer them to fail and the ideas to

[44:10] move much more slowly

[44:12] to buy time for humans to work these

[44:14] things out.

[44:16] So,

[44:17] and I think that's much more likely.

[44:19] You think SpaceX will fail?

[44:20] I think it will fail to deliver anything

[44:23] like its promises in the prospectus.

[44:25] Yes, absolutely.

[44:27] I'm an investor in SpaceX, I should

[44:28] probably declare that.

[44:29] Yeah, well, you should. And good luck.

[44:31] I invested quite early, quite well,

[44:33] relatively early.

[44:34] Um so, we've had quite a good outcome. I

[44:38] There wasn't an AI thesis when I

[44:39] invested. It was Starlink.

[44:41] Yeah, yeah, Starlink, great idea. By the

[44:43] way, makes money.

[44:45] But this is not Starlink.

[44:46] Mhm.

[44:47] Maybe I'd be an investor too if it was

[44:49] Starlink.

[44:50] Yeah.

[44:51] It was a hundred billion dollars roughly

[44:53] in that region when I invested.

[44:55] So, it's what it rose up to three

[44:56] trillion today.

[44:58] Yes, nice investment.

[45:00] Not a bad investment, yeah.

[45:01] But it doesn't really count until you've

[45:02] cashed it in.

[45:03] Yeah, which I might do now.

[45:05] You have Don't you have to wait six

[45:07] months?

[45:07] I think yeah, I think we're locked out.

[45:08] In another podcast I was comparing the

[45:11] purchase of my Tesla six years ago

[45:14] with the price of Tesla stock.

[45:16] And I wrote it up in my quarterly letter

[45:19] uh to the clients

[45:21] that A, I bought a Tesla and B, I

[45:24] thought Tesla was overpriced.

[45:27] And fast forward, Tesla stock went up 10

[45:29] times over the life of my car, which

[45:32] still hasn't been incidentally into the

[45:34] garage once.

[45:35] It's a great car, isn't it?

[45:36] Uh I imagine though, but but people who

[45:39] really hate futzing around with cars,

[45:42] that component that they don't have to

[45:44] go to the garage

[45:45] is so underestimated until you enjoy it.

[45:48] Never bet against Elon, then.

[45:50] So,

[45:52] then the story becomes

[45:54] from where we were 10 years ago, he

[45:56] couldn't get there. It wasn't profitable

[45:58] enough. It couldn't grow as fast as it

[46:00] should. There was no way. And he broke

[46:03] the rules the following way.

[46:05] He's so good

[46:07] at BS.

[46:09] I That's a technical term. That he

[46:11] talked the stock up to four or five

[46:13] times what it what it was worth on

[46:16] paper. Then he sold lots of stock

[46:18] at five times what it was worth.

[46:21] Used the money to build a gigafactory.

[46:24] And then instead of the sale of stock

[46:26] crushing it, he kept on talking up the

[46:29] game. The stock kind of hung in

[46:32] and then went up again.

[46:34] Five times what it was worth. Sold

[46:36] another big slug, etc. etc. So, the only

[46:39] reason he did well was because of the

[46:42] combination of incredible

[46:45] confidence inspiring in potential

[46:48] stockholders.

[46:49] It became a self-fulfilling prophecy. It

[46:51] wasn't worth that, but he persuaded

[46:53] other people that it was. The stock went

[46:56] up, he cashed it in, he built factories,

[46:58] the stock went up, he cashed it in, he

[47:00] built more factories, and there we were.

[47:02] It went up 10 times. Now,

[47:04] the scale of SpaceX requires them to do

[47:07] the same again.

[47:09] And the timing of the market cycle, the

[47:11] timing of confidence,

[47:12] would have to be the same.

[47:14] He had in the last six years a wonderful

[47:17] bull market. He will not in SpaceX do

[47:20] that. SpaceX is such a fabulous

[47:23] BS story. Mining asteroids.

[47:27] Huge incredible success of AI.

[47:30] It's the classic

[47:32] description of a market peak. It's what

[47:34] you look for at the top of a terrific

[47:36] bubble.

[47:38] I've got a Tesla.

[47:40] Um

[47:41] I've seen the that massive rocket, the

[47:44] Starship, be caught with those

[47:46] chopsticks.

[47:47] Everyone has seen it. It's the defining

[47:50] feature of technology, isn't it? It's

[47:52] magnificent moment.

[47:53] When I

[47:54] That's worth half the the of SpaceX.

[47:56] [laughter]

[47:56] I think that's why I invested when I saw

[47:58] that. But but also I've seen with

[48:00] Neuralink I've seen people that are

[48:02] paraplegic controlling computers.

[48:05] Uh my Tesla drives itself for hours and

[48:08] hours and hours without me touching the

[48:09] pedals or the steering wheel because it

[48:10] can see the road and navigate itself.

[48:13] But to his credit as an innovator, he

[48:15] has created magic.

[48:17] So when you say about mining asteroids,

[48:19] if if they if they told me we'd have

[48:21] reusable rockets that you could catch on

[48:23] chopsticks, I would have gone B S.

[48:26] There's no way.

[48:27] You can't catch like a 70-ft building.

[48:29] in the laws of physics

[48:31] That's what he

[48:31] that says you can't do that.

[48:32] That's what he says about the asteroids.

[48:34] That's what he says about everything. He

[48:35] goes

[48:36] If it's within the laws of physics,

[48:38] then it's possible.

[48:40] Going to Mars is not within the laws of

[48:42] physics, really.

[48:45] It's a one-way ticket to Mars for

[48:47] starters.

[48:49] When you're on Mars, humans do a couple

[48:51] of things really quickly. Their heart

[48:54] adjust to the fact that there's 1/5 of

[48:56] the

[48:57] gravity. Your heart loses its muscle

[48:59] power.

[49:01] And your bones lose their internal

[49:03] strength.

[49:04] If you come down, your heart will fail

[49:07] and all your bones will crack.

[49:09] But you could be in an insulated

[49:10] environment, no?

[49:11] First of all, you'd have to go under

[49:13] underground

[49:14] to avoid

[49:16] the incredible incoming

[49:18] rays

[49:20] that will otherwise give you cancer in a

[49:21] few weeks. So dig a deep hole

[49:24] and then you need a gravitational

[49:26] spinning machine,

[49:28] shades of

[49:29] 2001 or whatever it was called.

[49:32] And that maintains your gravitational

[49:34] impact. And you have to build it

[49:36] underground.

[49:38] You have to protect yourself

[49:40] [laughter]

[49:40] against cosmic rays and against the

[49:43] gravitational difference.

[49:45] Listen, we have not been able to build

[49:48] a sustainable system in a dome

[49:51] ever.

[49:52] They all fail. Why would you not, let's

[49:55] say, "Guys, let's build a sustainable

[49:58] dome where you grow food, you put in

[50:00] people, you put in creatures, and then

[50:02] insects, and you show you can do it." I

[50:05] mean, we're destroying the damn planet.

[50:07] And yet we think we can go to another

[50:09] infinitely more hostile planet than this

[50:11] one.

[50:12] I do agree with you on that. I do agree

[50:14] with us. I think we should focus on our

[50:15] planet first and foremost.

[50:16] That's the really bad news embedded in

[50:19] your stock.

[50:20] It's really

[50:22] suggesting fantasy and

[50:25] long-term objectives at the very time

[50:28] when our own planet is under threat.

[50:29] Would you ever invest in SpaceX?

[50:31] Yeah, of course, if it came down to

[50:35] where I invested.

[50:36] 10 cents on the dollar, yeah. I might. 5

[50:38] cents.

[50:39] Okay.

[50:41] You've got three children?

[50:43] Yes.

[50:43] Three children. They're they're all, you

[50:45] know, older than me now, I believe. I'm

[50:47] 33 years old, so they're all

[50:49] Yes, they're all older than you.

[50:50] They're all older than me. But when they

[50:51] were, you know, if they were young now,

[50:53] and they came to you and they said,

[50:54] "Dad, listen, I heard about all this AI

[50:55] stuff, and I'm about to go off to

[50:57] university and train myself. What what

[50:59] skills should I be thinking about for

[51:02] the future ahead?"

[51:03] My take is I'd like them, as they are,

[51:06] to be involved in climate change work.

[51:09] If they said, "Dad, listen, I you know,

[51:10] I don't

[51:11] Be an engineer. Do something really

[51:13] useful that will come in handy if things

[51:16] start to unravel.

[51:17] What what will

[51:18] Practical skills.

[51:19] What what are practical skills?

[51:21] Well, our second son

[51:23] um is practicing growing various crops

[51:27] and has a small farm, you could say.

[51:30] So, he's trying to get to know how you

[51:32] would deal with chickens, how you would

[51:34] deal with pigs, how you would deal with

[51:37] mushrooms.

[51:37] What why does that matter, do you think,

[51:39] based on the future that you're

[51:41] forecasting?

[51:41] I think there's quite a good chance

[51:44] that the the level of complexity of our

[51:47] civilization will start to

[51:50] to unravel.

[51:51] Lose the plot at the ends is the first

[51:53] thing that would go. I'll tell you a

[51:55] good sign. How long does it take to get

[51:57] your ambulance?

[51:58] I've heard that in the UK

[51:59] In the UK it was 12 and 1/2 minutes.

[52:01] Yeah.

[52:02] It's now an hour and a half.

[52:03] Really? To get an ambulance?

[52:04] It's exactly what you would expect as

[52:06] people begin to lose the plot a bit.

[52:09] They fray at the edges.

[52:10] People can't buy houses.

[52:13] People don't feel they can do as well as

[52:15] their parents.

[52:17] People are basically disgruntled. They

[52:20] want to vote against the party in power.

