E78: VC fund metrics that matter, private market update, recession, student loans, Bill Hwang arrest

00:00:00.000 | Is there gonna be an open mic night in?

00:00:02.000 | We were gonna have you speak, Freedberg,

00:00:04.560 | but we realize you're not capable, so.

00:00:06.880 | We want the show to be entertaining.

00:00:08.240 | Yeah, it's not, that's not Percival, Freedberg.

00:00:11.520 | You guys are missing out.

00:00:12.880 | I'll tell you guys what makes my stand-up comedy so good.

00:00:15.280 | Oh, God, here we go.

00:00:16.080 | Oh, my God, we're back on this, Jesus Christ.

00:00:18.160 | It's my creative sensibility.

00:00:19.840 | So if I have some time to prep and write my script

00:00:23.360 | and read my own creative insights.

00:00:26.080 | Yeah, okay, bring one joke next week.

00:00:28.480 | J. Cal, for all the time we've spent together

00:00:30.720 | on this podcast, you know so little about me.

00:00:32.960 | It's so depressing, I gotta be honest.

00:00:34.880 | Well, you know, here's the thing about friendship.

00:00:36.640 | It's a two-way street, you gotta open up a little bit.

00:00:38.640 | We gotta go out and get drunk one night.

00:00:40.160 | Absolutely.

00:00:40.720 | ♪ I'm going all in ♪

00:00:42.560 | ♪ We'll let your winners ride ♪

00:00:43.840 | ♪ I'm going all in ♪

00:00:45.440 | Rain Man, David Sass.

00:00:46.720 | ♪ I'm going all in ♪

00:00:49.760 | ♪ And instead ♪

00:00:50.400 | ♪ We open-source it to the fans ♪

00:00:52.080 | ♪ And they've just gone crazy with it ♪

00:00:53.600 | Love you guys.

00:00:54.160 | ♪ I'm going all in ♪

00:00:57.840 | I just want to,

00:00:58.400 | I just want to give a shout out to this guy, Andrew Lacey.

00:01:01.440 | Okay.

00:01:01.840 | Okay.

00:01:02.400 | Shout out.

00:01:03.200 | He is the CEO of a company called Prenuvo.

00:01:06.800 | Oh yeah.

00:01:07.200 | Can you just flash it on the screen?

00:01:08.720 | Prenuvo.

00:01:10.000 | I went to Prenuvo, and what they do is,

00:01:12.080 | they do a head-to-toe MRI scan in 45 minutes,

00:01:15.600 | and they use a bunch of machine learning

00:01:18.000 | and image recognition to help a radiologist

00:01:22.480 | interpret these MRIs in real time beside you.

00:01:26.080 | It's a service that you have to pay a few thousand dollars for.

00:01:28.320 | Yeah.

00:01:28.720 | So, I went to Prenuvo, and I was like,

00:01:30.320 | "Oh, this is crazy."

00:01:31.120 | I was like, "This is crazy."

00:01:31.840 | I was like, "This is crazy."

00:01:32.240 | And then I went to the other location in Silicon Valley, in Redwood City, and a couple of others,

00:01:37.040 | and we mentioned it.

00:01:37.840 | But the reason I'm bringing this up is he sent me an email yesterday, and he said,

00:01:41.360 | "I just want to thank you and the besties for mentioning Prenuvo."

00:01:45.120 | Because we had a bunch of people come, and he said, "We found no less than 11 life-saving diagnoses."

00:01:53.440 | 11.

00:01:53.920 | 11 people.

00:01:54.480 | 11 individual listening to the pod.

00:01:56.480 | Pod saves lives.

00:01:57.440 | Went to Prenuvo.

00:01:58.240 | Went to MRI.

00:01:58.720 | Found all kinds of issues from a brain tumor and brain cancer to stomach cancer and other things,

00:02:06.560 | and was able to get the care that they needed.

00:02:10.000 | Amazing.

00:02:10.640 | Anyways, I just want to give a shout out to him for doing a lot of really important work.

00:02:14.560 | And for the folks that are listening that have some money set aside and can afford to do this,

00:02:19.280 | I would just really encourage you.

00:02:20.400 | We have no financial stake in it, nothing other than we are users of it.

00:02:23.520 | But check out prenuvo.com, and shout out to Andrew and his team.

00:02:28.160 | Yeah.

00:02:28.320 | Okay, here we go.

00:02:29.040 | Three, two, let's start the show.

00:02:30.880 | The war in Ukraine has him insane in the membrane, and Biden's new disinformation council

00:02:37.280 | is going to have him detained to calm him down from tanking Solana.

00:02:41.200 | He started smoking that marijuana.

00:02:43.520 | You know him as the Rain Man.

00:02:44.640 | He's here again, David Sacks.

00:02:45.760 | How you doing?

00:02:46.240 | Have a good week?

00:02:46.720 | Yeah.

00:02:47.520 | Not bad.

00:02:48.000 | All right.

00:02:48.960 | Big energy this week, huh?

00:02:51.440 | Okay.

00:02:51.760 | In high school, he had no friends, but thanks to the pod, undergrads are in his DMs, all forms of

00:02:58.080 | stake, he's a purge, and he's the vanguard of all the virgins, the queen of quinoa, the

00:03:04.480 | Sultan of Science, David Friedberg.

00:03:06.720 | Wait, I missed like half of that because Chamath was laughing so hard.

00:03:11.920 | I can do it again.

00:03:12.560 | Do it again.

00:03:13.120 | Do it again.

00:03:13.760 | Let me try from the top.

00:03:14.640 | Outtakes.

00:03:16.960 | In high school, he had no friends, but thanks to the pod, undergrads are in his DMs, all

00:03:21.920 | forms of stake, he's a purge, and he's the vanguard of all the virgins, the queen of

00:03:26.240 | quinoa, the Sultan of Science.

00:03:28.000 | David Friedberg.

00:03:29.200 | Just for the record, there's no undergrads in my DMs, but I appreciate the intro.

00:03:34.160 | All right, we'll check.

00:03:35.200 | All right.

00:03:35.760 | In three, two, he's trying.

00:03:37.920 | Warfrey Berg is tweaked and the show hasn't started.

00:03:41.200 | I think I'm taking over intros next week.

00:03:43.040 | Okay, do it.

00:03:43.440 | I'm at least gonna do J Cal.

00:03:44.640 | Yeah.

00:03:44.960 | Please, by all means, next week you do mine.

00:03:47.040 | You're a comedian who has a chance to prepare in advance and think your thoughts.

00:03:50.240 | Go ahead, big boy.

00:03:51.200 | Give me a week.

00:03:52.000 | You got it.

00:03:52.560 | Okay.

00:03:52.800 | Cheers next week.

00:03:53.680 | Let's see these latent stand-up skills in action.

00:03:56.240 | Yeah, absolutely.

00:03:57.200 | He's been hiding that.

00:03:57.920 | He's taking them from us.

00:03:58.480 | Yeah.

00:03:59.360 | I don't know a lot of stand-ups who hide their ability.

00:04:01.680 | You know the funny thing about hiding something and not having something?

00:04:04.560 | From the outside in, they look the same.

00:04:06.000 | You can't tell the difference.

00:04:10.080 | Sorry, J Cal.

00:04:10.720 | I'll go over to you.

00:04:11.280 | Okay.

00:04:11.920 | He's dropping annual letters in luxurious sweaters.

00:04:15.440 | As far as the SPACs go, well, it can only get better.

00:04:18.160 | The dictator himself, Chamath Palihapitiya.

00:04:20.800 | Ouch.

00:04:22.000 | I cannot comment on the SPACs.

00:04:23.920 | Oh my God.

00:04:25.440 | I mean, this is getting brutal.

00:04:27.840 | Who's writing these?

00:04:29.040 | Oh my Lord.

00:04:30.240 | All right, everybody.

00:04:30.800 | It's been a big week.

00:04:31.680 | Did you read my annual letter, any of you three assholes?

00:04:36.000 | I saw your commentary.

00:04:37.920 | That's a no.

00:04:38.560 | I get it.

00:04:38.960 | I get it.

00:04:39.440 | I reviewed the table where you listed all your results, and I actually sent it to my team.

00:04:43.600 | I was like, this is a really nice way of summarizing a firm's results over a long period

00:04:49.040 | of time because you had every fund and your totals and all the key metrics.

00:04:55.840 | Well, can I talk about that for a second?

00:04:57.280 | Yes, please.

00:04:57.760 | What's incredible about what you're saying, Sachs, is I was interested in a bunch of other

00:05:02.720 | funds that I'm invested in and their returns.

00:05:04.720 | Then I've also seen a bunch of leaked fundraising decks of all kinds of other firms from growth

00:05:10.480 | stage to crossover to PE.

00:05:12.000 | It's incredible that they are not standardized.

00:05:15.520 | Some people only show gross IRR.

00:05:18.560 | Some people show net IRR.

00:05:21.040 | Some people don't show the total value of the paid-in capital, which means if you have

00:05:26.080 | a $100 fund, what is the total value?

00:05:27.680 | What is the total value of all of its holdings?

00:05:29.360 | Some people don't show DPI, which is distributions of paid-in capital, which means, okay, for

00:05:34.560 | every dollar you've taken in, how many dollars have you sent up?

00:05:37.040 | If you don't show all of them, what was shocking to me is how much you can kind of hide and

00:05:43.440 | play and manipulate the numbers.

00:05:45.600 | One of the most crazy things that I saw is that there are these late-stage funds that

00:05:50.960 | write into their fundraising decks that what they actually use are lines of credit to juice

00:05:56.880 | IRR.

00:05:58.160 | So what they do is if they're about to do a deal, they'll actually get a loan from a

00:06:02.720 | bank, put that money into a company, wait until it's about to get marked up, and then

00:06:09.440 | what they do is they actually call that original money from their LPs and pay back their capital

00:06:13.600 | call line of credit.

00:06:14.400 | What does it do?

00:06:15.040 | It inflates IRR.

00:06:16.480 | But this is why if you see the other numbers, it still shows that it's kind of like not

00:06:22.560 | doing much of anything.

00:06:23.440 | If you ever see multi-hundred percent IRRs or high

00:06:27.520 | huge IRRs with zero DPI and a marginal TVPI, it's folks that are playing games to trick

00:06:36.000 | LPs.

00:06:36.720 | Just a heads up to everybody.

00:06:37.600 | That is so weird.

00:06:38.480 | So what you're saying is, just to summarize for people in the audience who don't understand,

00:06:41.680 | hey, we get judged on the rate of return each year.

00:06:44.480 | So if the stock market does 7% or 8%, we're expected to do triple that.

00:06:47.760 | So we've got to hit 20%, 25% each year.

00:06:50.640 | Now, the clock starts ticking when the money gets called from the LPs, the partners, and

00:06:55.760 | gets put into the company.

00:06:56.880 | Correct.

00:06:57.440 | So if you invest in year two of your fund, you pull the money down from the LPs, you

00:07:01.440 | put it into YouTube, whatever it is.

00:07:03.760 | What you're saying is they will take a loan against that future money from a bank at an

00:07:07.920 | absurdly low interest rate, let's say 1% or 2%.

00:07:10.240 | Correct.

00:07:11.280 | They make the YouTube investment.

00:07:12.960 | Then two years later, YouTube has a price round that marks it up 20x.

00:07:16.640 | Then they put your cash in in year three of the fund, year two.

00:07:20.880 | And pay back the loan.

00:07:21.600 | And pay back the loan.

00:07:22.560 | Now they've paid 2% two years in a row, but the thing's gone up 20x.

00:07:27.120 | Correct.

00:07:27.360 | That's dirty.

00:07:30.560 | Well, so it's dirty enough that the SEC has actually now introduced legislation.

00:07:35.360 | It was in February that basically is going to try to uncover all of this nonsense.

00:07:40.080 | You'll have to be much more transparent.

00:07:42.400 | The format that I used, in my opinion, is the most transparent way of not being able

00:07:46.880 | to hide the cheese.

00:07:48.160 | You show all the critical elements together in a simple table that will make it very obvious

00:07:53.840 | who's playing games and who can actually make money.

00:07:55.760 | There is a...

00:07:57.280 | There's a semi-legitimate version of the loan thing, which is where this comes from

00:08:03.200 | is a capital call loan.

00:08:04.720 | So we're making a bunch of investments throughout the quarter.

00:08:07.040 | A million dollars here for a seed deal, 10 million for a series A.

00:08:10.320 | It's happening all the time.

00:08:11.840 | You don't necessarily want to hit your LPs with capital calls for every single little

00:08:15.280 | small investment.

00:08:16.320 | So what we do is you get a capital call line from SVB or something like that.

00:08:21.440 | And then you do one capital call per quarter.

00:08:25.120 | Right.

00:08:26.160 | So they will loan you the money.

00:08:27.200 | And then you do a capital call for the next quarter.

00:08:28.880 | And then you do a capital call for the next quarter.

00:08:29.920 | And then you do a capital call for the next quarter.

00:08:30.880 | And then you do a capital call for the next quarter.

00:08:31.840 | And then you do a capital call for the next quarter.

00:08:32.880 | And then you do a capital call for the next quarter.

00:08:33.920 | And then you do a capital call for the next quarter.

00:08:34.880 | And then you do a capital call for the next quarter.

00:08:36.080 | And then you do a capital call for the next quarter.

00:08:37.040 | And then you do a capital call for the next quarter.

00:08:38.160 | And then you do a capital call for the next quarter.

00:08:39.120 | And then you do a capital call for the next quarter.

00:08:40.160 | And then you do a capital call for the next quarter.

00:08:41.120 | And then you do a capital call for the next quarter.

00:08:42.160 | And then you do a capital call for the next quarter.

00:08:43.120 | And then you do a capital call for the next quarter.

00:08:44.160 | And then you do a capital call for the next quarter.

00:08:45.120 | And then you do a capital call for the next quarter.

00:08:46.160 | And then you do a capital call for the next quarter.

00:08:47.120 | And then you do a capital call for the next quarter.

00:08:48.160 | And then you do a capital call for the next quarter.

00:08:49.200 | And then you do a capital call for the next quarter.

00:08:50.160 | And then you do a capital call for the next quarter.

00:08:51.200 | And then you do a capital call for the next quarter.

00:08:52.240 | And then you do a capital call for the next quarter.

00:08:53.200 | And then you do a capital call for the next quarter.

00:08:54.240 | And then you do a capital call for the next quarter.

00:08:55.280 | And then you do a capital call for the next quarter.

00:08:56.240 | And then you do a capital call for the next quarter.

00:08:57.280 | And then you do a capital call for the next quarter.

00:08:58.320 | And then you do a capital call for the next quarter.

00:08:59.360 | And then you do a capital call for the next quarter.

00:09:00.320 | And then you do a capital call for the next quarter.

00:09:01.360 | And then you do a capital call for the next quarter.

00:09:02.320 | And then you do a capital call for the next quarter.

00:09:03.360 | And then you do a capital call for the next quarter.

00:09:04.400 | And then you do a capital call for the next quarter.

00:09:05.440 | And then you do a capital call for the next quarter.

00:09:06.480 | And then you do a capital call for the next quarter.

00:09:07.520 | And then you do a capital call for the next quarter.

00:09:08.560 | And then you do a capital call for the next quarter.

00:09:09.600 | And then you do a capital call for the next quarter.

00:09:10.480 | And then you do a capital call for the next quarter.

00:09:11.520 | And then you do a capital call for the next quarter.

00:09:12.480 | And then you do a capital call for the next quarter.

00:09:13.520 | And then you do a capital call for the next quarter.

00:09:14.560 | And then you do a capital call for the next quarter.

00:09:15.520 | And then you do a capital call for the next quarter.

00:09:16.560 | And then you do a capital call for the next quarter.

00:09:17.520 | And then you do a capital call for the next quarter.

00:09:18.560 | And then you do a capital call for the next quarter.

00:09:19.600 | And then you do a capital call for the next quarter.

00:09:20.640 | And then you do a capital call for the next quarter.

00:09:21.680 | And then you do a capital call for the next quarter.

00:09:22.800 | And then you do a capital call for the next quarter.

00:09:23.920 | And then you do a capital call for the next quarter.

00:09:25.040 | And then you do a capital call for the next quarter.

00:09:26.000 | And then you do a capital call for the next quarter.

00:09:27.040 | And then you do a capital call for the next quarter.

00:09:28.000 | And then you do a capital call for the next quarter.

00:09:29.040 | do we all look at when we are LPs in a fund? Well, this is what I put down. I put down the

00:09:35.760 | ones that I look at for everybody else that I'm an LP in. What one is that for you? Multiple

00:09:41.640 | cash investment? I need to look at the totality of it. I need to understand what is your gross

00:09:47.280 | and your net IRRs. Those are important things to understand because it shows how efficiently

00:09:51.840 | you put the money to work. Of course. But then ultimately the other two things that

00:09:56.300 | really matter is what is the total value you've created and then what percentage of that have

00:10:00.980 | you given back to me? Because that allows you to understand how much paper value there

00:10:07.740 | is. For example, today, let's just say you had a fund that had a TVPI, total value of

00:10:12.920 | paid in capital of a 5X. A 5X on a fund is incredible. But if you've distributed none

00:10:19.080 | of that, well, guess what? If we're sitting here in May of 2023 or 2022 rather, the total

00:10:25.740 | value of your paid in capital is not really 5X. It may be only 3X and it may be actually

00:10:30.080 | 2.5X considering what the markets have done to these companies. It allows me to really

00:10:37.100 | understand how performant funds are in not just being a part of the game but actually

00:10:44.820 | generating realizations. This is the hardest part. As I told you, Jason, this past quarter,

00:10:50.580 | I think I passed 2X across my funds when I was managing outside capital.

00:10:55.180 | I think, my gosh, it took me 11 years to return 2X the money. That means I've returned $2.5

00:11:02.860 | billion. You know how hard that was?

00:11:05.680 | Yeah. I mean, you got to time the exit. You have to have the ability to exit.

00:11:09.440 | You can't even time the exit. You have to be constantly managing and working your portfolio.

00:11:14.560 | Sometimes you're selling in secondary transactions. Sometimes you're actually trading up in private

00:11:19.220 | markets where you help this company merge with another private company. Other times,

00:11:23.720 | if I think about it, the number of times I've been able to get a loan, I've been able to

00:11:24.620 | get a loan. I've been able to get a loan. I've been able to get a loan. I've been able to get a loan.

00:11:25.120 | The number of IPOs I've had is relatively diminutive. How do you make $2 billion where

00:11:28.480 | I've only had one IPO, which has been Slack? Yeah.

00:11:31.600 | This is a really, really hard business. It was just a reminder that in the last four or five

00:11:37.840 | years, managing capital has seemed relatively easy. But in these next few years, you're going

00:11:43.120 | to see who's really, really good. It's kind of that old Warren Buffett quote. You can see who's

00:11:48.240 | naked when the tide goes up. Said another way, the last five years, raising a fund has been really

00:11:53.000 | easy. Jason:

00:11:54.060 | And writing checks has been really easy. And now comes Act Three, which is returning a multiple on

00:11:59.900 | the money you easily collected. And boy, is that hard. All of these new LPs-

00:12:05.500 | The other thing that I learned-

00:12:06.380 | Let me just tell you this one thing, though. All these LPs send me, even if I'm not an LP,

00:12:10.300 | they send potential LPs their performance because they're so proud of it, like quarterly. I'm like,

00:12:15.340 | "I'm not even in this fund." And they have these crazy markups, crypto investments, this, whatever,

00:12:19.260 | but they've returned no capital. And so it's like-

00:12:23.500 | Just to give you a sense of it, if you look at the most fantastic organization in the world,

00:12:28.620 | if it were an investment manager, which is Berkshire, their long run 50-year track record

00:12:33.740 | is around 20%. Gross. If you look at the most successful asset manager in the world,

00:12:40.780 | and I would put Blackstone at that, just incredibly good and best in class in probably three

00:12:46.540 | enormous parts of the worldwide economy, real estate, credit, and private equity,

00:12:52.540 | their long run track record is that on 200 and some odd billion dollars of private equity,

00:12:57.660 | and another 100 billion dollars of real estate, they've returned 2x. That's what the upper bound

00:13:05.980 | is. Doubling people's money and generating 15% to 20% is the best you can expect if you are really

00:13:13.020 | excellent and long-lived. That's the best. What do you look at, Freeberg, when you're

00:13:17.500 | an LP? What number do you care about? Because you LP other funds, and I think all of us do.

00:13:21.980 | I made my first venture fund investment in 2006. I am still getting distributions from that fund.

00:13:35.100 | I'm looking at it, and I'm like, "This is a 2.4x over that period of time." I'm like,

00:13:40.460 | "What the hell? Why did I even put this money into this fund?" I guess this makes sense for pension

00:13:45.580 | funds and very large balance sheet, long-range investors that need to diversify.

00:13:51.420 | But as an individual, I should have put my money and had liquidity on it for 16 years rather than

00:13:57.980 | have it locked up in a bunch of private companies sloshing around and dribble out. At the end of all

00:14:03.340 | this, I only get 2.5x my money back. Two and a half times your money in 16

00:14:07.420 | years. What's that IRR? It's like low teens. Yeah, not a great deal.

00:14:10.940 | No, no. It's lower. You would have been better owning the S&P 500.

00:14:14.780 | That's right. For me, I think the only metric that matters, which I think you're saying, Chamath,

00:14:21.580 | is how much cash I got out relative to cash I put in. Initially, my IRR is negative 97%.

00:14:29.020 | Then it goes up to negative 80%, and then negative 60%, and negative 30%, and negative 20%.

00:14:34.540 | Now it's 14% because I finally got more money out than I put in. It doesn't feel to me like

00:14:41.340 | just generally private investing, everyone gets excited because we all get sold stories,

00:14:46.780 | and individuals all get sold stories of, "You put $1 in, you get $100 in." J. Cal. wrote a book,

00:14:50.620 | called How I Made $100 Million from Whatever You Invested in Uber.

00:14:55.500 | Yeah.

00:14:56.060 | That story, I think, gets everyone excited. But the reality is, the vast majority of the time,

00:15:02.220 | and if you diversify your bets like this, you're going to end up waiting a long time to get your

00:15:07.180 | money back. You're going to be locked up. A top performing fund is returning 2.5x after 15 years,

00:15:14.140 | which is not much better than investing in the S&P where you could sell that anytime you want,

00:15:18.780 | and use that cash for any purpose you want. Yeah.

00:15:21.020 | Well, if you did a $100,000 investment, and you returned $260,000 in 15 years,

00:15:26.940 | I'm on an IRR calculator right now, internal rate of return is 6.58%.

00:15:31.020 | Yeah. Better off than the S&P.

00:15:33.100 | Yeah. And if you did QQQQ, depending on how hot the market was then, yeah.

00:15:39.580 | It's really, really, really hard to actually make money. There are always going to be periods

00:15:45.820 | where people look like geniuses and have markups, but you can really see when people have

00:15:50.460 | skill after a decade and a couple of up and down cycles.

00:15:53.580 | Same with hedge funds, by the way, right? Hedge funds put up a score every year,

00:15:56.380 | and in certain macro cycles that can last many, many years,

00:16:02.300 | everyone looks like they're doing well. And then all of a sudden, tides go out, and you lose more

00:16:09.340 | than you made over that period of time. And then you realize, "Holy crap, I was actually in an

00:16:14.060 | insurance business," where you get paid some small premium every year, and then you have some massive

00:16:18.860 | loss one year, and that massive loss is going to be a huge loss. And then you're going to have some

00:16:20.380 | massive loss. It turns out your underwriting wasn't good because you lose more than the

00:16:24.540 | sum of all of the premium you collected over that period of time. And unfortunately,

00:16:28.460 | a lot of investing looks like this, which is you have small returns for a long period of time,

00:16:33.820 | and then some massive loss, and the whole business makes you look like,

00:16:37.820 | along the way, a genius. But the reality is over any long cycle, most folks end up in a bad position

00:16:44.860 | and they end up losing the market. The SEC, by the way, has solved this for mutual,

00:16:50.300 | and ETFs. There's very strict standard reporting. And I do think that as, for example, if you go to

00:16:59.740 | the big banks, sorry, Sax, to interrupt. I just want to finish the last thought. If you go to the

00:17:02.700 | big banks, and you have, if you're an individual, like a doctor or a dentist or somebody, and

00:17:07.500 | they will aggregate and pool capital and put it into these funds on your behalf, as an example.

00:17:12.860 | It looks like JP Morgan or Goldman Sachs is a $50 or $100 million LP in one of these big funds, but in

00:17:20.220 | fact, it's just the sum of a bunch of folks on their platform. It stands to reason that if the

00:17:25.660 | SEC can actually mandate standardized reporting for private investing, it would actually be a

00:17:29.740 | really good thing because all of these games will, and probably currently are, as far as I've seen in

00:17:36.060 | these presentations, tricking a lot of folks to put their hard-earned money into things that

00:17:40.860 | actually will never make money. And it's because if you selectively cherry pick how you present

00:17:44.700 | this data, you can tell a partial truth. So, you know, I would really, I would

00:17:50.140 | love, I'm happy to be compared to any organization, but every time I hear somebody

00:17:53.980 | chirping about how good they are, my only comment is, I just want to see your table in the same

00:17:58.620 | format as my table, and we can compare it because it allows me to really understand.

00:18:02.140 | Yeah, liquid returns. And by the way, the point I made earlier about

00:18:05.340 | when markets are generally good, hedge fund, public market investors generally can look

00:18:11.180 | like they're doing well by having a good marginal return above the benchmark every year, and then

00:18:16.540 | one year have a big drawdown, and suddenly they realize that they're underwriting what

00:18:20.060 | wasn't that good. The same can be true in private investing in the opposite way, in the sense that

00:18:25.660 | you'll put in small checks, small checks, and lose money and lose money and lose money and then have

00:18:30.220 | one big banger, and you get 100x return, and you look like a genius, because your whole portfolio

00:18:34.860 | looks good. But you fast forward and you keep doing that for another 10 years, all those small

00:18:38.380 | checks may not even add up to the banger. And that's, that's the flip reality that you realize.

00:18:43.900 | And by the way, I think that's a good analogy for the difference between public and private

00:18:46.780 | investing. You have similar cash flow economics, where you can have small

00:18:49.980 | returns and then a big loss in public. And you can have small losses and then a big return in

00:18:54.300 | private. And the timing of when you present your data can make anyone look good if you catch a good

00:18:59.340 | hit at the right time, or you don't have a bad hit at the wrong time. And then the framing over

00:19:04.540 | a long enough period of time, I think really becomes the key measure. And the reality is most

00:19:08.940 | people don't make it long enough in their career to actually to actually present true results in

00:19:13.820 | how they really do underwrite.

00:19:14.860 | And by the way, to the extent anybody's listening is able to invest in these private funds,

00:19:19.260 | I think Jason mentioned this superficially. So let me just dig into it, because I think it's

00:19:23.580 | really, really thoughtful what he said, which you should understand. If you have the option

00:19:29.580 | to invest in a private fund, you have to understand that that private fund has two huge

00:19:34.940 | negative things working against it relative to investing in the S&P 500. So you could put your

00:19:40.700 | money into a Vanguard ETF. Or if you could put your money into a private fund, you need to realize

00:19:45.740 | two things. Number one is it is illiquid.