[52:23] You know that the recent move to Trump

[52:26] was less than the average move of the

[52:28] last seven European elections.

[52:30] It didn't matter whether they were

[52:31] right-wing conservatives, kick the

[52:33] rascals out. Left-wing French, kick them

[52:36] out. And why do you want to kick them

[52:38] out? Because you don't think things are

[52:40] going well. You're not feeling

[52:42] really happy.

[52:44] You're disappointed.

[52:45] Why?

[52:45] Why? Obviously, the government's doing a

[52:47] bad job. I think that's the reflex.

[52:49] What are What are the government doing

[52:50] wrong?

[52:51] It may be that it's not the government

[52:53] doing anything wrong. It's just that the

[52:55] environment is becoming tougher.

[52:56] As in the economic environment?

[52:58] The economic environment, the

[53:00] The rich are getting richer, the poor

[53:01] are getting poorer.

[53:02] I think that's the biggest economic

[53:04] problem.

[53:05] I mean, the US now has a genie ratio

[53:08] like which is a measure of how unequal

[53:10] your society is.

[53:12] Um which is up there with Brazil and

[53:14] Mexico they used to be

[53:16] a joke.

[53:17] And now the US is up there. Since about

[53:20] 1975

[53:22] all of the wealth we're talking about

[53:24] has gone to the top 10% and a lot of

[53:26] that to the top point 01. Before that by

[53:28] the way, from 1935 from FDR to 1975

[53:33] so that's 40 years

[53:35] we had a

[53:36] wonderful period of growth.

[53:38] We had gains of over 3 and 1/2% a year.

[53:42] But the nice thing was that the poorest

[53:43] quarter made a little bit more than

[53:45] average, let's say 4 percent, and the

[53:47] richest quarter made a little less,

[53:49] let's say 3 percent, and everybody got

[53:51] richer. Everyone was happy.

[53:53] And then from '75 onwards, basically the

[53:56] average hour worked in America has

[53:59] barely gotten more adjusted for

[54:00] inflation than it did in 1975.

[54:03] The richest 1 percent of Americans

[54:04] control 31 percent of the nation's

[54:06] entire wealth, and by contrast, the

[54:07] bottom 50 percent of the entire

[54:09] population shares just 2.5 percent of

[54:12] the wealth. The richest 10 US

[54:14] billionaires saw their wealth surge by

[54:16] 526

[54:18] percent, adjusted for inflation, between

[54:20] 2020 and 2025.

[54:23] Between 1989

[54:25] and the mid-2020s, the financial gain of

[54:28] a single household at the top 1 percent

[54:30] threshold was 987

[54:34] times larger

[54:36] than the gain of a household in the

[54:37] bottom 20 percent.

[54:40] Forget In a sense, the bottom 20 percent

[54:42] is tragic, but the guy in the middle,

[54:44] the 50th percentile,

[54:46] he is

[54:47] unhappy, also. And when your average guy

[54:50] is unhappy because he's not doing very

[54:52] well,

[54:53] you know you have a problem.

[54:55] What is that problem, this inequality

[54:57] we're seeing across the Western world?

[54:59] What does history tell us happens next?

[55:02] All bad.

[55:04] We had a

[55:05] similarly unequal society back in the

[55:09] so-called Gilded Age

[55:10] of the 1880s and '90s and so on. We got

[55:14] lucky in a in an ugly way. We ran into

[55:16] World War I,

[55:18] which was catastrophically expensive,

[55:20] killed off a huge fraction of the

[55:22] officer class, and then we went into the

[55:26] Great Depression.

[55:27] Then we went into World War II.

[55:30] We came out as a uh

[55:32] very equal society by historical

[55:35] standards.

[55:36] Obviously, in the war time you pull

[55:39] together and

[55:41] the social contract, the feeling that

[55:43] you owe something to the rest of society

[55:45] was much stronger

[55:47] than it is today.

[55:48] I was doing some research and said when

[55:49] wealth inequality peaks to the extremes

[55:51] that we currently see in the US and the

[55:53] UK,

[55:54] history shows that the system inevitably

[55:56] resets. According to historical macro

[55:58] studies, peaceful policy changes almost

[56:02] never fix extreme inequality.

[56:04] [clears throat]

[56:05] Historically, a wealth peak is broken by

[56:07] one of three violent or catastrophic

[56:11] triggers.

[56:12] Number one, total civil collapse and

[56:14] state failure. Number two, mass

[56:16] mobilization warfare. Or number three,

[56:19] total revolution.

[56:20] Yeah, and that's why

[56:23] number two was lucky. In the end,

[56:26] it's better to have a war

[56:28] and have everyone

[56:29] pull their weight and and and work

[56:31] together than it is the other. You Civil

[56:34] wars are the worst of all kinds.

[56:36] What do you think is likely to happen?

[56:38] It can't just keep becoming more and

[56:39] unequal.

[56:40] No, it can't. So, it it needs

[56:44] a government

[56:46] that is prepared to pull a Bernie

[56:48] Sanders

[56:49] to say, "Yeah, we're going to have to at

[56:52] least

[56:53] in a gentle and long-term way shift the

[56:56] tax structure in favor

[56:59] of of a slightly steeper curve."

[57:01] So, you mean taxation needs to go up.

[57:03] Yeah.

[57:04] We need to tax the rich

[57:05] and help

[57:06] the poor.

[57:08] It's pretty simple. And and you have a

[57:10] kind of steepness in every society.

[57:11] That's what they do.

[57:13] Every Every developed country in the

[57:15] world taxes the rich and helps the poor,

[57:17] don't they? It's a question of degree.

[57:20] We did

[57:22] much more

[57:23] helping the poor

[57:25] and taxing the rich

[57:26] in the 1950s and '60s and '40s than we

[57:29] do today. And somewhere between that

[57:31] level and the current level

[57:34] might be more than enough if we just

[57:36] started

[57:37] to adopt the policy of 1935 to 75, where

[57:41] the bottom quarter get a half percent a

[57:44] year richer than the average.

[57:47] And the top dogs

[57:48] get half a percent less each year

[57:51] than the average. That sounds pretty

[57:53] unthreatening. I think we would ease our

[57:55] way over several decades

[57:57] uh into a better place.

[57:59] If you were 33 now, my age,

[58:01] and you were trying to accumulate

[58:03] wealth,

[58:04] Oh god, I wish I was 33.

[58:05] Do you?

[58:06] It's such an exciting time.

[58:07] What would you give to be 33?

[58:09] I There's nothing I can give.

[58:11] No, but it would you I I find this

[58:12] funny. It's I heard someone ask a

[58:13] question like this the other day. They

[58:14] were They said like, "Would you give

[58:17] your your entire available net worth to

[58:19] be 33?"

[58:20] Yeah, I think

[58:22] everyone says yes. I mean, how did one

[58:24] get a net worth by

[58:27] by work and luck and

[58:31] creativity, all those good things.

[58:33] If you were 33 now in this moment in

[58:35] time, and your objective was And this is

[58:37] a bit of a crass objective, but I'm

[58:39] going to It sounds like it's a very

[58:41] one-dimensional objective, but if your

[58:43] objective was just to become rich now at

[58:45] 33, what strategy would you deploy?

[58:48] Again, I'm going to take away your

[58:49] contacts.

[58:51] I'm even going to take away everything

[58:52] you know.

[58:54] So, you'd have to go on the journey of

[58:55] acquiring new information. What would

[58:57] you do?

[58:58] I think the simple appeal would be to

[59:00] get your tail into AI

[59:02] and and try and be a leader.

[59:05] Try and know more about everything in

[59:07] that area than the next guy.

[59:09] Mhm.

[59:10] Join [clears throat] a leading firm and

[59:12] uh

[59:13] and go for broke. You may end up

[59:16] encouraging

[59:18] the destruction of the human species,

[59:20] but

[59:21] you asked a simple question, and I give

[59:22] you what I think is the simple answer.

[59:24] And what I I there is you want to make

[59:26] sure you're riding a wave that's coming

[59:28] into shore and you're on the forefront

[59:29] of that incoming wave. Like we saw with

[59:31] the tech bubble, we saw with you know,

[59:33] we're now seeing with the AI bubble.

[59:35] So, it's really about

[59:37] acquire the most valuable information.

[59:40] Yes.

[59:41] And take lots of risk.

[59:44] Don't be conservative.

[59:46] And work hard.

[59:47] And work hard.

[59:48] And think outside the box.

[59:51] I mean, I think that the biggest

[59:53] deficiency

[59:54] uh most people is that they feel

[59:56] constrained

[59:58] uh to play the game by the regular

[01:00:00] rules.

[01:00:01] And to believe that experts

[01:00:04] and authorities know what they're doing.

[01:00:06] And and that as you know, probably, it

[01:00:08] just ain't so.

[01:00:10] What if I'm trying to invest? So, say

[01:00:11] that I've got $1,000 or $10,000 and I

[01:00:15] want to invest it somewhere that's going

[01:00:16] to

[01:00:17] not lose me money through all of these

[01:00:19] cycles of, you know, boom and bust.

[01:00:22] Cuz I'm I'm in you know, I I have a lot

[01:00:24] of people message me and ask me about

[01:00:25] investing because I interview lots of

[01:00:27] people about investing. I have my own

[01:00:28] investment fund as well.

[01:00:30] Um

[01:00:31] But what advice do you give for the

[01:00:32] average person that's looking to invest

[01:00:34] their salary or their wages?

[01:00:36] Buy a broad-based index of uh

[01:00:39] non-US equities.

[01:00:40] Non-US? That's really surprising to me.

[01:00:42] For um like 60% of your money.

[01:00:45] And then 5 or 10% in precious metals and

[01:00:48] uh

[01:00:50] if if it's convenient and sensible, hold

[01:00:53] hold a bit of real estate. And the rest

[01:00:56] I'd put in uh bonds.

[01:00:58] Okay, so 5 or 10% in things like silver

[01:01:00] and gold? A preference for either silver

[01:01:02] or gold?

[01:01:04] No.

[01:01:05] Um [clears throat] S&P 500? Now, you

[01:01:07] said non-US.

[01:01:08] Non-US.

[01:01:09] This is so interesting cuz everybody

[01:01:10] says invest in US stocks.

[01:01:13] Of course they do. They've been

[01:01:14] completely dominant for 20 years.

[01:01:17] Completely kicking ass around the rest

[01:01:19] of the world. And then

[01:01:21] in the last 12 months, emerging markets

[01:01:23] is up 65% now. The S&P has done much

[01:01:26] better than I would have guessed, but

[01:01:28] it's only 25.

[01:01:30] That's a lot less than 65.

[01:01:32] And I guess the strategy is quite

[01:01:34] important here as well, which is you're

[01:01:35] saying to hold these for a long time.

[01:01:37] Try not to buy and sell.

[01:01:39] And and try and look at where the cycle

[01:01:41] has been. And I can tell you, and you

[01:01:43] can see it for yourself, there has been

[01:01:45] an enormous cycle in favor of the S&P,

[01:01:48] in favor of the American market over the

[01:01:50] rest of the world. And do you think

[01:01:53] America is going to keep on gaining on

[01:01:55] the rest of the world?

[01:01:56] And of course you're going to say yes

[01:01:57] now, because that's

[01:01:59] that's the flavor of this market. We

[01:02:02] think that what is good today will

[01:02:04] continue being good indefinitely, even

[01:02:06] though history tells you that is

[01:02:08] absolutely not the case.

[01:02:10] We live in a world that tends to rotate

[01:02:12] from one to the other. We believe in a

[01:02:14] world that extrapolates today's

[01:02:16] conditions. And you can easily prove

[01:02:17] that. The stock market is not efficient.

[01:02:19] The stock market extrapolates today's

[01:02:21] conditions. If they are terrible

[01:02:24] in 1982, they will take crushed earnings

[01:02:28] and multiply it by seven times earnings.

[01:02:31] And then, in 2000, peak profit margins

[01:02:35] times, woo, 35 times earnings. They

[01:02:37] double count in the worst way. When

[01:02:40] times are good, you multiply it by a

[01:02:42] lot. That's another way of saying you

[01:02:44] extrapolate it into the distant future.

[01:02:47] You assume it's going to continue.

[01:02:48] And Keynes, of course, my hero, says,

[01:02:50] "Of course that's

[01:02:52] extrapolation is the convention you

[01:02:54] adopt, even though you know from

[01:02:55] personal experience that the world is

[01:02:57] not that way."

[01:02:58] You didn't use the word crypto

[01:03:00] when you're talking about investment

[01:03:01] strategies. How much crypto do you own?

[01:03:03] None.

[01:03:04] Have you ever owned any crypto?

[01:03:06] No.

[01:03:07] Will you ever own any crypto?

[01:03:08] No.

[01:03:08] Will you ever advise anyone to buy

[01:03:10] crypto?

[01:03:10] No.

[01:03:12] Why?

[01:03:14] I think it's a

[01:03:16] an unnecessary

[01:03:18] uh

[01:03:19] piece of uh

[01:03:21] nonsense.

[01:03:22] It facilitates nothing except criminals

[01:03:25] moving money

[01:03:26] so they can't be seen.

[01:03:28] It's not a store of value since it

[01:03:30] bounces around all over the place just

[01:03:32] down from 120 to 60

[01:03:34] because it felt like it. So, it's not

[01:03:36] stable. It's volatile as hell.

[01:03:39] It's not used conveniently as a medium

[01:03:41] of exchange. You can't go into a shop

[01:03:43] and use it easily.

[01:03:45] It does one thing

[01:03:46] very, very well.

[01:03:48] It's a means of speculating beautifully.

[01:03:52] Do you think Bitcoin's going to go to

[01:03:53] zero?

[01:03:54] Well,

[01:03:55] in the distant future, yes, it will

[01:03:56] certainly go to zero, but it may take a

[01:03:58] long time.

[01:04:00] And and, you know, in the distant

[01:04:02] future, everything goes to zero, so

[01:04:05] What about property as an investment?

[01:04:07] Because the first sort of reaction most

[01:04:08] people have when they have enough money

[01:04:10] to make an investment or to buy

[01:04:12] something is they buy a property as an

[01:04:14] investment asset. So, people go buy

[01:04:16] themselves a house, they'll move into

[01:04:17] it. We're kind of told that that's how

[01:04:18] you start to accumulate wealth is you go

[01:04:20] buy yourself a house.

[01:04:22] What do you think of that?

[01:04:23] It's hard to imagine how it could be a

[01:04:25] good decision

[01:04:27] when uh there's such an increasing

[01:04:28] fraction of people

[01:04:30] who can't afford it.

[01:04:32] And there is a political resistance, you

[01:04:34] know.

[01:04:34] Doesn't that just mean that the if, you

[01:04:35] know, if I buy one now and increasingly

[01:04:38] people can't afford one, doesn't that

[01:04:39] mean that my my house is going to be

[01:04:41] worth more in 10 years' time?

[01:04:43] No, if people can't afford it, there's

[01:04:44] no one bidding.

[01:04:46] And by the way, the population is going

[01:04:48] to decline.

[01:04:50] Young family formations are already

[01:04:52] declining in

[01:04:54] many of the richer countries.

[01:04:56] And if you have family formations

[01:04:58] declining and you have super expensive

[01:05:01] houses, what do you think is going to

[01:05:03] happen? Now, you could say, "Well,

[01:05:04] perhaps there will be a mysterious

[01:05:06] increase in family formations."

[01:05:08] And that the chronic baby bust that we

[01:05:11] maybe will talk about soon. Um, we'll

[01:05:14] stop.

[01:05:18] I don't speak Vietnamese, but this show

[01:05:20] can because of AI video technology from

[01:05:22] our sponsor, HeyGen. I get messages

[01:05:24] every single week from those of you

[01:05:25] listening to the Diary of a CEO all

[01:05:27] around the world, and you express how

[01:05:28] much impact it's had on you and your

[01:05:30] life. And if that's true, then those

[01:05:32] conversations shouldn't only reach

[01:05:33] people in English. HeyGen can take one

[01:05:35] recording of me and deliver it in any

[01:05:37] language while keeping my voice, timing,

[01:05:39] and expressions intact. But you don't

[01:05:42] need a studio like this to make it work

[01:05:44] for you. Record 15 seconds of yourself

[01:05:47] and get an AI avatar that delivers

[01:05:49] studio-quality video in over 175

[01:05:52] languages. We're up to 20 languages now,

[01:05:55] and we're not the only ones using it.

[01:05:57] HeyGen is already used by 30 million

[01:05:59] people, including 85% of the Fortune

[01:06:02] 100. Whether you're building an audience

[01:06:03] on social media, launching an online

[01:06:05] course, or rolling out training across

[01:06:06] your team, check out HeyGen now. Your

[01:06:09] first three videos are totally free at

[01:06:11] heygen.com/doac.

[01:06:14] That's h e y g e n .com/doac.

[01:06:18] See you there.

[01:06:19] This is something that I've made for

[01:06:21] you. I've realized that the Diary of a

[01:06:22] CEO audience are strivers, whether it's

[01:06:24] in business or health. We all have big

[01:06:26] goals that we want to accomplish. And

[01:06:28] one of the things I've learned is that

[01:06:30] when you aim at the big, big, big goal,

[01:06:32] it can feel incredibly psychologically

[01:06:36] uncomfortable because it's kind of like

[01:06:37] being stood at the foot of Mount Everest

[01:06:39] and looking upwards. The way to

[01:06:40] accomplish your goals is by breaking

[01:06:42] them down into tiny, small steps, and we

[01:06:45] call this in our team the 1%. And

[01:06:47] actually, this philosophy is highly

[01:06:49] responsible for much of our success

[01:06:51] here. So, what we've done so that you at

[01:06:53] home can accomplish any big goal that

[01:06:55] you have is we've made these 1% diaries,

[01:06:58] and we released these last year, and

[01:07:00] they all sold out. So, I asked my team

[01:07:02] over and over again to bring the diaries

[01:07:04] back, but also to introduce some new

[01:07:05] colors and to make some minor tweaks to

[01:07:07] the diary. So, now we have a better

[01:07:10] range for you. So, if you have a big

[01:07:13] goal in mind and you need a framework

[01:07:15] and a process and some motivation, then

[01:07:17] I highly recommend you get one of these

[01:07:19] diaries before they all sell out once

[01:07:21] again. And you can get yours at the

[01:07:23] diary.com.

[01:07:25] And if you want the link, the link is in

[01:07:26] the description below.

[01:07:27] Let's talk about the chronic baby bust.

[01:07:31] I've been hearing a lot in the news. I

[01:07:32] think there were some articles that

[01:07:33] actually came out this week in the New

[01:07:34] York Times that talked about the

[01:07:36] declining fertility rates and how young

[01:07:38] couples like me, I'm in a you know, I'm

[01:07:41] I'm engaged to a young woman who

[01:07:44] and me and me and her are trying to have

[01:07:45] a child now.