00:19:49.180 | And not just for 10 years, but it could be illiquid for 12 or 14 or in, you know,

00:19:53.260 | Friedberg's case, 16 years. So you need to get paid a premium for owning that. And then the

00:20:00.060 | second is depending on the business model, you may have very high failure rates, which means that you

00:20:05.580 | need to really hit these outsize Grand Slam home runs. And if you don't, then you're going to be

00:20:12.060 | worse off than if you invested in the S&P 500. So that deserves a premium. And so Jason's right,

00:20:17.740 | which is the S&P 500 is a premium. And so Jason's right, which is the S&P 500 is a premium.

00:20:19.100 | And so Jason's right, which is the S&P 500 is a premium. And so Jason's right, which is the S&P 500 is a

00:20:19.500 | premium. And so Jason's right, which is the S&P 500 is a premium. And so Jason's right, which is

00:20:19.500 | between 7% and 8% over long periods of time, predictable compounding. You have to add another

00:20:26.700 | 7% to 8% for this illiquidity premium, and another 7% to 8% for the business model viability of, for

00:20:34.460 | example, being in venture. When you add those three things together, you do need to get paid

00:20:39.660 | basically in the low to mid 20s returns to be justified. Otherwise, you are much better off

00:20:46.620 | just owning the S&P 500. Much, much better. Jason:

00:20:49.020 | Much, much better off. Sachs, what do you look for when you're LPN? And now that you have many

00:20:54.620 | large funds? What do you think LPs are looking for now? And what do you advise them to stay focused

00:21:00.220 | on? Sachs:

00:21:00.940 | The number one metric that matters is DPI, which is the ratio of distributions to paid in capital.

00:21:06.140 | And it's basically money in versus money out, right? At the end of the day, that's all that

00:21:09.660 | matters is how much money did you put in the fund? How much money did you get out?

00:21:13.740 | The issue is that such a possible point, these are 10 to 12 year funds, and it takes a long time

00:21:18.940 | to get distributions. So all the other metrics are basically triangulations or approximations

00:21:24.300 | of what you think the fund's going to do until you actually get to distributions. So I would say

00:21:28.700 | in the long term, it's all DPI. In the short term, you look at TVPI, the total value to paid in

00:21:33.660 | capital. So it's basically what's the marked up value of all the positions in the portfolio versus

00:21:39.900 | how much cash has gone in. And then the big question is, does the TVPI turn into DPI?

00:21:47.500 | DPI.

00:21:47.980 | Does the total value-

00:21:48.860 | To explain that to people, if Chamath had invested in Slack, but there hadn't been an outcome,

00:21:55.180 | it could be on the books for a billion dollar position. So the TVPI is looking really great.

00:22:00.460 | But until that company goes public, and the shares are distributed, the LPs haven't realized it. So

00:22:08.220 | it could be ephemeral, or it could go down significantly as we've seen with public markets.

00:22:12.940 | Yeah. So in the last four months, we just returned our fund one. In terms

00:22:18.780 | of real distributions, I think we have a DPI of 1.1 or 1.2 on that fund now. The TVPI is 4 to 5.

00:22:26.140 | But it feels great just to distribute the entire fund out to LPs.

00:22:30.300 | Literally, in my first two funds, I think we did that as well. And it's a really great feeling.

00:22:35.020 | Sometimes selling 10% or 20% of a position early and getting over that hurdle and just getting into

00:22:43.580 | the 1 to 2x, that's a pretty great feeling. By the way, just to talk about how difficult it is to

00:22:48.620 | convert paper gains into real gains, let's just say, Jason, in your example, you had a fund that

00:22:54.300 | had these huge paper gains but haven't distributed anything as coming into this year. Here's a little

00:23:00.300 | interesting data about the ultimate buyer of all of these tech stocks, which is the NASDAQ.

00:23:05.180 | People that buy stocks in the NASDAQ, listen to this as of yesterday.

00:23:09.820 | More than 45% of stocks on the NASDAQ are now down 50%. So basically, one in two.

00:23:19.340 | More than 22% of stocks on the NASDAQ are down 75%. So almost one in four and more than one in

00:23:27.820 | five. And then more than 5% of stocks, so one in 20, on the NASDAQ are down 90%.

00:23:35.020 | So you can use this to actually get a blended average.

00:23:39.980 | But what it means is that the ultimate buyers of tech stocks are taking a 60% discount to what

00:23:48.300 | they were able to buy even just four months ago. 60%. So there is no public mark that will support

00:23:58.620 | a private mark unless it's also discounted by at least 60%. Now think about that when you talk

00:24:05.980 | about this entire panoply of companies that have been overfunded, many who are under-executing and

00:24:12.860 | burning enormous amounts of money, who now have to come back out to the market. As any sufficient

00:24:18.140 | sophisticated buyer will have to tell them the truth, which is, "I'm sorry, guys, but the data

00:24:22.140 | says there's a 60% discount to this mark. Are you willing to accept it or not? Otherwise, the lights

00:24:26.780 | are going to go off." Yeah.

00:24:28.060 | And these marks only happen, at least in the private markets and venture funds,

00:24:33.420 | when a transaction occurs. So if somebody raised a bunch of money,

00:24:36.220 | as we talked about in previous episodes, at a billion dollars,

00:24:38.460 | and they're now worth $500 million, that's only going to work itself out in fund documents and

00:24:46.860 | reports for a year. Yeah.

00:24:47.980 | A year or two later when the next transaction occurs. So there is a lagging effect.

00:24:52.940 | One thing I just want to bring up before we go into maybe GDP or the Bill Hwang situation

00:25:01.100 | is what we talked about on this pod last year about what was going to happen in private markets.

00:25:07.100 | I've been seeing the last two or three weeks, and I don't know, Sax and Freiburg, what you're seeing

00:25:11.900 | in private markets. But really acutely, people who are going out and skipping rounds, this

00:25:17.820 | is the first time I've seen a lot of people who are going to be in private markets. And I think

00:25:20.860 | that's a big part of the reason why I'm so excited about this. I'm going to get credit

00:25:24.220 | for work that hasn't been done. I'm going to raise $10 million without product market fit.

00:25:28.540 | Oh my lord, has the dialogue changed? I've been on many calls with founders who've met with 50 VCs,

00:25:36.060 | and the conversations are moving to, "How many months to break even? And how many customers do

00:25:44.140 | you have? And how have they increased? And let's talk about the churn." It is getting

00:25:47.660 | super pragmatic out there. If you're a founder, and we said this a year ago, but it's worth stating

00:25:52.220 | here, this is not the moment I would try to over optimize. If you have a term sheet or money on the

00:25:57.420 | table, I would close it, just founder to founder. What are you seeing, Sax?

00:26:02.220 | Yeah, I mean, it's gotten a lot harder, I think, especially at the growth rounds. We actually

00:26:06.540 | have signed two growth term sheets recently. And it was much harder for us to do growth

00:26:13.500 | rounds last year, just because you had these huge mega funds come in at crazy

00:26:17.500 | valuations. But now, they're kind of licking their wounds, and we're starting to see some really

00:26:21.340 | attractive growth opportunities. Everyone else is backed off. So it's interesting.

00:26:25.660 | Yeah, it's changed quickly.

00:26:27.900 | Yeah. Now, one thing to, you know, to Roth raised a good point about,

00:26:31.100 | you know, private, not only are private valuations sort of sticky, but private marks are sticky. And,

00:26:37.740 | you know, companies only get remarked every couple of years. And so whereas the public markets get

00:26:41.100 | remarked every day. So it is hard to know, like, what is the proper valuation of a company that

00:26:47.340 | raised money last year? Because yes, valuation multiples have come way down, but then also,

00:26:53.180 | they may have grown, and their performance is better. So the analysis that I saw Jason Lemkin

00:26:58.220 | do in his LP newsletter, and we're basically repeating it for our entire portfolio is to

00:27:03.740 | calculate what was the ARR multiple that you pay, basically valuation divided by ARR, what was that

00:27:10.780 | entry multiple? And what is it today? And so we're doing that across our whole portfolio.

00:27:15.660 | So what you see is,

00:27:17.180 | sorry, sorry, Sachs, clear, LTM ARR, or, you know, NTM ARR, which one?

00:27:23.260 | Basically, you lost 12 months next 12 months?

00:27:25.340 | Yeah, no, you just look at their current ARR, which is, you know, run rate, their current

00:27:30.140 | run rate revenue. Yeah, exactly.

00:27:31.820 | January, you times it by 12.

00:27:33.660 | Or in this case, April, April,

00:27:36.620 | basically, yes, you take the current month and multiply by 12. But they have to be annual

00:27:40.220 | commitments, right? So if it's not, it has to be annually recurring revenue, if they're not in,

00:27:44.780 | if it's not an annual commitment with an expectation,

00:27:47.020 | that's recurring, you can't count it. So for example, you don't count professional services

00:27:51.100 | revenue in that, in any event. So the point is, you, you basically calculate what was the multiple

00:27:58.700 | that you paid at, you know, entry in the company? And what is it today, as a function of the current

00:28:04.460 | valuation? And what we see is, yeah, there's a lot of companies that we got into, I don't know, two

00:28:09.660 | years ago at evaluation multiple that you couldn't defend today, 60 times 80 times 100 times. But the

00:28:16.860 | multiple today is more like 10 or 20 times, because it's actually grown really fast. So you

00:28:21.740 | need to look at both sides of the equation. And that's the analysis we're running for every

00:28:25.500 | company in our portfolio. And then you know, LPS can decide how to how to market.

00:28:29.340 | I mean, the most important thing is what's the next investor if they need more capital

00:28:34.620 | going to market at?

00:28:35.500 | Well, the question is, are you growing faster than valuation multiples are falling?

00:28:39.180 | Correct. And then can you that means you could have a down round a neutral round or possibly

00:28:44.940 | an up round, but it doesn't. So are you growing faster than valuation multiples are falling?

00:28:46.700 | So are you starting to see people or people discussing on the board level,

00:28:50.540 | or in your firm? Hey, maybe we take a sideways round, a neutral round, we just go to last year's

00:28:56.620 | price and top off another 10 million? Are you seeing that I've still told some of the boards

00:29:00.940 | I'm on just keep fundraising, just keep the round open and top off if there's money available,

00:29:04.780 | because you know, especially if you raised around eight months ago, six months ago,

00:29:10.140 | those prices, like if people are still willing to invest in those terms, that's a good deal.

00:29:14.460 | I literally had this conversation with the founder,

00:29:16.540 | founder this week where they had raised that in a great valuation. And they turned money away.

00:29:21.420 | Because they were like, Yeah, that was a mistake.

00:29:24.060 | We're still growing. So why would we take the money now if our valuation is going to be,

00:29:28.540 | you know, double in nine months? And now it looks like Yeah, maybe you know, that extra

00:29:34.140 | one to $5 million would have been good to lock up. Okay. So adding to these headwinds, I think we

00:29:38.700 | we've been talking about the possibility of a recession for those new to the to the concept,

00:29:46.380 | the concept of recession if you're under the age of 30, and haven't really lived through one as an

00:29:50.140 | adult. It's two quarters, the official definition, two quarters of negative growth of the GDP. Well,

00:29:56.700 | it turns out, US GDP fell 1.4% in q1. And q4, we had a 6.9% growth rate. q1 was the weakest since

00:30:06.220 | the spring of 2020. When COVID hit Nick, cue the clipboard Saxon, I basically said this may happen

00:30:12.780 | in January of this year.

00:30:16.220 | So I think the question is, you know, with the losses we're seeing, and I mean, every day,

00:30:20.460 | it just keeps like you've seen more red, that this could turn into a recession, you know,

00:30:24.220 | popping of bubbles is usually followed by, by recessions are, so I think, you know,

00:30:30.300 | the fortunes of the economy could turn really quickly here. And

00:30:34.380 | that is that is the marginal risk, the marginal risk is actually for recession, David is saying

00:30:38.460 | something really important. The risk, in my opinion, is not of runaway inflation anymore. The

00:30:45.580 | Fed is now a big part of the recession.

00:30:46.060 | David Chou: And the Fed is now in this really delicate situation where China cut rates last

00:30:49.100 | week, we have an FOMC meeting, the Open Markets Committee that sets rates on Wednesday, I think,

00:30:53.820 | of this coming week. What is he supposed to do? The risk is to a recession, because if we

00:30:58.620 | overcorrect, yes, and the leading indicators all around the world tell us that their economies are

00:31:03.900 | weak, then inflation may have actually been much more transitory than we thought. And right now,

00:31:09.420 | we have to decide. Because if we overcorrect, we're going to plunge the United States economy

00:31:14.620 | into a recession. David Chou:

00:31:15.900 | Yeah, I think that's a good point. And I think that's a good point. And I think that's a good point.

00:31:16.140 | David Chou: There's a lot of data here. And obviously,

00:31:18.460 | this is when this data is always in the review mirror. So obviously, we're talking about Q1,

00:31:24.620 | it takes a while to collect this data. And there's a lot of different factors going on at the same

00:31:29.340 | time, obviously, COVID and obviously supply chains, consumer spending rose at a 2.7% annual

00:31:35.500 | rate in Q1, a slight acceleration from Q4, there was also a 9.2% rise in business spending.

00:31:41.020 | So we have a lot of spending going on, who knows if that is spending that actually occurred,

00:31:45.740 | and the previous quarters and because of supply chains, like people's cars are being delivered,

00:31:50.140 | people's machines and manufacturing equipment is being delivered now.

00:31:53.820 | David Chou: We had negative GDP in Q1, for a whole host of

00:31:57.580 | reasons that can effectively be summarized by the fact that we are still trying to restart an economy

00:32:04.860 | at the tail end of a pandemic, and we're doing it in fits and starts. And so we have these small

00:32:08.860 | bursts of incredible GDP, which we had last year, and then contractions in the economy. The thing

00:32:15.580 | that's always been true about the United States is that we are a consumer driven economic engine,

00:32:22.220 | which means that as long as people feel confident, and they're buying things, the economy tends to do

00:32:27.900 | well, and we tend to move forward as a society. When consumer confidence ebbs, and people contract

00:32:34.460 | their spending, we are in a world of hurt. The last couple of years, we've had a lot of

00:32:40.540 | consumer savings, right? We've had a lot of money that's been pent up in the system, whether it's

00:32:45.420 | a loan forgiveness or all of this stuff has allowed people to feel much richer.