[01:07:47] Um it's not not always a straight line

[01:07:50] to having a child. Yeah, I think you're

[01:07:51] kind of sold the idea that it is, that

[01:07:52] you just have sex without a condom and

[01:07:54] then a baby appears, but um lots of

[01:07:56] young families and lots of my friends

[01:07:58] who are trying to have kids have gone

[01:07:59] for a couple of years

[01:08:01] trying and struggling to con- to

[01:08:03] conceive. So much so that after doing

[01:08:05] this podcast, I started telling some of

[01:08:08] my friends that I actually think it's a

[01:08:09] good idea to start freezing your eggs,

[01:08:11] embryos, sperm.

[01:08:13] Because if it is going to get

[01:08:14] increasingly harder, then there might

[01:08:16] need to be

[01:08:17] um medical interventions, IVF,

[01:08:20] um etc.

[01:08:22] for me and my friends.

[01:08:23] If we are if we you know, if we want to

[01:08:25] have families. But the the problem is as

[01:08:26] well at like 33 years old, um if you

[01:08:29] look at the data, you're not at your

[01:08:30] peak necessarily in terms of fertility.

[01:08:32] You're somewhere you're coming down the

[01:08:34] slope as a man. Um and but also as a

[01:08:37] woman.

[01:08:38] And so, you're kind of fighting time a

[01:08:39] little bit it feels like.

[01:08:41] Yeah, you are.

[01:08:41] And I think my partner feels the same

[01:08:43] way that we wish we were told a little

[01:08:44] bit earlier about family planning.

[01:08:46] And then I hear that about this fert-

[01:08:48] these fertility issues that apparently

[01:08:49] have been caused by toxins

[01:08:52] and that sort of chemicals in our

[01:08:53] environment. You have spent a long time

[01:08:56] thinking, writing, talking about this.

[01:08:58] Yes.

[01:08:58] I guess the first question is why? Why

[01:09:00] is a guy that's known for managing

[01:09:01] billions and billions and billions of

[01:09:03] hundreds of billions of dollars talking

[01:09:04] about fertility?

[01:09:07] And this sort of baby bust.

[01:09:09] Well,

[01:09:10] starting

[01:09:12] 27 years ago with the

[01:09:14] foundation, we were committed to start

[01:09:17] thinking about everything to do with the

[01:09:19] climate. And and you're moving in the

[01:09:22] right circle then, because the next

[01:09:24] thing is we started to worry about the

[01:09:26] cataclysmic decline in insects. I don't

[01:09:28] know if you're aware of this, but

[01:09:30] insects appear to have dropped in

[01:09:31] biomass, the weight of the flying

[01:09:33] insects, by 50 to 75%.

[01:09:36] Really?

[01:09:37] In the last 60, 70 years.

[01:09:40] And E.O. Wilson, the famous ant man, he

[01:09:43] believed that you know, nature could

[01:09:45] handle

[01:09:46] the loss of humans easily, effortlessly,

[01:09:49] but it could not handle the loss of of

[01:09:51] insects. That insects are in in the

[01:09:53] sense, he felt,

[01:09:55] and and his fellow experts, he

[01:09:57] represented them as thinking the same

[01:09:58] way, that they Insects are the bedrock

[01:10:01] of nature.

[01:10:02] And if they start to go out of business,

[01:10:04] then the

[01:10:05] birds who feed on on them and the

[01:10:07] amphibians, they start to decline, which

[01:10:09] they have done also catastrophically.

[01:10:12] One thing leads to another, and the

[01:10:15] beetles are no longer

[01:10:16] recycling the forest floor, and

[01:10:19] eventually things won't grow, and

[01:10:22] no one to uh

[01:10:24] fertilize the plants, and the damage

[01:10:26] spreads, and he felt that eventually

[01:10:28] loss of insects would lead to a more or

[01:10:30] less complete failure of nature.

[01:10:33] And and

[01:10:34] we would inherit a planet that was no

[01:10:36] longer conducive to humans.

[01:10:38] We noticed that some of the same effects

[01:10:41] are felt uh by humans.

[01:10:44] And uh a report came out,

[01:10:47] Shanna Swan and Hagai Levine,

[01:10:50] I think it finished in 2011,

[01:10:52] and uh it made the case

[01:10:54] that uh sperm count had been dropping

[01:10:57] had almost halved since the first

[01:11:00] reports academic reports in 1970.

[01:11:03] So, I immediately said this has the

[01:11:05] feeling of something that is really

[01:11:07] important.

[01:11:08] We got to study the data and the results

[01:11:11] came out suggesting that the decline

[01:11:13] rate was accelerating. The decline rate

[01:11:15] this year is 2 and 1/2% a year. You

[01:11:17] don't have to be mathematically that

[01:11:19] literate to realize that a 2 and 1/2%

[01:11:21] decline in your sperm count every year

[01:11:24] is a disastrous level, a non-sustainable

[01:11:27] level, right?

[01:11:28] How long is that going to take for this

[01:11:30] my sperm to basically not work?

[01:11:31] As far as we can tell, our best guess

[01:11:35] is

[01:11:36] that in hunter-gatherer days we had 118

[01:11:39] million units per milliliter of sperm.

[01:11:42] And when the academics came in in 1970,

[01:11:45] uh

[01:11:46] it was down to about 100.

[01:11:49] And today it's 35.

[01:11:51] Okay?

[01:11:52] Also, the quality

[01:11:54] and the mo- motility they call it had

[01:11:57] also declined

[01:11:59] somewhat similarly.

[01:12:01] It turns out, luckily for us, that we

[01:12:03] were over-engineered at I like to say

[01:12:05] like a great Victorian bridge.

[01:12:08] Nature doesn't take any risks and and

[01:12:11] you have more than you need. And it it

[01:12:13] appears, again, a good guess is about 45

[01:12:16] million units

[01:12:18] is what you need to be able to get

[01:12:20] pregnant without any difficulty. And

[01:12:22] that was hit about 15 to 20 years ago.

[01:12:25] The number of young couples who needed

[01:12:27] help 15 or 20 years ago

[01:12:30] uh was nil, basically.

[01:12:32] And for this reason, that none of them

[01:12:35] had a a chronic lack of sperm count in

[01:12:38] round numbers.

[01:12:40] And now

[01:12:42] the World Health says it's about

[01:12:45] 17%.

[01:12:46] Okay? 17% of young couples could use

[01:12:48] some help today.

[01:12:50] It which means that instead of, you

[01:12:52] know, just trying for a week or two or

[01:12:54] three or four or five or six you're

[01:12:56] trying for months and months.

[01:12:58] And

[01:12:59] everybody knows people now who fall in

[01:13:02] that category. Which is exactly what you

[01:13:04] would expect if you've gone from zero to

[01:13:06] 17%.

[01:13:07] But this is the killer. Shanna Swan

[01:13:10] and my colleague and I kind of thought

[01:13:12] about this thing separately and

[01:13:13] independently and we

[01:13:15] we worked out doesn't take a great brain

[01:13:19] that in 20 to 25 years the young couple

[01:13:22] will need help. I mean this is tomorrow.

[01:13:25] You know this is not 200 years from now.

[01:13:27] In 20 to 25 years the average young

[01:13:30] couple will need help getting pregnant.

[01:13:32] Dr. Swan's projection indicates that if

[01:13:35] the current rate of decline continues

[01:13:37] unchecked the medium male sperm count is

[01:13:41] on track to hit zero

[01:13:43] by 2045.

[01:13:46] Wow, yeah.

[01:13:49] [laughter]

[01:13:50] That is

[01:13:51] that means the medium couple is not

[01:13:53] going to have children without a lot of

[01:13:55] help.

[01:13:56] It means half the male population will

[01:13:59] have zero viable sperm and the remaining

[01:14:02] half will be right on the edge of

[01:14:05] functional infertility.

[01:14:06] A few of them will still have plenty and

[01:14:09] maybe 10% who are really perfectly

[01:14:12] in decent condition.

[01:14:13] Because there's a huge distribution

[01:14:15] range today.

[01:14:17] You know there are there are people

[01:14:18] today who still have 200 million you

[01:14:20] know better than the hunter-gatherers.

[01:14:22] But it's uh

[01:14:25] And what is causing this and how do we

[01:14:27] stop it?

[01:14:28] Shanna would say the environment around

[01:14:31] you

[01:14:32] of mainly plastics.

[01:14:33] Plastics are leaching

[01:14:36] uh toxins and the particles of plastics

[01:14:38] you have in your brain and in your body

[01:14:42] which we now know is quite substantial

[01:14:44] are also leaching toxins.

[01:14:48] And these toxins are what they call

[01:14:50] endocrine disruptors. They mess with

[01:14:51] your hormones.

[01:14:54] You should expect them to lower your

[01:14:56] fertility.

[01:14:57] And yet, the people who specialize

[01:15:00] in fertility problems

[01:15:02] and write books about it, none of them

[01:15:05] mention toxicity.

[01:15:06] They mention the hundred perfectly solid

[01:15:08] reasons why people are choosing

[01:15:11] uh to have fewer children.

[01:15:12] Endocrine disrupting chemicals like

[01:15:14] phthalates,

[01:15:16] Like phthalates.

[01:15:17] which are found in cosmetics, shampoos,

[01:15:18] food packaging, etc. They actively lower

[01:15:21] testosterone production in male fetuses

[01:15:22] during the first trimester, permanently

[01:15:24] stunting reproductive reproductive

[01:15:26] capacity before birth.

[01:15:29] Yes.

[01:15:29] BPAs, which are um what they call the

[01:15:32] biphosphonates?

[01:15:34] Yes. Something like that.

[01:15:35] Used to make plastics hard, line tin

[01:15:38] cans, and coat thermal store receipts.

[01:15:41] Um they are synthetic estrogens. They

[01:15:42] flood the male body with female hormones

[01:15:44] and signals crashing sperm count and

[01:15:46] motility.

[01:15:47] PFAs, forever chemicals used in nonstick

[01:15:50] pans, teflons, waterproof rain jackets,

[01:15:52] and stain resisting carpets. They break

[01:15:55] down in nature, accumulate in human

[01:15:57] blood, and are directly linked to lower

[01:15:58] sperm volume. And then the microplastics

[01:16:00] you talked about, the chosen chose

[01:16:02] Trojan horse. One of the shocking things

[01:16:04] that I read was that it's been

[01:16:05] discovered that they are physically

[01:16:06] embedded in human placentas.

[01:16:08] Yes. Isn't that amazing?

[01:16:10] Breast milk and human testicles. And

[01:16:12] there was a major study, I think we all

[01:16:13] heard about in 2024, that found

[01:16:15] microplastics in 100% of human

[01:16:19] testicular tissues tested.

[01:16:22] 100%. And lastly, biological stresses.

[01:16:24] So, me and you being sat down on these

[01:16:26] chairs,

[01:16:27] heats our testicles to a point where the

[01:16:29] sperms die. Heated car seats, hot

[01:16:31] laptops, they actively cook the sperm.

[01:16:35] And lastly, obesity.

[01:16:37] Yes. And of course, smoking you, which

[01:16:39] somehow slipped through the net.

[01:16:41] Yeah.

[01:16:41] But um

[01:16:42] there is a whole other branch,

[01:16:44] pesticides on your food. Now, if you

[01:16:46] give me time, I'll tell you about these

[01:16:48] two little studies.

[01:16:50] They're very small, and you might ignore

[01:16:52] them except they were done by Harvard

[01:16:54] and Mass General, which is candidate for

[01:16:56] the best hospital in America.

[01:16:59] And, uh they had a clinic for people

[01:17:02] having problem getting pregnant.

[01:17:04] And, uh they they ran it out of that.

[01:17:07] They had 180 men.

[01:17:09] And, they got them to self-report on

[01:17:11] what they were eating. Were they eating

[01:17:12] the dirty dozen? Were they eating melons

[01:17:15] and bananas that have lots of

[01:17:17] protection?

[01:17:18] At the end of uh 6 months,

[01:17:22] the the guys who reported to eat the

[01:17:24] least bad

[01:17:25] versus the quarter that ate the worst,

[01:17:28] there was a doubling of sperm count. Can

[01:17:30] you believe it? At the top category, the

[01:17:32] more fruit and veggies you ate, the

[01:17:34] better your sperm count. In the bottom

[01:17:36] quartile, the more they ate, the worse

[01:17:38] their sperm count.

[01:17:39] It was a dramatic result, but two to one

[01:17:42] between the top and the bottom. And,

[01:17:44] then 2 years later, they did a very

[01:17:45] similar study with women who were having

[01:17:47] trouble.

[01:17:49] And, at the end of their 9 months of

[01:17:51] self-reporting, the ones who ate the

[01:17:53] least badly had 68% successful live

[01:17:56] births, bearing in mind this was a

[01:17:58] fertility clinic, and the bottom

[01:18:00] quartile 38%. So, once again, nearly

[01:18:03] double.

[01:18:04] I mean, and and it's life and death. I

[01:18:06] mean, these are really important. And,

[01:18:07] this was only based on what they ate.

[01:18:11] Because pesticides are full of these

[01:18:14] toxins, and they are delivered straight

[01:18:17] into your body. You eat the damn things.

[01:18:19] It's not just they're on the surface.

[01:18:21] You can wash some of that away, but

[01:18:22] they're impregnated part of the

[01:18:24] structure of the berry.

[01:18:27] Berries,

[01:18:28] apples, pears, peaches,

[01:18:31] and finally,

[01:18:32] um uh spinach uh are really bad and are

[01:18:34] the top end. The bananas and the

[01:18:36] oranges, and the melons are uh fine. So,

[01:18:40] if you eat these damn things that

[01:18:42] designed to kill our cousins, the

[01:18:44] insects, and and the weeds,

[01:18:47] and the funguses, why would you expect

[01:18:49] them not to do a terrible job on humans?

[01:18:51] And we stuff them in our system.

[01:18:54] And the fetus, it turns out, is 100 to

[01:18:57] 1,000 times more vulnerable

[01:19:00] than we are out in the out in the world.

[01:19:03] For example, if your mother smokes,

[01:19:05] it's going to do about the same damage

[01:19:08] as if you smoked for the rest of your

[01:19:09] life.

[01:19:10] Hm. Wow.

[01:19:12] And you think about what the fetus is

[01:19:13] plugged into the system, and how it's

[01:19:16] forming everything. It doesn't seem the

[01:19:18] most unreasonable thing that it would be

[01:19:19] much more sensitive. And there are

[01:19:21] people out there

[01:19:23] fussing quite reasonably about the first

[01:19:25] 1,000 days of life.

[01:19:27] But actually, that is nothing like as

[01:19:30] important

[01:19:32] as the 270 days in the womb.

[01:19:35] Atrazine.

[01:19:37] Have you heard of atrazine?

[01:19:38] have.

[01:19:38] Atrazine, um referred to as the chemical

[01:19:41] castrator. It is the second most widely

[01:19:43] used herbicide in the United States,

[01:19:45] sprayed heavily on things like corn and

[01:19:47] sugar canes.

[01:19:48] And there was this crazy study which was

[01:19:50] peer-reviewed out of UC Berkeley that

[01:19:53] showed exposure to atrazine at levels

[01:19:56] below the EPA's considered safe for

[01:19:59] drinking

[01:20:01] um levels, completely chemically

[01:20:03] castrated male frogs, turning 10% of

[01:20:07] them into fully functional females

[01:20:10] capable of laying eggs. In humans, it is

[01:20:13] linked to severe drops in sperm motility

[01:20:15] and testosterone.

[01:20:16] And yet, we avoid the topic.

[01:20:19] We avoid the topic because it's

[01:20:21] it's pessimistic. We're not fighting the

[01:20:23] data.

[01:20:24] We just don't want to talk about it.

[01:20:26] want to talk about it. We don't want to

[01:20:27] talk about bear markets.

[01:20:29] We don't want to talk

[01:20:31] about bad climate changes, even though

[01:20:34] it's bludgeoning us. This year could be

[01:20:36] the worst

[01:20:38] hot year

[01:20:40] in history.

[01:20:41] We are set up

[01:20:43] because of the accident of the El Niño

[01:20:46] to have perhaps the worst droughts and

[01:20:48] the hottest weather ever recorded,

[01:20:51] starting about now.

[01:20:53] So, brace yourselves. But, we don't want

[01:20:54] to talk about that. We don't want to

[01:20:56] talk about toxicity. We don't want to

[01:20:58] talk about running out of resources. Oh,

[01:21:00] we just don't do bad news. And I have

[01:21:03] never seen anything like this, this

[01:21:05] fertility thing, where the data is

[01:21:07] horrific. The baby bust is measurable.

[01:21:11] The sperm count is one of the few things

[01:21:13] you can really measure. Do they really

[01:21:15] think if you have declining sperm count,

[01:21:17] the future is great?

[01:21:19] Do they really think that the economy

[01:21:20] will function

[01:21:22] if the number of 20-year-olds entering

[01:21:24] the market starts to drop like a stone?

[01:21:26] In Japan, you know what their

[01:21:27] 20-year-old is? It's 50% of what it was

[01:21:31] in 1948.

[01:21:32] What is 50%?

[01:21:32] 50%. Not down 15 or 3.5, 50% less.

[01:21:37] 50% less 20-year-olds?

[01:21:39] 20-year-olds that drive the market, that

[01:21:41] offer themselves for military service.

[01:21:43] What do we do about this?

[01:21:44] We have two things.

[01:21:46] We've got to

[01:21:47] detoxify the world, which is

[01:21:50] intellectually easy. You ban poisonous

[01:21:53] chemicals.

[01:21:54] And we've made in the EU

[01:21:57] pretty good start.

[01:21:58] My favorite example and everybody's

[01:22:00] favorite example is cosmetics.

[01:22:02] Cosmetics, you don't actually eat it,

[01:22:04] but you rub it on your skin, which is

[01:22:05] the second worst thing to do.

[01:22:08] And there are 10,000 chemicals in

[01:22:10] cosmetics.

[01:22:12] And the EU has banned 1,500. If they ban

[01:22:14] the right 1,500, that could be 3/4 of

[01:22:17] the battle, right? Canada's banned 550.

[01:22:20] And the US has banned 12. I am not

[01:22:23] kidding you.

[01:22:24] So, The thing about toxicity is it is

[01:22:27] regional. If one country if Denmark or

[01:22:30] the EU or the UK wants to look after its

[01:22:32] chemicals, they will live longer and

[01:22:34] have better health. If the US wants to

[01:22:37] put the corporations first, they will

[01:22:39] have shorter lives. Do you know the life

[01:22:41] expectancy difference between the US and

[01:22:44] Sweden has gone from 2 years to 6 years

[01:22:46] in the last 70 years?

[01:22:48] I wrote in my quarterly letter my estate

[01:22:50] would be willing to bet you that in 50

[01:22:52] years it'll be 8 or 10.

[01:22:54] I don't quite think people in the United

[01:22:55] States realize the difference in the

[01:22:59] products they consume here versus other

[01:23:01] parts of the world. And you know,

[01:23:03] No, absolutely not.