00:32:52.220 | As a result, they've started to spend in dribs and drabs. The problem now is that because prices

00:32:58.300 | are so high, all of those savings have largely been depleted. I just sent you guys a text in

00:33:04.700 | the group chat of what consumer spending looks like, and consumer savings rather.

00:33:09.580 | It tells a really, really scary story, which is that the savings boom is largely

00:33:15.260 | over. Personal savings rate fell to 6.2% in March, the lowest since 2013. What does that mean? Well,

00:33:22.220 | it means that the setup is there for us to really contract what we are able to spend as a society.

00:33:28.940 | I think now the odds even push further in this direction that we could have more quarters of

00:33:36.780 | negative GDP. All of a sudden, we're back to what we talked about before, which is a 2019-like

00:33:42.140 | scenario, where the government is going to be able to get rid of the debt, and the government is going

00:33:45.100 | to be able to get rid of the debt. The Fed, specifically, races forward to tackle inflation.

00:33:49.340 | In 2018 and 2019, it turned out to be a head fake. By the way, in 2019, the stock market ended up

00:33:56.700 | more than 30%, up 32% or something like that. Crazy numbers. By the way, back then in 2019,

00:34:03.100 | China turned over. It looked like it was going to be a fast-moving economic recovery for China,

00:34:09.900 | and instead, they sort of slowed down. We have the same thing here. We have a quarter of negative

00:34:14.940 | GDP. We have China in lockdowns. We have every company that's in the manufacturing supply chain

00:34:20.460 | ecosystem telling the world that we don't really know what this is going to look like. Intel today

00:34:25.020 | actually said there's going to be shortages in chips through 2024. I think it could be a very

00:34:34.220 | difficult path ahead for the Fed. How do you raise rates 400 basis points into a slowing economy?

00:34:42.460 | How do you raise rates 400 basis points into a slowing economy? You could raise basis points 75,

00:34:44.780 | you know, 75 bps, maybe 100 bps, but it gives them very little freedom to operate without

00:34:51.420 | really tanking the economy. There's also another point to highlight here, which is

00:34:55.260 | in some of this data that was released, there was a strong indication that there are real

00:35:02.060 | issues right now with inventories. I don't know if you guys have tried to

00:35:06.940 | buy an appliance or a car lately, or a piece of furniture, but like-

00:35:12.220 | I tried in the Q4 to buy a car.

00:35:14.620 | I mean, right now there's like one year delays to get a frigging couch. I mean,

00:35:19.100 | like everything in the global supply chain, somewhat related to the kind of big inflationary

00:35:25.660 | pressure that hit us at the end of last year, and then everyone placed orders, all the factories

00:35:29.580 | kind of had to produce a lot, they all couldn't keep up, through to what's going on in China right

00:35:34.220 | now where there's lockdowns and factories are shut down. I have several businesses in the hardware

00:35:39.260 | space that are actively searching and frantically trying to find a way to get the right product.

00:35:44.460 | And I think the reason for this is that you know, the market is a very competitive one.

00:35:48.460 | And so I think you know, there's a lot of things that are happening. And I think the market is a

00:35:52.700 | very competitive one. And I think that's one of the reasons why we're seeing this kind of surge,

00:35:56.140 | is that there's a lot of people who are like, you know, this is a very competitive market. And I think

00:36:00.780 | that's a very competitive market. And I think that's a very competitive market. And I think that's

00:36:03.900 | a very competitive market. And I think that's a very competitive market. And I think that's a very

00:36:04.780 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:06.220 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:09.100 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:12.940 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:15.580 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:16.780 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:19.980 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:22.780 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:25.020 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:28.460 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:30.620 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:33.100 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:34.780 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:38.940 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:42.060 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:43.420 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:44.540 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:45.580 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:46.300 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:47.980 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:49.020 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:49.820 | competitive market. And I think that's a very competitive market. And I think that's a very

00:36:50.940 | this adversity right now on the market, it seems an

00:36:53.640 | interestingly, and by the way, that doesn't that doesn't mean

00:36:55.740 | sorry, that doesn't mean that we're not gonna have recession.

00:36:57.980 | Because, you know, when I'm not able to spend money on Apple,

00:37:00.940 | Apple spending less on their suppliers, they're spending less

00:37:03.060 | on their suppliers. So there is a trickling effect of capital

00:37:06.120 | flows and the recessionary effect may be hit. But, you

00:37:09.180 | know, there is capital and there is demand for consumption. It's

00:37:12.540 | just that we're really clogged up right now.

00:37:14.340 | Well, and the consumer confidence index has been on a

00:37:18.520 | bit of a roller coaster, we were at 130 before the pandemic. For

00:37:22.440 | the year of the pandemic, we were down in the high 80s 8788

00:37:25.840 | 89. We rocketed back up. You know, in 2021, people started to

00:37:31.540 | feel like, oh, we've got these vaccines, things are gonna go

00:37:34.280 | back to normal rocket back up to 128. And it's been a slow tick

00:37:38.120 | down to where we're now at 107. And so I think consumers don't

00:37:43.160 | know what to think they don't know if you know, inflation is

00:37:45.760 | transitory, they don't know if gas is going to be

00:37:48.340 | separate.

00:37:48.340 | $7 or $4. They don't know if they should spend a big spend on

00:37:53.560 | a big vacation or not. And so this I think in terms of people's

00:37:58.100 | planning, I don't know if people can plan how their own personal

00:38:02.320 | budgets, right. And I think that's on the confidence thing

00:38:05.100 | to Chamath point, we need to have a predictable economy. You

00:38:10.600 | know, it can't be this schizophrenic, to use the term

00:38:15.280 | sacks, what do you what do you think about what we're seeing

00:38:17.580 | here?

00:38:17.980 | In terms of, we're obviously, either in a recession, or dip, you

00:38:24.580 | know, dancing around it, we're basically, you know, on the edge

00:38:27.640 | of the cliff right now, I think it's probably the most

00:38:29.680 | accurate.

00:38:30.160 | I tweeted in February, hey, anyone noticed that we've just

00:38:32.980 | entered a recession, and I got dunked on by all the

00:38:35.600 | professional economists, and you know, all these people, but the

00:38:38.320 | experts, the experts, the experts, exactly, correct. And

00:38:42.140 | now it's like the data just came out negative 1.5% economic

00:38:45.520 | growth in q1. So what I wrote at the time was exactly right.

00:38:49.720 | And, you know, I don't know how the thread the Fed threads this

00:38:53.500 | needle. I mean, we've got a slowing economy with negative

00:38:56.860 | GDP growth, you've got inflation is still rampant. It's not as I

00:39:02.800 | don't think it's gonna be as high as last year, just because

00:39:04.540 | we're lapping a much bigger number from last year. So on a

00:39:07.000 | year over year basis, the comps are you started a higher price

00:39:10.840 | level, but inflation is still there. So, you know, I don't know

00:39:14.860 | what you do about that.

00:39:15.360 | about that. It's, it's a really tough situation. And when you

00:39:19.600 | have this kind of wealth destruction in the stock market,

00:39:21.960 | I mean, you know, and we, there was a good tweet that you

00:39:26.700 | shared, we should put up on the screen, I mean, so much, like

00:39:29.900 | wealth has been destroyed, you don't necessarily see it if you

00:39:32.120 | just look at the big cap indices, but you look at all the

00:39:35.800 | engines of process, sort of growth and prosperity, the small

00:39:40.440 | caps, the recent IPO's, the growth stocks, they've been

00:39:43.040 | absolutely hammered, it really hasn't been this bad, since the

00:39:46.360 | dotcom crash of 2000. Like, and not just the, like, April period,

00:39:51.440 | but like, all the way in October, where it kept going.

00:39:53.540 | And then the 2008 recession, yeah, the 2008 real estate

00:39:57.920 | crash. So we're already like top three worst situations for growth

00:40:03.140 | stocks in the last 20 years. And when you have that kind of like

00:40:07.700 | wealth destruction, it eventually trickles down into

00:40:09.800 | the economy, because people just feel, you know, companies start

00:40:12.620 | cutting.

00:40:12.960 | budgets, people have less money, that's built to spending

00:40:16.020 | goes down.

00:40:16.620 | That dynamic that that we're referring to in this tweet in

00:40:20.080 | that image is called dispersion, which means, you know, people

00:40:23.120 | baby being be confused when you hear why are all these stocks

00:40:26.680 | down so much, but the the indices are not down as much.

00:40:30.060 | And it's exactly for the reason that David just said, which is

00:40:32.600 | that underneath the surface, the mega cap tax consumes so much of

00:40:39.800 | the market cap of these indices. So, you know, the Google,

00:40:42.920 | the Microsoft, the Apple's and the Tesla's, those four just clog up

00:40:47.600 | an enormous percentage, I think it's approaching 40% of these of

00:40:51.100 | these indices. And so underneath the surface, you have dispersion,

00:40:54.860 | which means you have these tale of two kinds of stocks, you have

00:40:57.660 | these four big mega caps, and then you have everybody else. And

00:41:02.540 | the mega caps are generating so much cash, that they're just

00:41:05.320 | basically keeping the market afloat. So at this point, maybe

00:41:09.440 | there's a small silver lining. And that silver lining is that

00:41:12.900 | to be bearish right now, is effectively not being bearish

00:41:17.100 | these growth stocks, because as we said, they've been just

00:41:19.560 | decimated. At this point to be bearish the indices means very

00:41:23.640 | specifically to be bearish those four names, and only those four

00:41:27.780 | names. And so that may actually mean that the market has

00:41:31.980 | effectively crashed already.

00:41:33.420 | Yeah, but by the way, I'm not necessarily bearish on growth

00:41:36.600 | stocks from here, because like you said, they've already been

00:41:38.880 | beat up so badly. The stock market is usually a leading

00:41:42.020 | indicator.

00:41:42.600 | What I'm a what I'm a bearish about is just the state of the

00:41:45.240 | economy because the stock market is traded down, it trades down

00:41:48.540 | on expectations. So it was already trading down months

00:41:52.020 | ahead of the slowdown in the real economy. So now new in

00:41:56.160 | December, the market new in November, the recession was

00:41:58.800 | coming in, like around November 6 of last year, and they knew it

00:42:01.620 | was coming in. Yeah,

00:42:02.580 | Mark knew when we talked about the sales that Bezos and Musk

00:42:05.580 | did the, you know, when when we sold equities, we were saying

00:42:09.580 | like, it's like, you can't keep all of your money,

00:42:12.440 | you know, on the table all the time, unless you have the

00:42:16.620 | durational wherewithal, meaning you're just not time bounded,

00:42:20.300 | and you can just be there forever. And not everybody's in

00:42:22.640 | that position.

00:42:23.140 | And endowment could be in that position, but individuals with

00:42:26.300 | no an endowment is not because they have to create

00:42:28.240 | distributions every year, right? They have to talk about the mega

00:42:30.740 | endowments where they, you know, for you know, you know, Ford or

00:42:33.920 | Harvard may not need to do this. But yeah, smaller ones might

00:42:36.060 | actually be operating, you know, Memorial Sloan Kettering might

00:42:38.720 | actually be operating their budget from it.

00:42:40.700 | But just to go back to David's point, like, it's a really

00:42:42.740 | difficult spot, like, what is the Fed supposed to do? So

00:42:44.720 | they're probably going to tighten 50 basis points in May,

00:42:46.820 | that's relatively well expected, we'll be, we'll be able to

00:42:50.180 | digest that reasonably well. But what did they say to David's

00:42:53.420 | point, you know, if they all of a sudden go on a crazy program

00:42:56.940 | of quantitative tightening, right? And what is that again,

00:42:59.320 | that's when, you know, we were spent, they were spending, they

00:43:02.020 | were printing, you know, money, billions and billions of

00:43:05.340 | dollars, going into the market, buying securities and giving

00:43:09.620 | people the money, right?

00:43:10.700 | That's called quantitative easing. Now we're doing the

00:43:13.700 | opposite, right? So where they're selling, and they want

00:43:16.440 | the money back. Now, the problem is, what that does is that

00:43:19.000 | removes liquidity from the market. And when you remove

00:43:23.300 | liquidity from a market, you actually make it a little bit

00:43:26.300 | more fragile, a little bit more precarious, a little bit more

00:43:28.960 | price sensitive. And so it puts us in a very tough situation,

00:43:34.160 | when the economy is slowing, when these guys may be raising

00:43:38.400 | rates, and then at the same time,

00:43:40.500 | removing money from the system, it may be a lot for all of us to

00:43:44.220 | handle. And so I think that they're under a really difficult

00:43:47.500 | Well, and if you had a decisions,

00:43:49.860 | there is a business cycle. And you know, there are always

00:43:52.440 | recessions, recessions periodically every seven to 10

00:43:54.720 | years, but they have really magnified this because you had

00:43:57.960 | the Fed for years, maintain interest rates really too low,

00:44:02.280 | and doing quantitative easing during a boom. And then the

00:44:05.680 | federal government was printing trillions and trillions of

00:44:08.120 | dollars. And they didn't stop, it was one thing, but it was one thing that was really important.

00:44:08.320 | to do it during that sort of COVID recession. But then last

00:44:15.160 | year, they printed that last 2 trillion. And that's what set off

00:44:17.500 | this wave of inflation. So you know, when I was like in school

00:44:20.440 | learning about economics, and they would tell us that all

00:44:22.240 | these government programs and actions are like automatic

00:44:24.700 | stabilizers, or what have you, like the government helps balance

00:44:27.740 | out the business cycle. No, the government like magnifies the

00:44:31.000 | business. They've made this so much worse.

00:44:33.340 | Well, they're putting their hand on the steering wheel, right?

00:44:35.500 | Because like, let the economy drive, let the free market do

00:44:37.960 | this.

00:44:38.180 | And if you start, you know, you might oversee or into federal

00:44:41.120 | government is great at setting incentives, right and creating

00:44:43.860 | like tax credit programs and incentives for private

00:44:46.100 | enterprise to invest money. But when they act as a direct market

00:44:49.160 | participant and start to actually direct capital flows

00:44:51.540 | and make decisions about how the capital market should work, it

00:44:54.420 | never ends well, because this is not what they're good at.

00:44:56.680 | Well, I think there's also another I mean, just to counter

00:44:59.620 | that there's there's also this other issue of not just

00:45:01.960 | incentives, but when they create a free capital that then allows

00:45:07.340 | a market.

00:45:08.180 | To find a way to take advantage of that free capital. And that's

00:45:11.360 | effectively what we've seen happen with Medicare, Medicaid,

00:45:15.060 | as well as with the student loan program. And, you know, I don't

00:45:19.220 | know if we're gonna get to the student loan program today. But

00:45:21.620 | I think, you know, to your point, Chamath, one of the

00:45:24.080 | things that's happened with the cost of education in this

00:45:26.660 | country is that the federal program, which was, you know, and

00:45:31.000 | I took a bunch of notes here to talk about this today. But the

00:45:34.280 | federal government began guaranteeing student loans in

00:45:36.940 | 1965.

00:45:37.960 | It's called the federal family education loan program. And that

00:45:41.020 | program made capital available for students to borrow to spend

00:45:46.240 | on universities or whatever education they want to go go

00:45:50.660 | get of their own choice. And the idea being that that will give

00:45:54.940 | them the ability to go make more income and extend their careers

00:45:57.780 | and educate the workforce. And the problem is that when that

00:46:00.880 | capital was made available, a lot of private universities

00:46:04.040 | started to emerge and private for profit colleges started to

00:46:06.880 | emerge.

00:46:07.740 | And in the years since that that program was introduced, I just

00:46:10.400 | want to give you guys some crazy statistics. So in the 1969 70

00:46:15.360 | era, the cost for a public four year college was 1200 bucks a

00:46:18.840 | year, that's room board tuition and fees. And in 2020, that cost

00:46:24.300 | rose to $21,000. And here's the the other crazy stat for private

00:46:29.700 | four year college in 1970 2500 a year 2019 2020 $46,000 a year.

00:46:37.520 | And so that capital basically allowed these for profit

00:46:41.360 | organizations or these organizations that are trying to

00:46:44.080 | grow their endowments, which are effectively like for profits,

00:46:46.620 | to charge any price they wanted. And the consumer, the student

00:46:50.720 | would be able to get free capital to fund that quote

00:46:53.720 | unquote education, because it was available to them for free

00:46:57.740 | from the federal government. And so the federal government

00:47:00.360 | created a bubble in education costs. And that bubble in

00:47:04.100 | education costs has now overburdened 15%.

00:47:06.360 | 15%

00:47:07.060 | of American adults with student loans, that many of which would

00:47:11.300 | they would never be able to pay back. And now we're in this

00:47:13.600 | really awkward situation of saying, hey, maybe we should

00:47:16.280 | forgive those loans, because it's unfair that people are

00:47:18.260 | burdened by this. And, and doing so obviously doesn't solve the

00:47:22.680 | fundamental problem, which is that making those loans

00:47:25.180 | available in the first place creates an inflationary bubble

00:47:28.240 | effect in the end asset. And the end asset in this case is

00:47:31.320 | education. But we've seen the same thing with housing. And

00:47:34.580 | we've seen the same thing with pharmaceutical drugs, and

00:47:36.600 | medical care and other services. So any place where the federal

00:47:39.980 | government steps in and says, I will provide a backstop, I will

00:47:43.180 | provide free capital to support and create a quote unquote

00:47:46.180 | incentive for this market to accelerate, you end up with

00:47:49.560 | these inflationary bubble,

00:47:50.520 | you're gonna have people game the system, right? You get

00:47:52.800 | whatever University of Phoenix types and you even the large

00:47:56.720 | AJ Calderon universities raising tuition to observe things and

00:48:00.980 | people take these loans to moth.

00:48:02.760 | Before their frontal lobes are even fully developed, and they

00:48:05.700 | have long term.

00:48:06.300 | Understanding of the ramifications of this. So where

00:48:10.540 | do you stand on this?

00:48:11.100 | Chamathia? So there's a there's an interesting article in the

00:48:14.280 | Atlantic about who really wins when you forgive student loan

00:48:18.520 | debt. And I and I just pulled out some facts. So I'm just

00:48:21.160 | going to look down here and read them just so I get them right.

00:48:23.060 | It said in the article, 13% of the US population carries

00:48:28.820 | federal student loan debt. grad students account for 37% of that

00:48:34.300 | federal student loan dollars.

00:48:36.000 | Currently, it's 1.6 trillion of total total student debt versus

00:48:40.720 | about 10 trillion of mortgage debt. So the average debt has

00:48:44.460 | gone from about 25k in 2012 to 37k in 2022. So, you know,

00:48:50.040 | almost a 50% increase in a decade. The majority of student

00:48:53.780 | debt is held by white borrowers. Only 23% of black Americans age

00:48:59.500 | 24 or greater have a college degree in 2019. So the majority

00:49:04.560 | of the black population would not be doing college degrees.

00:49:05.700 | So it's really hard to see that. But the average debt is still a

00:49:08.340 | 50% increase in a decade. So that's a pretty good estimate. So

00:49:10.660 | we're going to go through some of the numbers. And then we're

00:49:13.360 | going to go through some of the numbers that were published in

00:49:16.460 | the paper. So the average debt is $619. That's $619. And that's

00:49:21.080 | $619. So that's $619. So that's $619. And then the average debt is

00:49:24.640 | $619. Now, let's go to the next slide. So the average debt is

00:49:27.300 | $619. So the average debt is $619. So that's $619. And the average

00:49:30.360 | debt is $619. So that's $619. So that's $619. And then the average

00:49:35.400 | debt is $619. And then the average debt is $619. And then the

00:49:38.400 | average debt is $619. And then the average debt is $619. And then

00:49:41.400 | the average debt is $619. And then the average debt is $619. And

00:49:44.400 | then the average debt is $619. And then the average debt is $619.

00:49:47.400 | And then the average debt is $619. And then the average debt is

00:49:50.400 | $619. And then the average debt is $619. And then the average

00:49:53.400 | debt is $619. And then the average debt is $619. And then

00:49:56.400 | the average debt is $619. And then the average debt is $619.

00:49:59.400 | And then the average debt is $619. And then the average debt is

00:50:02.400 | $619. And then the average debt is $619. And then the average debt is

00:50:04.400 | of the 2020 biden electorate graduated from a four-year college or university versus 36

00:50:12.140 | of democrats in 2012. So you know one of the takeaways is that this may be an issue that

00:50:19.820 | affects a certain percentage of the dems who went to college but it may not represent a

00:50:25.960 | plurality of all democrats and it doesn't represent you know a majority of all. They

00:50:30.280 | sure are vocal though to your point i think. Yeah i mean look this is i think that there are two

00:50:35.160 | motivations uh political motivations for doing this now they're pretty obvious um and then i

00:50:41.700 | just want to say three things on on kind of the concern about this and why i feel very strongly

00:50:47.640 | that if we don't fix the underlying system you cannot forgive student loans you have to fix the

00:50:54.780 | system before forgiving student loans. Fix it first what's the number one fix? Well so let me just say

00:50:59.140 | the two motivations the two motivations are the first one is that we don't have a system where

00:51:00.260 | students can't pay their tuition fees and the second motivation is number one this is a stimulus

00:51:02.260 | so this morning the biden administration said that they were thinking about taking executive action

00:51:06.260 | to make the first ten thousand dollars of student loans forgiven so if you do the math across 43

00:51:11.860 | million people that's a roughly half trillion dollar forgiveness what happens that half trillion

00:51:18.180 | dollars much like we saw last year becomes a stimulus payment it is money that people now

00:51:22.580 | have that they didn't have before it is capital that they or freedom from debt that they didn't

00:51:27.060 | have before and it will stimulate the economy so there is a very very strong motivation for

00:51:30.240 | students to do this and we have a very important economic incentive here to do this which is if we

00:51:34.420 | do it it will be stimulating to the economy and people will spend more and the economy will grow

00:51:40.340 | by the way that's a it's a two and a half percent boost to gdp right so half a trillion dollars of

00:51:44.940 | free money just flushes into the system the second thing is that it will help in the midterms is their

00:51:49.500 | point of view right so they've obviously done this they've done the polling here right and and it's

00:51:53.260 | like hey when i was in junior high the kid that ran for class president was like i'm going to make

00:51:57.340 | everything in the vending machine free guess what that kid got voted in. That's why we're going to

00:52:00.220 | get him in so you know the idea that you're just going to give everyone free give your your loans

00:52:04.080 | back to you for free everyone's like my gosh this is the best thing ever elizabeth warren your genius

00:52:08.720 | you know bernie sanders your genius joe biden your genius let's say yes and so they believe

00:52:13.440 | through polling that this is going to help um help them in the midterms um but the challenge is

00:52:18.360 | if we don't solve the problem if there's no standard of value of an education if there's

00:52:24.080 | no standard around whether or not a specific accredited university increases your income and

00:52:29.840 | earning capital that's going to help you in the midterms and so i think that's a really important

00:52:30.200 | thing to think about and i think that's what we're going to be doing and i think that's what we're going to be doing is we're going to be doing this for the rest of our lives.

00:52:30.700 | potential as an individual or increases the opportunity for you as an individual

00:52:34.860 | you are wasting money you are giving federal dollars to private companies who are profiteering

00:52:40.980 | from that and the individuals are not going to benefit from it and i think that that we're seeing

00:52:45.180 | this sorry and we're seeing the structurally continue in a lot of other places where the

00:52:49.700 | federal government doesn't hold itself accountable to the standards of how their stimulus is meant to

00:52:54.660 | benefit the individuals that is being funded for the individuals are not getting a good education

00:52:59.060 | in many cases they're not getting a good education they're not getting a good education they're not

00:53:00.180 | earning more by getting this education to moss data speaks to the average but a large percentage

00:53:05.800 | of people go to crappy universities that don't improve their earnings potential and then the

00:53:10.280 | federal government says here's this free money that private university just made a bunch of money

00:53:15.160 | and no one's better off and guess who's end up paying for it taxpayers are going to end up paying

00:53:19.160 | that private company a bunch of money because we're going to forgive all the loans and so we

00:53:22.840 | have to have a standard around whether or not a dollar should be loaned to pay for education at a

00:53:28.360 | specific university by having that university pay for it and then the federal government says

00:53:30.160 | here's this free money that private university has to pay for education at a specific university

00:53:32.160 | and so we have to have a standard around whether or not a dollar should be loaned to pay for education

00:53:34.160 | at a specific university by having that university pay for education at a specific university and

00:53:36.160 | then the federal government says here's this free money that private university has to pay for education at a specific university

00:53:38.160 | and so we have to have a standard around whether or not a dollar should be loaned to pay for education at a specific university

00:53:40.160 | and so we have to have a standard around whether or not a dollar should be loaned to pay for education at a specific university

00:53:42.160 | and so we have to have a standard around whether or not a dollar should be loaned to pay for education at a specific university

00:53:44.160 | and so we have to have a standard around whether or not a dollar should be loaned to pay for education at a specific university

00:53:46.160 | tuition is because there's so much demand because there's

00:53:47.720 | free money. And so if we actually saw the federal Loan

00:53:50.560 | Program cut back or put these standards in place, the cost of

00:53:53.420 | tuition would actually decline. And profiteering would decline.

00:53:56.820 | People will get a better education and the taxpayers

00:53:59.100 | would be better off. end of diatribe. Sorry.

00:54:00.740 | No, no, it's I think it's completely legitimate sex. We

00:54:03.240 | talked on a previous episode, about how people make things

00:54:06.840 | like immigration, you know, such a charge philosophical debate,

00:54:10.560 | when there are point based systems being used in Canada,

00:54:13.040 | Australia and other places that make it much more logical.

00:54:15.900 | Do you think the solution here is to freeberg's point of just

00:54:19.740 | and I'm interpreting freeberg's point as what is the value of

00:54:23.280 | this degree nursing, great nurses can take out 100% of

00:54:26.820 | their loans, because we know there's a nursing shortage. You

00:54:29.700 | know, philosophy, graduate students maybe can't take out

00:54:33.840 | more than $5,000 in debt, because we don't see a bunch of

00:54:37.140 | job openings for that.

00:54:38.460 | Getting a history degree at Trump University is a lot

00:54:40.500 | different than getting a nursing degree.

00:54:41.940 | So Saks, what's the solution here? And then we'll, we'll

00:54:45.720 | go to the next question.

00:54:45.900 | I'm going to give you your your swing at bat in terms of buying

00:54:51.900 | votes. Yeah, let's go solution first before we go partisan.

00:54:55.140 | Look, I think that alone only makes sense when it generates ROI,

00:55:00.660 | right, it makes you're going to generate more income on the other

00:55:03.540 | side of that loan to make that loan worthwhile. And the problem

00:55:06.480 | here in too many cases is these kids go to these schools, they

00:55:09.600 | spend five years there, they get a degree in some woke nonsense.

00:55:14.040 | And of course, it doesn't help their earnings power.