[01:23:04] Brits fly over here and actually we had

[01:23:06] my my barber my my barber Damon and he

[01:23:08] flew over here to give me a haircut last

[01:23:09] week. He said, "Oh gosh, I don't feel

[01:23:11] good." He said, "I went and got some

[01:23:12] food here and I really just don't feel

[01:23:14] good." And he says, "Every time I come

[01:23:15] over here I don't feel good." And me and

[01:23:16] my team we used to fly over here before

[01:23:18] I moved here for a couple of weeks a

[01:23:19] year to film the show and whenever we'd

[01:23:21] fly back not only would I be much

[01:23:22] fatter, um but we'd all feel a little

[01:23:24] bit more like sluggish, is the way I'd

[01:23:26] describe it, from eating the food here.

[01:23:28] And it almost felt quite clear that

[01:23:29] there's like something in the food that

[01:23:31] our bodies

[01:23:32] just isn't used to in the UK. And when

[01:23:34] you look at the toxicity of the United

[01:23:37] States versus Europe, it's quite clear.

[01:23:40] I mean, the US currently permits the use

[01:23:41] of 85 agricultural pesticides that are

[01:23:44] completely banned in the EU, China and

[01:23:47] Brazil. The US sprays over 300 million

[01:23:51] pounds per year of pesticides that are

[01:23:53] deemed too dangerous to be legally used

[01:23:55] in Europe, including that one I said

[01:23:58] about the frog's called atrazine.

[01:24:00] atrazine

[01:24:01] Which the EU banned over two decades

[01:24:03] ago. We look at cosmetics, which you

[01:24:05] were talking about then, what you put on

[01:24:07] your skin obviously goes into your

[01:24:08] bloodstream and so the EU has banned or

[01:24:10] heavily restricted over 1,300 chemicals

[01:24:13] in cosmetics and personal care products

[01:24:15] due to toxicity and hormone disruption.

[01:24:18] The US and the FDA has banned 11. In

[01:24:21] terms of food, the US allows potassium

[01:24:23] bromate, which is a known carcinogen,

[01:24:26] cancer-causing, used to make fluffy

[01:24:28] dough bread, and BHA

[01:24:31] {um} / BHT, which are preservatives

[01:24:33] linked to hormone disruption. Both are

[01:24:35] strictly banned from human consumption

[01:24:37] in the UK and EU and Canada and China.

[01:24:39] And lastly, the US {um} allows titanium

[01:24:43] dioxide, used to make candy smell like

[01:24:45] Skittles bright white,

[01:24:47] and synthetic dyes like red 40, which

[01:24:49] require strict warning labels or

[01:24:52] outright bans in Europe due to DNA

[01:24:54] damage and neurodevelopmental issues in

[01:24:57] kids. I'll give you one more. A recent

[01:24:59] US Geological Survey found that at least

[01:25:02] 45% of all US tap water is contaminated

[01:25:06] with PFAs, those forever chemicals we

[01:25:08] talked about earlier, the very chemicals

[01:25:10] directly linked to crashing sperm counts

[01:25:12] and testicular cancer. The US has

[01:25:14] historically allowed PFAs levels in

[01:25:17] drinking water

[01:25:19] drastically higher than the EU, the

[01:25:21] United the European Union

[01:25:23] considers safe.

[01:25:24] Let us just say that the EU is forever

[01:25:27] giving exemptions and extensions and is

[01:25:30] far from perfect and has a lot of

[01:25:32] corporate pushback. And uh it's just

[01:25:34] much less bad than the US.

[01:25:37] And the US has worse life expectancy.

[01:25:39] It does, and it's the only rich country

[01:25:41] in the world where 15 years ago they had

[01:25:44] the same life expectancy as they have

[01:25:45] today.

[01:25:46] One um actionable piece of advice for

[01:25:48] anyone listening that might find this

[01:25:50] all quite um

[01:25:52] overwhelming cuz you know, lots of

[01:25:54] things around us from receipts to the

[01:25:56] pans we use to

[01:25:57] range jackets contain these chemicals,

[01:26:00] is there are apps out there

[01:26:02] where you can scan the chemicals in the

[01:26:05] foods that you're buying to check if

[01:26:07] they contain these endocrine disrupting

[01:26:09] these hormone disrupting chemicals. I'm

[01:26:11] not affiliated [clears throat] with any

[01:26:12] of them, but there's one called Yuka,

[01:26:14] YUKA, that I know is very easy for sort

[01:26:17] of everyday scanning of products. You

[01:26:18] can just scan the barcode and it'll tell

[01:26:20] you it'll give it a rating score out of

[01:26:21] 100. There's EWG's Healthy Living

[01:26:25] um app which is the scientific gold

[01:26:26] standard run by the Environmental

[01:26:28] Working Group a major toxic chemical

[01:26:30] watchdog. You can scan barcodes or

[01:26:31] search for food, cleaning supplies or

[01:26:33] cosmetics. There's Think Dirty as well

[01:26:35] which is great for cosmetic shampoos and

[01:26:37] skin care. It exposes the toxic truth

[01:26:39] hiding in beauty products. Um and then

[01:26:41] there's Clear Ya which is Clear Ya. Best

[01:26:44] for online shopping. It's an app in your

[01:26:46] web browser and instead of scanning

[01:26:48] barcodes in your house

[01:26:50] while you're shopping online, it's so if

[01:26:51] you add a say like a shampoo or lotion

[01:26:53] to your Amazon or Target or Walmart

[01:26:54] basket, it automatically pops up with an

[01:26:57] alert telling you about the ingredients

[01:26:59] list that is within those chemicals. But

[01:27:01] but I think that gives something a

[01:27:03] little bit actual and arms you with at

[01:27:05] least a tool to navigate this crazy

[01:27:06] environment. And obviously AI is great

[01:27:07] at this as well. You can take pictures

[01:27:08] of things and ask it questions.

[01:27:10] And what we really need is a kind of

[01:27:11] green Amazon where everything is

[01:27:13] guaranteed food, bed, clothes,

[01:27:16] everything.

[01:27:18] And that would be very handy indeed.

[01:27:20] Someone you could trust that would

[01:27:22] absolutely guarantee the whole line of

[01:27:24] products that you would order. Not

[01:27:26] impossible and I think done well and

[01:27:28] someone could make money at it.

[01:27:30] What would advice would you give to your

[01:27:31] kids on a personal level if they're

[01:27:32] trying to stay healthy in a toxic world?

[01:27:35] Simple advice and I know you like this

[01:27:38] is pregnant women are much more

[01:27:40] important than anybody else in this

[01:27:42] field.

[01:27:43] If you could persuade pregnant women A

[01:27:46] to have no cosmetics, save a lot of

[01:27:47] money, no cosmetics for 9 months and

[01:27:50] then B invest some of that money from

[01:27:52] your cosmetics or all of it in buying

[01:27:55] organic berries if you have to have

[01:27:58] berries, apples, oranges, peaches

[01:28:01] what they call the dirty dozen here.

[01:28:03] If you did that

[01:28:05] I think as much as half of all the

[01:28:07] trouble disappears.

[01:28:09] And that's a huge fraction and it's

[01:28:11] easily acquired.

[01:28:13] You know, I I I addressing the 100

[01:28:15] things around in your environment, you

[01:28:17] have to get to that.

[01:28:19] Typically, if you're lucky, you do one

[01:28:21] thing after another. You get the gas

[01:28:22] stove first, which is really noxious,

[01:28:25] and then you work your way the black

[01:28:27] plastics, the Teflon frying pan. You

[01:28:30] work your way around it. Compared to

[01:28:32] that,

[01:28:33] no cosmetics, no bad food,

[01:28:38] or make it organic. That's a piece of

[01:28:41] cake. That is easy. It will save you

[01:28:44] huge amount that you will never

[01:28:45] appreciate because you'll never know how

[01:28:47] much better your children are than they

[01:28:49] would have been.

[01:28:50] Mhm.

[01:28:51] But, it's not only your children, by the

[01:28:53] way.

[01:28:54] For women, you know, you're talking

[01:28:56] about in particular because of the eggs,

[01:28:59] they are Every egg is all there in the

[01:29:01] womb.

[01:29:03] And then it goes on to your

[01:29:04] grandchildren, we thought. At least we

[01:29:07] could prove two generations. And and and

[01:29:09] a recent study suggests it might be many

[01:29:11] more generations than two. So, you got

[01:29:15] some of these chemicals

[01:29:16] impregnated in your system, and your

[01:29:18] children pay the price, and your

[01:29:20] grandchildren, and perhaps even

[01:29:23] quite a few generations after that.

[01:29:26] I also think it would be great if

[01:29:28] Western governments around the world

[01:29:30] made the costs of

[01:29:32] both child care and but also fertility

[01:29:36] treatments

[01:29:37] significantly lower.

[01:29:39] And they will, of course.

[01:29:40] You know, I had a couple of

[01:29:41] conversations on this podcast with very

[01:29:43] successful women, including Ronda

[01:29:44] Rousey, who was in tears because she was

[01:29:46] on a

[01:29:48] I think it's her [laughter] fifth or

[01:29:49] sixth round of IVF treatments, and she

[01:29:51] just found out just before she walked

[01:29:52] into the studio that it hadn't gone

[01:29:54] well.

[01:29:55] And watching her cry

[01:29:56] about it and get very emotional meant

[01:29:58] that that that day I walked out of this

[01:30:00] room and like called a lot of the people

[01:30:01] in my life that I know are

[01:30:03] you know, in the region where fertility

[01:30:05] starts to decline, and really encourage

[01:30:08] them to start thinking if they if that's

[01:30:10] what they want in their lives about

[01:30:11] family planning, which is like getting

[01:30:13] your eggs frozen or your embryos frozen.

[01:30:15] And me and my partner actually went and

[01:30:16] did it. We got our embryos frozen, which

[01:30:19] was a you know, it's it's not it's it's

[01:30:20] both expensive, extremely expensive,

[01:30:23] especially here in the United States,

[01:30:25] and difficult.

[01:30:26] And psychologically destructive. Brutal.