00:55:15.880 | I mean, that's a bit that's a fundamental issue here is that

00:55:18.220 | these degrees are worthless, right? I mean, if you go if you

00:55:21.500 | go to if you go to college to get, you know, to become a

00:55:24.620 | doctor, or maybe a computer program or something where the

00:55:27.460 | skills have value, then of course, you can pay back the

00:55:30.340 | loan because you get a gainful job. But, you know, otherwise,

00:55:34.720 | if you just major in fine arts at Harvard or something like

00:55:37.120 | that, I mean, you basically graduate, you get a job at what

00:55:40.820 | the New York Times is your dream, you can't pay back your

00:55:43.180 | loan, you're saddled with this enormous debt.

00:55:45.040 | And think about the cultural impact that has you have this

00:55:47.980 | young generation who believes in socialism. And I think this is a

00:55:50.780 | big part of the reason why is they have no capital and they

00:55:53.380 | have no ability to accumulate capital because they're so

00:55:56.440 | saddled with debt.

00:55:57.460 | So to interpret where you said sex hard to believe in

00:56:00.220 | capitalism, if you got no capital,

00:56:02.380 | right, if you start if you start the race at negative $250,000 in

00:56:06.580 | debt to get a degree that was basically worthless for you.

00:56:09.260 | Yeah, so system is

00:56:10.400 | so long, I think maybe what we do is we reform the debt, I had

00:56:14.660 | actually

00:56:14.920 | okay with forgiving the debt in some instances, if you got a

00:56:19.420 | reform of the system. In other words, right, if we stopped

00:56:21.820 | funding these worthless degrees, but if you're basically going to

00:56:25.160 | acknowledge that, hey, we need debt forgiveness, because these

00:56:27.480 | degrees are worthless, why would you keep funding those degrees?

00:56:29.980 | So, you know, we need to have a like a more honest,

00:56:32.320 | comprehensive solution here. The other thing we should do

00:56:35.380 | actually, is one really crazy part of bankruptcy law is that

00:56:40.420 | student debt is one of the only types of debt that's not

00:56:44.500 | dischargeable in bankruptcy. I don't know if you guys know that.

00:56:46.780 | But right under George W. Bush's presidency, explain it to everybody.

00:56:49.900 | Yeah, basically, look, when when if if you ever get to the point

00:56:53.380 | where you have too much debt, and you can never pay it back, you

00:56:55.500 | declare bankruptcy, and then the court starts you over from zero.

00:56:58.900 | So you can at least start building some wealth, right? But

00:57:01.900 | you lose credit, but you lose. Exactly. No one's gonna want to

00:57:04.600 | give you credit after that. But at least you're not so deep in

00:57:07.300 | the hole, you can never recover. So that's the point of a

00:57:10.100 | personal bankruptcy. But the crazy thing is that in bankruptcy,

00:57:14.080 | you cannot get your college debt, your student debt

00:57:17.680 | cancelled, you can get your credit card debt cancelled, you

00:57:20.500 | can get other types of debt cancelled, you can't get your

00:57:22.480 | student loans cancelled. It's crazy. So that's one thing they

00:57:25.920 | should fix immediately, is make these debts dischargeable.

00:57:29.380 | Private market sacks, you wouldn't need to do that, right?

00:57:31.960 | The reason that's the case is because it's federal dollars

00:57:34.300 | that are funding those loans. But if it was private market

00:57:36.840 | dollars, people actually if banks and lenders took a loss,

00:57:41.320 | when people couldn't pay back the loans, then the market would

00:57:43.660 | work itself out. The problem is, it's the federal government

00:57:46.040 | stepping in and trying to be a market maker, right? And it

00:57:48.420 | creates this this totally crazy incentive, right?

00:57:50.740 | It creates it creates double distortions. On the one hand,

00:57:52.960 | like you said, it basically means that because government's

00:57:55.960 | money is funding everything, the tuition goes up because college

00:57:58.300 | just take advantage of it. But then also nobody's really making

00:58:01.060 | a smart ROI decision about whether a smart underwriting

00:58:04.780 | decision about whether this loan is worth making whether it

00:58:08.420 | actually stands a reasonable shot of being paid back.

00:58:11.200 | There is such an easy free market solution to this.

00:58:13.240 | Yeah, absolutely. And it's called the market solution here.

00:58:15.820 | It's called an ISA stands for income sharing agreement. This

00:58:19.540 | is where you give a loan to somebody and you get a

00:58:23.200 | percentage of their income over a period of time capped at a

00:58:27.580 | certain multiple say two x. And what this does is it aligns the

00:58:32.080 | person giving the loan with the job that's expected to come from

00:58:36.040 | the education you already have that you already have that it's

00:58:38.200 | called taxes. Yeah, but here's the problem. Nobody's watching

00:58:41.620 | the store.

00:58:42.120 | So nobody's looking at it saying,

00:58:42.820 | I'm going to give an ISA at this percentage return for nursing

00:58:46.540 | nursing. I got to pay 50% of my income every year to the federal

00:58:49.120 | government to the government like I paid taxes.

00:58:50.800 | The thing we have to remember is like if the federal government

00:58:53.500 | tries to do this, it really is just about buying votes going

00:58:56.080 | into a midterm election. And here's why. If you arbitrarily

00:59:00.160 | give a bailout of one sliver of the population,

00:59:04.000 | unless that sliver is really, really large, which we know it

00:59:07.840 | is not, it's going to really anger everybody else. Think of

00:59:12.400 | all the people that are tradespeople, working class

00:59:14.560 | people who don't have a college degree. What are they going to

00:59:17.500 | think? What about all the people that just finished paying off

00:59:20.380 | their debt? What are they going to think? It's going to upset so

00:59:24.280 | many people. And ultimately what this is, is a bunch of coastal

00:59:27.700 | elites who are miscast in jobs and saddled with debt is pushing

00:59:33.100 | for a program that isn't a broad based mechanism to create equality

00:59:37.900 | at all. It's just a get out of jail free card for a small people

00:59:41.440 | for a small group of people who unfortunately were taken

00:59:44.320 | advantage of. And this is the thing that we're not losing

00:59:46.420 | sight. We're losing sight of. You can only pay back a loan if

00:59:51.340 | you're making more money than you owe. And the fact that this

00:59:55.000 | exists shows that these loans were really poorly constructed

01:00:00.040 | and they were given in instances where they should not have been

01:00:02.980 | in the private markets. We've seen that happen, but we go

01:00:06.340 | through a cleansing mechanism to sort it out. Right? We've gone

01:00:09.700 | through- That's literally what happened during the

01:00:11.200 | 2008 real estate bubble. People gave mortgages to people who could

01:00:14.440 | not pay them back. Exactly. If I as a lender think that you're

01:00:17.740 | not going to be able to pay back the loan, I don't give you the

01:00:20.860 | loan. That's the simple mechanism that exists in free

01:00:24.400 | markets. And part of the issue is a lot of people got loans

01:00:27.760 | thinking without doing the calculation, will I ever be able

01:00:31.360 | to pay this back? And they took the loan to get an education.

01:00:33.760 | The other thing- The binary concept that I will just make

01:00:36.100 | money. But let me ask one other question of you guys. At what age

01:00:39.580 | and at what level- Yeah.

01:00:40.960 | level do you think individuals should take responsibility for

01:00:45.100 | the decisions that they're making when they take on

01:00:47.380 | personal debt? Because we see ourselves getting in the cycle

01:00:50.500 | where consumers are given debt, they don't think about the

01:00:54.460 | consequences of that debt down the road or do the analysis

01:00:57.100 | themselves and maybe they're not equipped to. And they'll take

01:00:59.620 | out a loan on a car, on a house, on a- No, but the problem is-

01:01:04.360 | And on a loan- On an education-

01:01:06.220 | But here's the thing. Like education is a very dangerous thing because

01:01:10.720 | we put so much societal credit and external signaling to it, and we give everyone effectively

01:01:16.600 | the same quantum of risk. But that's not true for a credit card, nor is it true for a car loan.

01:01:21.460 | So the private markets are efficient in that when you first try to get a credit card-

01:01:25.660 | Sure. You don't get an MX Centurion or

01:01:28.120 | platinum card. You're given a Chase Sapphire card with a $500 limit,

01:01:31.780 | and you earn the right to borrow more. Same if you applied for a car loan,

01:01:36.160 | the same with a mortgage, it's based on a down payment. So there's differential risk pricing.

01:01:40.480 | And if you don't have differential risk pricing, you're getting a lot of people-

01:01:44.620 | How would you edit education? The market would figure it out.

01:01:47.380 | The market would because you would differentially price the risk as you guys-

01:01:50.380 | You're literally a brainstormer right now. Like what are your grades?

01:01:52.780 | Well, no- What courses did you take?

01:01:54.580 | Whatever it is, we're not going to get it right. The market will get it right,

01:01:58.600 | but the market would figure it out. The problem is, and sorry, the incentive was,

01:02:03.160 | and this is a really important point. If you guys read Ray Dalio's book,

01:02:07.120 | which we've talked about a number of times, he's identified and highlighted

01:02:10.240 | that a growing economy in a successful country improves by improving education and having more

01:02:20.260 | people get higher education, generally speaking. And so the initial incentive, the initial intention

01:02:25.720 | behind the federal student loan program was a good one, which was to give people access to capital

01:02:31.180 | that the private markets were not providing at the time so that they could go out and get a higher

01:02:35.200 | education. We could improve the education of our workforce and we could grow our economy.

01:02:40.000 | Nowadays, the question that we always forget, remember, we always get one step away and then

01:02:44.920 | two steps away and five steps away and we miss the point. We're in that moment now where the

01:02:49.540 | question really is, is the federal student loan program doing more harm than good? Are we actually

01:02:56.020 | creating value from our higher education system in this country or not? No.

01:02:59.260 | No, but most importantly, is the private market there? Because you look at the total

01:03:03.220 | debt outstanding, $1.7 trillion. There would be a private debt market.

01:03:07.360 | Friedberg. Friedberg, don't sell beyond the close. The answer

01:03:09.760 | is no. We have a massive employment gap. The data tells you in every single which way possible that

01:03:16.480 | we are not educating our young people to take the jobs that are needed for a high growth, functionally

01:03:22.840 | moving economy. We know that. So we are miseducating these folks and then we are giving

01:03:28.960 | them access to enormous amounts of debt that they have no reasonable chance to pay back. And I think

01:03:34.780 | that that should be fixed by fixing the incentives of the universities. You are right. Universities

01:03:39.520 | are for-profit asset management businesses wrapped by this philanthropic do-gooder nonsense that they

01:03:45.820 | try to tell people to get you to go there and pay $50,000 a year in tuition. It's a joke.

01:03:50.440 | And they're calling people to think that these degrees are actually going to make

01:03:55.000 | them successful humans. They come out miseducated

01:03:57.580 | and undereducated and incapable of servicing the economy's needs. Separately, the other thing,

01:04:03.820 | if you take a step back and take student loan off the table for a second and just say, "Any

01:04:08.620 | A consumer handout that touches less than 40 or 50% of the economy or of the population

01:04:17.800 | of a country is very precarious.

01:04:22.220 | Student debt, in this case, 15% of the US population, so a lot of people.

01:04:26.240 | But it also means that there's 85% who don't benefit.

01:04:28.980 | What will those 85% of the people say when they have to foot the bill for the first 15%?

01:04:34.600 | Then what do you think happens with other kinds of debt?

01:04:38.100 | What happens when the oil lobby says, "Forgive our debt because we're in a national energy

01:04:42.460 | crisis."

01:04:43.460 | What will all the climate folks think about that?

01:04:45.460 | No accountability.

01:04:46.460 | It's no accountability.

01:04:47.460 | It's unfair.

01:04:48.460 | Well, it creates a slippery slope.

01:04:50.500 | My last point on this is, to the extent that we actually want to forgive student debt,

01:04:56.080 | I'm fine if that's the law of the land.

01:04:57.700 | That's great.

01:04:58.740 | It should go to the floor and it should be debated in Congress and it's a law that should

01:05:03.420 | be passed, but it should not be by executive edict trying to back in—

01:05:07.580 | To buying votes in a midterm election.

01:05:09.620 | It's gross.

01:05:10.620 | Sachs, until the end—

01:05:11.620 | Well, by the way, just on the politics of that, I think this could potentially hurt

01:05:14.540 | them because, Chamath, to your point, this is basically a bailout of the woke professional

01:05:19.760 | class.

01:05:20.760 | It's the underemployed graduates of these universities who, again, are members of the

01:05:25.720 | professional class.

01:05:26.960 | They majored in things that didn't increase their earnings potential.

01:05:30.340 | Meanwhile, the majority of the country is working class.

01:05:33.340 | Something like two-thirds of the country is still working class, meaning non-college educated.

01:05:37.060 | They're going to have to pay for this bailout.

01:05:39.340 | In one way or another, either through higher taxes or more deficit spending or more debt,

01:05:44.680 | the burden of this bailout is going to fall on them.

01:05:47.680 | Why should they have to pay to bail out this professional class?

01:05:51.140 | Literally, somebody working in retail is paying for somebody's graduate school degree in creative

01:05:55.800 | writing or something.

01:05:56.800 | It's completely and profoundly unfair.

01:05:58.540 | To the answer to Freberg's question, we actually know when executive function fully matures

01:06:04.280 | in adults, it's 25 years old.

01:06:06.140 | Yeah.

01:06:06.180 | Yeah.

01:06:06.280 | Yeah.

01:06:06.380 | Yeah.

01:06:06.440 | Yeah.

01:06:06.500 | Yeah.

01:06:06.540 | and that's when you can actually make long-term thinking. So, there is an argument that people

01:06:11.980 | should not be allowed to take these loans that are not even-- that you can't get out of,

01:06:17.420 | or there should be some cap on the amount of loans you can take because people at the age

01:06:22.380 | of 17, 18, 19, 20 are absolutely not able to make these decisions. There are other programs,

01:06:27.340 | as well, that work. So, in Canada, I went to a school called the University of Waterloo

01:06:31.660 | and… Fantastic engineering school. The reason I went there and I did electrical engineering

01:06:35.660 | there is that they had a program where after the first year-- so, the first year looks like every

01:06:40.140 | other year at every other school, okay? But you're there for two semesters from September to May.

01:06:46.300 | But after that, you start working and you alternate four months of work with four months of

01:06:51.900 | school. You get paid for that work and what it allowed me to do was graduate with meaningfully

01:06:57.900 | less debt, but it also allowed me to graduate with a commercial skill set. I was able to get a job.

01:07:04.780 | And in that moment, actually, I was working at a bank and I got profoundly lucky, which is I worked

01:07:10.140 | for an individual and I was trading interest rate derivatives and I was learning to trade

01:07:16.700 | technology stocks on the side. And this guy, Mike Fisher, incredible human being, and I made in one

01:07:23.580 | year like $25,000 or $30,000 for him. Yum, yum. Zip, zip.

01:07:27.980 | He wrote me a check and he said, "Here, you have $25,000 of student debt. Go pay it off right now.

01:07:32.140 | I'll let you cash out this whole book." How much did you--?

01:07:32.780 | I graduated with about $20,000. Yeah.

01:07:32.780 | This whole book. I graduated with about $28,000 of debt.

01:07:36.380 | I had about $8,000, I think. I had somewhere between $10,000 and $15,000,

01:07:41.260 | $10,000 and $20,000. And then I got my first bonus check after my first year of work after

01:07:46.540 | undergrad and I paid off all my debt and it felt incredible.

01:07:50.300 | Incredible. It was amazing. When I paid off my debt,

01:07:53.180 | I've never been in debt since. I walked downstairs to the bank and

01:07:57.020 | I gave them the check and I endorsed it and I said, "Here's my student loan number." And I was like, "Oh, my God.

01:08:01.900 | I was free." It was an enormous sense of relief.

01:08:06.780 | For me, it was credit card debt. I had accumulated all the credit card because I went to Cal. It was

01:08:09.980 | like four grand a year to go to Cal. It was a lot cheaper back then.

01:08:12.940 | If I didn't go to Waterloo, I would have had double the debt because I wouldn't have had work.

01:08:17.020 | But then also, I think about all these scenarios, I wouldn't have had two years of work experience.

01:08:21.500 | I may not have gotten the job that I did at Bank of Montreal at the time. That may not have been able

01:08:25.820 | to give me a chance to meet Mike Fisher. All these things could have happened. You can't rely on the

01:08:31.420 | luck of the butterfly effect so that you have a reasonable shot of building a good life.

01:08:35.820 | There are all these things in universities that I think are really mismanaged today,

01:08:41.100 | and they go and work against what is right in society. I'll give you another example.

01:08:45.660 | The dean of the engineering school and the president of University of Waterloo was here

01:08:49.980 | this week with me. I asked them, "Tell me about these global rankings." They said,

01:08:55.500 | "You know, it's just a really difficult game." They said, "If we wanted to compete to try to get high on the list,

01:09:00.940 | we would have to do the things that would undo all the things that made us great and unique in the first place."

01:09:07.580 | Right.

01:09:08.380 | I was like, "You know what? I am such a huge supporter of this school. Please just continue to do what you're doing."

01:09:13.660 | I'm so proud that they have the strength to just stand on their own two feet.

01:09:17.180 | But every other school is running this shell game of gerrymandering all of these statistics,

01:09:24.140 | trying to get high on the list, to trick some parent, to force their kid to go to some school, to then graduate,

01:09:30.460 | with $200,000 of debt, to get a job that doesn't then give them any line of sight to paying it off.

01:09:36.620 | I don't think it's their kids' fault, but you have to reform the system.

01:09:42.140 | I think the first thing you need to do is look inside these universities and hold these folks accountable.

01:09:46.620 | These incentive systems are just crazy.

01:09:51.900 | Speaking about crazy, we talked about Bill Wang and his—

01:09:56.300 | That's your transition? That's your transition?

01:09:59.980 | They can't all be as elegant and smooth.

01:10:03.420 | Here's Jake Howell. He's looking at the agenda for today, and he sees Bill Huang,

01:10:07.100 | and he's like, "Okay, how do I do this? How do I do this?"

01:10:08.780 | The Huang-er. The Huang-er.

01:10:09.900 | Yeah. Okay. Crazy. Crazy. The linkage is craziness. Okay, go.

01:10:13.980 | No, no, no. No, no, no. Hold on. The linkage is trillions and billions.

01:10:18.460 | Trillions and billions.

01:10:19.340 | Speaking of trillions and billions—

01:10:20.700 | Speaking of trillion-dollar mistakes—

01:10:22.700 | We got a—

01:10:23.900 | Bill Wang and his CFO were arrested on Wednesday in charge with racketeering, wire fraud, and conspiracy—

01:10:29.500 | We talked about this when it happened.

01:10:31.740 | His firm, Archegos—

01:10:35.500 | Archegos. Archegos. Archegos.

01:10:37.420 | Archegos.

01:10:38.060 | Archegos. His poorly-named firm and family office—

01:10:41.100 | We covered this in real time back on episode 28.

01:10:44.140 | They famously lost $20 billion over two days when they were margin-called back in March of 2021.

01:10:51.740 | He worked at Tiger Management, yada, yada.

01:10:54.300 | And it was at the time reported that they were trading—

01:10:59.020 | Billions of dollars at over 5x leverage.

01:11:01.820 | According to the SEC complaint, at its peak, the firm was managing $36 billion

01:11:07.100 | with $160 billion of exposure, which is 4.5 times leverage.

01:11:10.940 | But Archegos, or whatever it's pronounced, started with only $1.5 billion in assets

01:11:16.220 | in March of 2020.

01:11:18.860 | So Wang flipped $1.5 billion in capital into $160 billion of exposure in 12 months,

01:11:24.780 | essentially trading somewhere in the neighborhood of $100 to $1 at its peak,

01:11:28.540 | according to this complaint.

01:11:30.060 | A bunch of banks have lost money because they were supporting this.

01:11:34.780 | Credit Suisse lost $5.5 billion.

01:11:36.620 | Morgan Stanley lost $1 billion.

01:11:38.140 | UBS, $774 million.

01:11:41.180 | The New York Times described it as, quote, "orchestrating a stock manipulation scheme

01:11:45.500 | that relied on them masking and concealing the enormous risk they had taken."

01:11:50.780 | Chamath, you had some thoughts on this, I think.

01:11:52.940 | So first, I think we should probably explain how he did this, right?

01:11:57.340 | Yes.

01:11:57.580 | So—

01:11:57.660 | That's—

01:11:58.060 | That's everybody's question, is how did the banks let this happen?

01:12:01.020 | So explain.

01:12:01.500 | Well, I think first, it's what's the mechanism?

01:12:04.380 | So there are ways in capital markets to take really extreme bets.

01:12:09.340 | This way is what's called a total return swap.

01:12:15.020 | And so the basic way that this works is you have two people on each side of a trade.

01:12:20.620 | And what you basically say is, let's agree on what's called a reference asset.

01:12:27.580 | So I'll just use an example.

01:12:28.940 | Let's just say it's—I think Discovery was one of the companies that they were trading.

01:12:34.220 | So Discovery Communications.

01:12:35.660 | Let's look at—that's the reference asset, that stock.

01:12:38.060 | And what I'm going to do is buy protection.

01:12:43.340 | And what you're going to do is sell protection.

01:12:47.980 | And essentially what happens is, as the stock goes up and down, you're going to net the

01:12:55.100 | difference between these two people.

01:12:57.100 | And when you do it that way via a derivative—so what it forces the person to do, the bank

01:13:03.740 | in this case, is to go out and buy the stock, okay?

01:13:07.340 | Show that they are hedged in case the price goes up a lot because they have to pay that

01:13:12.940 | difference, in this case, to Bill Hwang.

01:13:16.300 | And if the price goes down, Bill Hwang has to pay that difference back to the bank.

01:13:22.780 | So what happened is that he went to three different banks.

01:13:26.620 | Morgan Stanley, Goldman Sachs, and Credit Suisse.

01:13:28.300 | And effectively what he did was he bought—he made these bets across a handful of names.

01:13:33.660 | But he did it with so much leverage that he ended up owning 60 or 70% of some of these

01:13:39.740 | companies.

01:13:40.220 | And in March of last year, when the stock market turned over, he owed them enormous

01:13:46.460 | amounts of money, so much so that these banks had to unwind these trades, which caused further

01:13:52.220 | downdrafts of the stock market.

01:13:56.140 | And so the stock market went through a lot of these downdrafts in the stock and almost

01:14:00.220 | spilled over to the broader stock market.

01:14:02.220 | Jason, the numbers from the SEC complaint are pretty crazy.

01:14:06.220 | As of March 31st of 2020, they had $1.6 billion invested on a gross exposure of $10.2 billion.

01:14:14.620 | What that means is they were able to go and lever up this $1.6 billion to behave in the

01:14:21.340 | market as if they had $10.2 billion.

01:14:23.820 | By January 1st of 2021—so nine months later—

01:14:26.620 | they had $7.7 billion of invested capital.

01:14:29.980 | So they'd done really well, right?

01:14:31.740 | They'd made 70% on this $10 billion.

01:14:33.740 | But they levered that up again, and so they had gross exposure of $54 billion.

01:14:39.100 | And then just, I think, three months later, by March 22nd, they had $36 billion of invested

01:14:48.380 | capital, meaning they had $36 billion of cash.

01:14:50.780 | This guy had taken $1.6 billion and spun it up to $36 billion in investment.

01:14:55.180 | Yeah, yeah.

01:14:55.660 | And basically—

01:14:55.740 | Yum, yum.

01:14:56.140 | This guy went like 20x.

01:14:57.420 | In a year.

01:14:58.220 | But then he had levered that up again, and he had $160 billion of gross exposure.

01:15:04.940 | And then the market turned, and he owed all this money, and so all these folks had to get out of it.

01:15:09.740 | But they also allege that he was trying to do short squeezes on the stocks to try to make them

01:15:13.660 | goose even more.

01:15:14.700 | So there was massive manipulation because of his position size, correct?

01:15:17.500 | Yes.

01:15:17.740 | So this is what happened.

01:15:19.020 | But then here's how it is allowed to happen.

01:15:21.100 | So if you try to do the same thing in interest rates,

01:15:24.860 | in the interest rates market versus the equities market, it's not possible.

01:15:28.300 | Why?

01:15:28.700 | If I wanted to go and buy a credit default swap, effectively think of that as the same

01:15:33.500 | kind of thing he did, but on the debt of a company, on the debt of Discovery.

01:15:37.100 | What I would do is I would be able to enter into that trade with a bank, but it goes into

01:15:42.940 | a clearinghouse.

01:15:43.660 | And that clearinghouse is able to tell all the banks how much risk is building up in

01:15:50.140 | the system.

01:15:50.620 | And the reason we implemented this clearinghouse was to make sure, because we're going to

01:15:54.380 | make sure coming out of the great financial crisis, none of that chaos ever happened again.

01:15:58.380 | But we did not include the equity markets in that clearinghouse and in the laws that

01:16:03.820 | regulate it.

01:16:04.300 | So what this is is a very shadowy gray part of the market that is poorly regulated, that

01:16:10.780 | has very little oversight.

01:16:11.980 | So what do the banks do?

01:16:13.100 | The banks say to you, if you want to put this thing on, give me a balance sheet so I understand

01:16:18.380 | what the risk is.

01:16:19.020 | A piece of paper, a report.

01:16:21.580 | And I think what they're alleging

01:16:23.660 | is that these guys lied so that any individual bank, in this case Goldman, Morgan, and Credit

01:16:29.580 | Suisse, had no idea because they kind of doctored these reports to each other.

01:16:33.580 | And that's why all this risk built up in the system.

01:16:36.620 | It would be solved if you had a clearinghouse for equity derivatives the same way you have

01:16:40.860 | for interest rate derivatives.

01:16:41.660 | It is crazy to think that somebody was doing this and thought they would get away with

01:16:47.660 | it and had been up 20x.

01:16:49.660 | The psychology of these people, the Madoffs of the world, I just find, I don't know, I'm

01:16:53.500 | just fascinated.

01:16:54.300 | I mean, why wouldn't he if he had 20x?

01:16:55.740 | We just thought, by the way, we talked about how the four of us are grinding to return

01:17:01.740 | 2x of our money in 10 years.

01:17:03.420 | Yes.

01:17:03.920 | And this guy's like YOLO.

01:17:05.580 | He's 7x or 10x, 1.6 billion dollars, and it was not enough.

01:17:11.180 | It's not enough.

01:17:12.380 | It's insane.

01:17:12.620 | I mean, people have-- I mean, what do you think the psychology of this is?

01:17:15.980 | I have no idea.

01:17:18.380 | That's what I'm trying to figure out, Sachs.

01:17:19.740 | What's the psychology of somebody who tries to do this?

01:17:22.620 | I'm not even gonna try to figure out Sachs.

01:17:22.660 | I'm not even gonna try to figure out Sachs.

01:17:22.900 | I'm not even gonna try to figure out Sachs.

01:17:22.940 | I'm not even gonna try to figure out Sachs.

01:17:23.260 | They're already a billionaire.

01:17:24.460 | They've already got their jet.

01:17:25.900 | They could go anywhere.

01:17:26.700 | They could have anything.

01:17:27.740 | They could buy any home.

01:17:29.420 | They could go on any vacation.

01:17:30.780 | That's the thing I never understand about these people is like,

01:17:33.900 | this has got to be some crazy sociopathic behavior.

01:17:37.580 | Jekyll, did you always want a jet?

01:17:39.500 | By the way, the guy--

01:17:41.340 | I just got a business select on Southwest.

01:17:43.980 | When you started your career, what did you want?

01:17:45.740 | The Knicks.