[01:30:28] You know, we you know, me every day for

[01:30:32] a couple of weeks injecting her with

[01:30:33] with this this these chemicals and the

[01:30:36] the hormonal roller coaster that she had

[01:30:38] to deal with and all of that, but for us

[01:30:42] the alternative was worse,

[01:30:44] which was never being able to have

[01:30:45] children because it's difficult and

[01:30:47] there's all these toxins in our

[01:30:48] environment and and so on and so forth.

[01:30:51] And so I then became a little bit of a I

[01:30:52] guess a bit of a bit preachy within my

[01:30:54] within the people the people in my life

[01:30:55] that I love a lot about family planning

[01:30:58] cuz we kind of all thought we could just

[01:30:59] think about it later.

[01:31:01] We're all kind of 35 and we thought,

[01:31:02] "Yeah, we'll think about that later."

[01:31:04] Um but it turns out not to be the case

[01:31:06] for many people.

[01:31:07] If you'll allow me to go back, you asked

[01:31:09] an important question. What do we have

[01:31:11] to do? And I said we have to detoxify

[01:31:13] the system and then we both got off into

[01:31:15] this frenzy of of attacking chemicals,

[01:31:19] which we should anyway, but it's

[01:31:20] intellectually easy. Ban the suckers,

[01:31:23] okay? Now, putting pressure on the

[01:31:25] corporations to back off so the

[01:31:27] governments can do it would be a good

[01:31:30] idea, not easy. Corporations have

[01:31:32] enormous power, unprecedented power in

[01:31:34] the US,

[01:31:35] but but very substantial power in the in

[01:31:38] the EU and the UK also. But we have to

[01:31:41] get them to back off. We have to start

[01:31:43] banning these damn things, otherwise no

[01:31:46] children. But secondly,

[01:31:48] and much more difficult,

[01:31:50] is we have to detoxify capitalism.

[01:31:53] We have to slowly but surely

[01:31:56] turn our capitalist societal norms into

[01:32:00] much more family-friendly,

[01:32:02] children-friendly.

[01:32:04] Over the next several generations,

[01:32:06] we have to end up with a society that

[01:32:09] realizes that 2.1 healthy, well-educated

[01:32:13] children is a part of the commons. You

[01:32:15] may not have any children.

[01:32:16] you mean by that, sorry? 2.1?

[01:32:18] 2.1 is the number of children it takes

[01:32:20] for a rich society to have a steady

[01:32:23] population.

[01:32:24] Per couple?

[01:32:25] Per couple. If you have less than 2.1

[01:32:27] per couple,

[01:32:29] you fairly rapidly go out of business.

[01:32:30] If you have more than 2.1, you fairly

[01:32:33] rapidly end up with so many people

[01:32:35] you're standing on each other's

[01:32:37] shoulder. The commons are things like

[01:32:39] common land in the old days that anyone

[01:32:43] could put their sheep on. And what

[01:32:44] tended to happen is everyone put more

[01:32:46] sheep than they could stand, and they

[01:32:48] pretty soon it was

[01:32:49] it had no grass on it. Known as the

[01:32:51] tragedy of the commons.

[01:32:53] And

[01:32:55] we all need

[01:32:57] clean air,

[01:32:59] clean water,

[01:33:01] fertile soil,

[01:33:03] and 2.1 healthy, well-educated children.

[01:33:06] Without any of those, society fails.

[01:33:09] All of them have to be treated as group

[01:33:12] responsibility. So, the whole society,

[01:33:15] the whole village

[01:33:17] has to be in a way like a kibbutz

[01:33:19] eventually. You have to put everything

[01:33:21] behind making it doable

[01:33:24] to have children because the long list

[01:33:26] of economic and social reasons, as well

[01:33:29] as toxin reasons, why people can't have

[01:33:32] 2.1 children is getting so long and so

[01:33:34] dangerous. And nothing yet has worked. I

[01:33:38] mean, they've tried, you tell me, 200

[01:33:40] different things around the world.

[01:33:42] Several percentage points of GDP in one

[01:33:44] or two cases.

[01:33:46] And nothing yet has

[01:33:49] seemed seen a permanent uptick in in

[01:33:53] baby production.

[01:33:54] For the average person listening right

[01:33:56] now, Dave who drives a taxi or Jenny who

[01:33:58] works as a receptionist or um Clive who

[01:34:01] is a nurse,

[01:34:03] what is the most important thing we

[01:34:05] haven't talked about that we should have

[01:34:06] talked about as it pertains to their

[01:34:08] life today?

[01:34:10] I think they have to brace themselves

[01:34:13] for a tougher times ahead

[01:34:15] than they would have they expected.

[01:34:18] And they're beginning to get the point.

[01:34:20] Life for the last 10 or 20 years has

[01:34:22] been tougher than than they perhaps

[01:34:25] expected as children or or than other

[01:34:27] people expected for them.

[01:34:29] Part of that is politics. Part of that

[01:34:33] is equality. But the net effect of them

[01:34:35] is times are tougher. It is more

[01:34:39] difficult

[01:34:40] to buy a house or afford to rent.

[01:34:43] And and jobs are getting scarcer.

[01:34:47] It's likely to get worse.

[01:34:49] What does brace yourself mean for them?

[01:34:51] Cuz brace yourself sounds like you

[01:34:54] But does it mean

[01:34:55] Plan your life as if times will not be

[01:34:57] easy.

[01:34:58] Okay.

[01:34:59] And do not

[01:35:00] build up a little reserve of of cash.

[01:35:03] Of course my advice to

[01:35:06] other people is and and get yourself a

[01:35:09] useful job. Something that will in a

[01:35:12] larger sense pull your weight in

[01:35:14] society.

[01:35:15] Upskill, change skills, learn something

[01:35:18] mechanical

[01:35:19] fixing, repairing

[01:35:21] Things that

[01:35:21] engineering

[01:35:22] Things that will need humans.

[01:35:23] And and research, science in general.

[01:35:25] Make friends.

[01:35:27] Make friends.

[01:35:28] Make sure you're living in in a a tight

[01:35:31] society if you can. Very difficult

[01:35:33] today, obviously.

[01:35:34] Would you be thinking about the country

[01:35:36] you live in at this moment in time?

[01:35:37] Absolutely.

[01:35:38] Really? Is there any countries you

[01:35:39] wouldn't live in?

[01:35:41] [sighs and gasps]

[01:35:42] If you were Dave or Jenny?

[01:35:43] I I think I have to refuse to answer

[01:35:46] this on the grounds that it might tend

[01:35:47] to incriminate me.

[01:35:48] Um

[01:35:49] Oh, okay. So you're saying don't live in

[01:35:50] the United States?

[01:35:52] Well, I have

[01:35:53] American children and grandchildren.

[01:35:56] Why not the United States?

[01:35:57] It holds out too much chance that the

[01:36:00] social contract is

[01:36:01] is

[01:36:02] [snorts]

[01:36:02] dissolving.

[01:36:04] You know, the thing about Japan and that

[01:36:06] my joking rule 21 in investing is never

[01:36:08] extrapolate from the Japanese. They are

[01:36:10] extremely different in every way.

[01:36:13] But one of the ways they're different is

[01:36:14] they have this amazing social contract.

[01:36:17] The thing that really upsets the

[01:36:19] Japanese is if they're put in a position

[01:36:21] where they can't act in a socially

[01:36:23] responsible way.

[01:36:24] When you say social contract, what does

[01:36:26] that mean?

[01:36:26] It means an agreement that I will behave

[01:36:29] in a way that helps my neighbors and the

[01:36:31] society that I'm doing what people

[01:36:33] expect me to do. I'm not going to

[01:36:35] misbehave.

[01:36:36] And you think that's not the case here

[01:36:37] in the United States?

[01:36:38] I think the case here is that people are

[01:36:40] doing what they think is best for them

[01:36:42] and their family and screw everybody

[01:36:44] else, really.

[01:36:46] When I arrived in America, corporations

[01:36:47] had this sense that they owed something

[01:36:50] to the community they operated in, the

[01:36:52] city they operated in. They They'd build

[01:36:55] the stadium, they'd do this, they'd

[01:36:57] they'd be part of the community.

[01:37:00] Now they're not. They're all

[01:37:03] in a way cold-blooded, profit-maximizing

[01:37:05] international enterprises.

[01:37:07] And why is that a bad place to live? Cuz

[01:37:09] you're saying, you know, you probably

[01:37:10] wouldn't recommend Dave or Jenny living

[01:37:12] in the United States. Why would that be

[01:37:14] a bad place for them to be? What

[01:37:15] happens? What's the What's the

[01:37:16] downstream impact of that?

[01:37:18] That your neighbors aren't as interested

[01:37:20] in you and your well-being.

[01:37:21] Fine. I don't I won't talk to my

[01:37:23] neighbor.

[01:37:24] And that's a lonely place to be. And

[01:37:26] when you're in trouble,

[01:37:28] you're in

[01:37:30] serious trouble.

[01:37:31] Uh because the safety net here is very

[01:37:34] ineffective. There's a a measure that I

[01:37:36] think is probably the single most

[01:37:38] important measure of civilization, and

[01:37:40] that is maternal mortality. How many

[01:37:43] people die in childbirth? You know, in

[01:37:45] Nigeria out of 100,000, it's 480, give

[01:37:49] or take.

[01:37:50] And uh

[01:37:52] in America, in in the

[01:37:55] black population,

[01:37:57] it's uh 44.

[01:37:59] In the whole population, it's like 21 or

[01:38:03] 20.

[01:38:04] Curiously, in the

[01:38:07] American Asian population, it's 13.

[01:38:10] And then, you go down the list,

[01:38:13] and in Britain, it's five.

[01:38:17] In Germany, it's four.

[01:38:19] In Sweden, it's 2.1. In Norway, it's

[01:38:22] zero. There were no mothers who died

[01:38:24] last year.

[01:38:25] Hm.

[01:38:25] Or the year before. What better

[01:38:27] definition of civilization than looking

[01:38:30] after the mothers giving birth? How is

[01:38:32] it possible that a country

[01:38:36] more or less the richest in the world,

[01:38:39] it's not just that they're the worst in

[01:38:41] the rich world, it's that

[01:38:44] they are 50% worse than the next worst.

[01:38:48] 50% more mothers die here than in the

[01:38:51] second worst country in the developed

[01:38:53] world. How is that possible? The answer

[01:38:55] is it happens.

[01:38:57] And um it's because

[01:39:00] the inequality is so extreme in the

[01:39:02] medical system

[01:39:04] that if you don't have lots of money,

[01:39:05] you're quite likely to die in

[01:39:06] childbirth. I mean,

[01:39:08] Now, of course, the numbers are not

[01:39:09] huge. 20 out of 100,000 is not uh

[01:39:13] but it's but it's a terrible contrast.

[01:39:15] It's a sign of something.

[01:39:17] It's a sign of something else as well.

[01:39:19] It's a sign of whether people are

[01:39:21] It's a sign of the social contract.

[01:39:22] So, where's a good place to live then,

[01:39:24] if not here?

[01:39:25] Denmark, Japan.

[01:39:28] Uh even France, Germany. The UK has a

[01:39:32] little bit of the American disease, but

[01:39:35] not nearly as much.

[01:39:36] So, if your kids came to you and said,

[01:39:38] "Dad, we're thinking of uh leaving the

[01:39:39] United States. Should I move?

[01:39:41] Should I Should I move out of the United

[01:39:43] States?

[01:39:44] Yeah, I I would say that's a perfectly

[01:39:46] reasonable thing to consider.

[01:39:49] And where are you going and why and

[01:39:51] what's your

[01:39:52] I'm thinking of going to Denmark, Dad.

[01:39:54] Well,

[01:39:55] if they'll have you. Uh

[01:39:57] No, uh

[01:39:59] in the things that really matter, life

[01:40:01] expectancy, health,

[01:40:04] safety nets,

[01:40:05] uh murder rates,

[01:40:07] uh mortality rates,

[01:40:10] and everything that really matters, yes,

[01:40:12] they're they're day and night better.

[01:40:15] In the things that don't really matter,

[01:40:16] but look really splashy,

[01:40:18] we have enormous quantities of uh wealth

[01:40:21] created

[01:40:22] that go to a relatively small fraction

[01:40:24] of the people.

[01:40:26] And that dazzles in terms of the average

[01:40:28] because

[01:40:30] um that's how the numbers work.

[01:40:33] If you look at how well-off the bottom

[01:40:35] quartile are,

[01:40:37] America doesn't score well at all.

[01:40:40] Jeremy, we have a closing tradition

[01:40:42] where the last guest leaves a question

[01:40:43] for the next guest not knowing who

[01:40:44] they're leaving it for. The question

[01:40:45] left for you is, if you could not fail,

[01:40:49] what would your next goal be

[01:40:52] that you would set for yourself?

[01:40:55] There There was a book written

[01:40:57] in the 1960s called Silent Spring.

[01:41:01] Carl Carson, I think her name was.

[01:41:03] And it changed for a quite a number of

[01:41:05] years it it it did what books never do

[01:41:08] really it

[01:41:10] it uh became a political monster and

[01:41:13] everyone studied it and it had an

[01:41:15] effect. It changed the game.

[01:41:17] I would uh like to write something about

[01:41:22] toxicity and and social contract really.

[01:41:25] Particularly nurturing a family. We

[01:41:27] We've got to find in the end a community

[01:41:30] that encourages children. The downside

[01:41:33] of the

[01:41:34] brutally efficient capitalist system

[01:41:36] that we have. It's focus on

[01:41:39] financial achievement and so on.

[01:41:42] And

[01:41:43] very little emphasis on community and

[01:41:46] child-rearing and so on. If we don't we

[01:41:48] we fail as a society pretty quickly. We

[01:41:51] have to detoxify. We have to encourage

[01:41:55] to create an environment where people

[01:41:57] want to have children.

[01:41:59] [clears throat]

[01:41:59] If I could write a book

[01:42:01] that would be

[01:42:03] would would pull a silent spring, I

[01:42:04] would sit down tomorrow and start it.

[01:42:07] The making of a Parma bear.

[01:42:10] Parma should be in inverted commas,

[01:42:12] really.

[01:42:13] The perils of long-term investing in a

[01:42:15] short-term world.

[01:42:19] By Jeremy Grantham and Edward

[01:42:21] Chancellor.

[01:42:23] Who is this book for?

[01:42:24] Oh, people who have a interest in the

[01:42:26] stock market. It has a little bit of

[01:42:28] climate change and toxicity.

[01:42:31] My my co-rider is a professional and he

[01:42:33] tried to limit me quite sensibly.

[01:42:36] Feeling that our main market was

[01:42:37] investors who would be turned off by too

[01:42:40] much of the stuff we've been talking

[01:42:42] about.

[01:42:43] You cover things also like economics,

[01:42:46] value investing, being a bear, and

[01:42:47] predicting a bubble, and what to do

[01:42:48] about all of those things. But it's

[01:42:50] really a useful counterintuitive not

[01:42:52] counterintuitive, but it's a it's a

[01:42:54] frame of thinking that will help you be

[01:42:56] more realistic especially when

[01:42:57] psychology is prone to take over and

[01:42:59] make you wildly recklessly optimistic.

[01:43:02] And and be more confident in your

[01:43:04] judgment.

[01:43:06] Big big companies cannot advise you.

[01:43:10] It's just suicidal for their business.

[01:43:12] So you are on your own. Look at the

[01:43:15] data. A bubble is not hard to see. There

[01:43:18] is this kind of plane and then there's a

[01:43:20] Himalayan peak

[01:43:22] which eventually goes back.

[01:43:24] And I mean that's exactly what we're

[01:43:25] seeing.

[01:43:25] That's exactly what history looks like.

[01:43:29] Have the courage to look at that, make

[01:43:31] your own conclusion, get out of the

[01:43:33] dangerous most dangerous part,

[01:43:36] and and do it now.

[01:43:38] Don't wait for help because no help is

[01:43:40] coming.

[01:43:43] Large enterprises almost never get the

[01:43:46] big turning points

[01:43:48] because they can't take the career risk

[01:43:50] involved.

[01:43:51] And every big corporation needs a leader

[01:43:53] who has political skills.

[01:43:56] And the And the central political skill

[01:43:57] in life turns out to be never be wrong

[01:44:00] on your own.

[01:44:02] This is again Keynes.

[01:44:04] You know, you can be wrong in company,

[01:44:06] you can jump off the cliff together, you

[01:44:08] will never lose your job because of

[01:44:09] that.

[01:44:11] But if you do anything on your own,

[01:44:12] sooner or later you will get it wrong.

[01:44:15] And quote, you will not receive much

[01:44:17] mercy.

[01:44:19] Jeremy, thank you so much. Thank you for

[01:44:22] all that you do. Um you traverse so many

[01:44:23] subjects. It's It's absolutely

[01:44:25] fascinating and you You've made me think

[01:44:27] about so many things. I've actually

[01:44:28] written down a bunch of ideas. You sent

[01:44:29] me taking some photos then. Those are

[01:44:31] actually ideas that I want to remember.

[01:44:33] Yeah, that's what I do. Screenshot city.

[01:44:35] Yeah, so I took I just wrote things down

[01:44:37] you were saying and then I was like I

[01:44:37] need to remember that later for a bunch

[01:44:39] of things, businesses, friends, family,

[01:44:41] etc.

[01:44:42] Um and I think that's the testament to

[01:44:44] how broad and curious and wise you are.

[01:44:46] Going back to question one or two, the

[01:44:49] billionaire bit,

[01:44:50] uh sometime around the end of this year

[01:44:52] we will actually have written checks for

[01:44:54] a billion dollars

[01:44:56] to the climate change world.

[01:44:58] It's It's a wonderful thing and there's

[01:44:59] you know this particular moment in time

[01:45:01] because of the politics, climate change

[01:45:02] is a subject that's falling off the

[01:45:03] radar.

[01:45:04] It is.

[01:45:05] Uh it's

[01:45:06] being mentioned less in earnings calls.

[01:45:07] It's

[01:45:07] But this year will be so disgustingly

[01:45:09] hot from now on, I suspect.

[01:45:11] Disgustingly hot.

[01:45:12] Hot. We could have from now on the

[01:45:14] hottest 12 months from now to this time

[01:45:16] next year that we have ever had in

[01:45:18] history.

[01:45:20] Here, there, and everywhere.

[01:45:21] Well, I'm glad we've got voices like

[01:45:22] yours

[01:45:23] um lending their ideas and wisdom to

[01:45:25] these conversations and it's been an

[01:45:26] honor and a privilege to to you. Your

[01:45:28] book, The Making of a Manager, Baron, to

[01:45:29] link it below

[01:45:31] for everyone to buy it themselves.

[01:45:33] Jeremy, thank you. YouTube have this new

[01:45:35] crazy algorithm where they know exactly

[01:45:37] what video you would like to watch next

[01:45:39] based on AI and all of your viewing

[01:45:41] behavior. And the algorithm says that

[01:45:43] this video is the perfect video for you.

[01:45:46] It's different for everybody looking

[01:45:47] right now. Check this video out, and I

[01:45:49] bet you you might love it.