01:17:47.020 | That's what I still want.

01:17:48.380 | Well, when you started, you wanted a house, right?

01:17:50.220 | And then you got the house and you wanted the home in Tahoe, and then you--

01:17:53.020 | You want the Knicks.

01:17:54.460 | The vacation home, and then you want the jet.

01:17:56.780 | And then, I mean, I don't know why this is confusing.

01:17:59.580 | Well, no, but I don't want it enough to put my entire freedom at risk or to cheat.

01:18:05.340 | Apparently, this dude was a Christian.

01:18:06.780 | I'll put that in quotes because I don't-- I mean, I don't know.

01:18:08.780 | Doesn't sound like Christian behavior, bro.

01:18:09.980 | Ran Bible study and stuff in the mornings.

01:18:12.380 | He lived in some modest house in Jersey, blah, blah, blah.

01:18:14.780 | But he was a bit of a freaky deke.

01:18:17.820 | What does that mean?

01:18:18.380 | So weird.

01:18:19.420 | I mean, the guy couldn't get enough.

01:18:20.940 | By the way, the dude was pinched in two.

01:18:23.020 | 2012 for insider trading and had to pay a settlement and might give back everybody's

01:18:26.620 | money.

01:18:27.100 | He got pinched.

01:18:28.140 | It's crazy.

01:18:28.860 | And it is what it is.

01:18:29.740 | You know, you never ran on your friends.

01:18:31.260 | I got pinched.

01:18:31.900 | He got pinched.

01:18:32.940 | Yeah, he got pinched.

01:18:33.900 | When you grow up in the streets, you know that.

01:18:35.580 | What happened to this guy?

01:18:36.380 | I got pinched.

01:18:37.180 | He got pinched.

01:18:37.660 | When you grew up in the streets.

01:18:38.940 | The guy ate cheese.

01:18:39.740 | He didn't run out.

01:18:40.300 | He ratted on his friends.

01:18:41.420 | He ran out of the Medjigo.

01:18:42.860 | He tried to steal some Medjigo.

01:18:43.740 | He got pinched.

01:18:44.140 | And he ratted on his friends.

01:18:45.100 | Now the CFO got pinched too.

01:18:46.460 | They flipped him.

01:18:48.220 | This is super deranged.

01:18:51.020 | Speaking of deranged.

01:18:51.900 | Transitions.

01:18:55.900 | Where are we going?

01:18:56.780 | Where are we going?

01:18:57.660 | You know what someone needs to do?

01:18:59.260 | Someone needs to take all of JCal's transitions from the last couple of shows and just put

01:19:03.020 | them together in a row.

01:19:03.980 | Yeah, just a supercut.

01:19:05.020 | Speaking of crazy.

01:19:05.420 | Speaking of deranged.

01:19:06.540 | Okay, speaking of deranged.

01:19:08.140 | Yeah.

01:19:08.460 | On Wednesday, the Department of Homeland Security.

01:19:11.340 | Speaking of billions.

01:19:12.300 | Announced a disinformation governance board.

01:19:16.300 | Disinformation governance board.

01:19:17.740 | According to the announcement, the board will immediately, immediately begin focusing on

01:19:21.820 | millions.

01:19:21.820 | Misinformation aimed at migrants at the US Mexican border.

01:19:25.260 | The board will be led by disinformation expert Nina Jankiewicz.

01:19:30.140 | He has researched Russian misinformation tactics and online harassment.

01:19:34.940 | This is also the woman who sings show tunes on TikTok.

01:19:37.980 | JCal, I feel like you should be running our disinformation board.

01:19:42.460 | You always have such a strong opinion.

01:19:43.820 | You have such a nose for what's BS and what's not.

01:19:47.020 | Here's what's going on here.

01:19:48.300 | So first of all, this woman claims to be an expert in disinformation.

01:19:51.740 | Let's evaluate that claim.

01:19:53.180 | She was an active pusher of the Steele dossier, which turns out is disinformation for which

01:19:59.260 | people are now under indictment.

01:20:00.700 | She also was active in trying to censor the Hunter Biden laptop story, which as it now

01:20:06.140 | turns out was not disinformation.

01:20:07.420 | It was absolutely true as acknowledged by the New York Times, the Washington Post.

01:20:10.940 | You would think that these blemishes on her record might disqualify her from being an

01:20:16.380 | expert on disinformation, but actually in the view that people are hiring her, these are

01:20:21.340 | actually good.

01:20:21.660 | They're actually qualifications because they are not interested in the truth.

01:20:24.540 | The reason this department is set up and what they mean by disinformation is they have hired

01:20:29.740 | her to push partisan political points.

01:20:32.220 | That's what's going on here.

01:20:33.420 | That's what disinformation is.

01:20:34.620 | Now, it used to be that if you disagreed with somebody, you just say, listen, I disagree

01:20:39.500 | with you or maybe you're an idiot, whatever, you're wrong.

01:20:41.980 | But now the way that these debates are set up and the way they work is they don't just

01:20:46.940 | say you're wrong or that's not true.

01:20:48.460 | They try to label you as disinformation so you can get you censored.

01:20:51.580 | And the point of hiring this disinformation czar is basically to censor the disinformation,

01:20:57.900 | basically to shut down the debate.

01:20:59.260 | That is basically the whole point of the censorship.

01:21:02.220 | Do you think there's any timing here with Elon by Twitter?

01:21:05.020 | Yes, of course.

01:21:05.820 | There was a great tweet about this.

01:21:09.980 | I mean, I love conspiracy sacks, by the way.

01:21:11.980 | I don't think it's conspiracy theory.

01:21:13.500 | There was a great tweet about this that we live in a future where it's like a mashup

01:21:18.620 | of George Orwell and Ayn Rand.

01:21:20.860 | Because here you are.

01:21:21.500 | You have Elon Musk, the heroic lone entrepreneur trying to rescue freedom of speech.

01:21:27.660 | At the same time, you have this Orwellian ministry of truth being created by the federal

01:21:31.500 | government.

01:21:31.900 | I mean, no awareness of naming.

01:21:33.740 | Yeah.

01:21:35.020 | It's just bizarre.

01:21:35.820 | But the disturbing thing about it is-

01:21:37.580 | Disinformation governance board is such a dystopian name.

01:21:40.380 | The thing about it that's a little bit scary here, I know you play the video of her doing

01:21:45.820 | show tunes and it seems sort of silly, but the thing that's scary is that this is under

01:21:50.540 | the homeland.

01:21:51.420 | Homeland Security Department.

01:21:52.620 | That's another weird wrinkle.

01:21:53.980 | Why is that there?

01:21:54.940 | It's the most militarized department in our government.

01:21:58.140 | So it's really scary to put the ministry of truth under the department that has all the

01:22:02.300 | soldiers and all the weapons.

01:22:03.020 | Ministry of truth is not the name of it, but it's close.

01:22:06.060 | Pretty darn close.

01:22:06.860 | Now, why is it there?

01:22:08.060 | I'll tell you why.

01:22:08.780 | Because this was built up to.

01:22:10.540 | Ministry of truth.

01:22:12.140 | Shout out George Orwell.

01:22:13.100 | A couple of months ago, there's a news story that we might have covered on this pod

01:22:17.660 | where the Homeland Security Department redefined

01:22:21.340 | disinformation to comprise.

01:22:23.820 | They said it represented an escalation of the terror threat level.

01:22:27.740 | So in other words, they basically said that this information was tantamount to terrorism.

01:22:31.900 | Remember that?

01:22:32.620 | Didn't we talk about that?

01:22:34.140 | This is the payoff to that.

01:22:35.900 | First, they define.

01:22:37.260 | They basically define the other side as being disinformation of the debate as being disinformation.

01:22:42.540 | Then they define disinformation as basically terrorism.

01:22:45.980 | Then they have the Homeland Security Department, which is supposed to be responsible for terrorism.

01:22:50.540 | Create this ministry.

01:22:51.260 | Of truth.

01:22:51.980 | This is what's going on here.

01:22:53.020 | It's really weird.

01:22:53.820 | Just to remind everyone there was concern in the last election.

01:22:57.820 | I'm going to play devil's advocate as I often find myself doing here.

01:23:01.100 | That just to try and explain the world.

01:23:04.540 | That's the reason I often play this role because I try to understand the world.

01:23:07.100 | But there was a real concern that the Russian government was using information warfare and

01:23:16.300 | propaganda through social media proven to influence voting.

01:23:21.180 | And that that is considered a security threat to the integrity of our elections.

01:23:26.460 | Therefore, this is a homeland security issue.

01:23:29.820 | And there is a question mark, of course, that everyone has on how far they're going to go.

01:23:34.460 | Once you set this precedent, when would they ever stop in terms of quote unquote policing

01:23:39.260 | information and policing what's true and managing internal propaganda and internal media delivered

01:23:44.780 | to us by the government?

01:23:45.820 | That's the other side of the coin.

01:23:47.180 | But the primary side of the coin, the initial side, the initial representation that I'm

01:23:51.100 | that I think folks do have concerns around is how do we keep foreign actors from creating

01:23:57.100 | misinformation campaigns that go viral and influence elections and sex?

01:24:01.740 | I don't know if you think that that's a concern we should or shouldn't have, but how would

01:24:04.460 | you address it if you were the president?

01:24:05.980 | And that was the challenge to like, how do we stop that from happening?

01:24:09.580 | The foreign actors interfering in our elections is certainly a concern we should have if it

01:24:14.300 | was actually happening on a big scale or in a meaningful way.

01:24:17.980 | There's the qualifier.

01:24:18.460 | I mean, this is basically look, this is basically a hoax.

01:24:21.020 | Okay.

01:24:21.820 | John Durham is basically out there making indictments right now, proving the extent

01:24:25.580 | of this hoax.

01:24:26.700 | It started with the whole Steele dossier, which was a piece of campaign opposition research

01:24:31.500 | that was manufactured by Hillary Clinton's campaign.

01:24:34.620 | The lawyers who basically produced it are under indictment.

01:24:37.580 | And that's where this whole thing of Russian disinformation came from.

01:24:41.100 | And the only proof for that thesis is that supposedly the Russians bought $100,000 of

01:24:46.380 | Facebook ads on Facebook.

01:24:48.460 | So I'm not denying that that occurred, but it was,

01:24:50.940 | it was relatively minor.

01:24:52.060 | It was a drop in the bucket of all the activity going on around the last election.

01:24:55.580 | Wait, wait, to be clear, to be clear, that was just the ads that were bought with,

01:24:59.020 | with like credit cards that said like FSB on it.

01:25:01.980 | Like, but who way to go Facebook security team?

01:25:04.780 | You probably, you know, didn't count all the number of credit cards that were stolen.

01:25:08.460 | I'm pretty sure the Russians are capable of stealing John Smith's credit card and using

01:25:11.580 | that to buy ads as well.

01:25:12.460 | Well, I looked at those ads.

01:25:13.820 | I used to see those ads.

01:25:14.780 | They were ludicrous.

01:25:15.740 | They weren't going to convince anybody of anything.

01:25:17.580 | I mean, they had like Jesus and the devil.

01:25:20.860 | arm wrestling each other.

01:25:22.140 | And the Jesus figure was basically set and the, the, you know, it was just absurd.

01:25:27.900 | I mean, the Jesus figure was saying that.

01:25:29.100 | Okay.

01:25:29.260 | Wait, to be clear, it happened and you've now stepped back your position on like, it

01:25:33.020 | just wasn't at scale to your opinion.

01:25:35.180 | I think, I think, look, the, the scale interference in the election was committed by big tech.

01:25:41.420 | I mean, they censored the Hunter Biden story two weeks before the election.

01:25:45.820 | It turns out that's a completely true story that Hunter Biden has extensive business dealings

01:25:50.780 | with the president.

01:25:52.060 | And that's not just in Ukraine, the country we are now.

01:25:55.660 | Yes.

01:25:55.980 | But we are now deeply involved in a war there.

01:25:58.700 | And that story, the electorate had the right to take that into account.

01:26:02.540 | Big tech censor that story.

01:26:03.900 | There was a reason for that.

01:26:05.100 | May I respond to that?

01:26:06.220 | Just to give people like making a very difficult decision.

01:26:09.580 | You have to remember Trump asked Putin on stage to hack Hillary's emails and they did.

01:26:14.620 | Then he asked the Ukraine to take action against the Bidens or he wouldn't give them support.

01:26:19.820 | He was impeached for that.

01:26:20.700 | If you put yourself in the, and I'm not saying Twitter made the right decision here, but there

01:26:24.780 | was, and there was also sexual material, you know, people's nudes, which, and hacked material and

01:26:29.500 | nudes are against the terms of service.

01:26:31.740 | So I think two things happened concurrently.

01:26:34.460 | One, listen, the people working at Twitter are 98% liberal.

01:26:37.980 | They don't want Trump.

01:26:38.620 | They saw it as an existential threat.

01:26:40.780 | And then two, they don't want to link to hacked material.

01:26:43.660 | Oh, really?

01:26:44.700 | Well, hold on a second.

01:26:45.580 | Hold on.

01:26:45.900 | During the whole Canadian trucker.

01:26:47.180 | Let me finish this point.

01:26:48.380 | No, I have to finish my point.

01:26:49.660 | The third point.

01:26:50.140 | And then I'll let you go.

01:26:50.620 | I'll let you go.

01:26:51.100 | Is that in addition to all that Hunter Biden is completely a grifter.

01:26:55.500 | Go.

01:26:55.980 | Okay.

01:26:56.380 | I agree with you on that one.

01:26:57.260 | So look during the whole Canadian trucker thing, remember when all the people who contributed

01:27:02.300 | to those Canadian truckers, they got docs.

01:27:04.940 | I mean, basically there was a hacker who leaked all the people who had donated and social

01:27:09.180 | networks were happy to print all that information.

01:27:11.260 | So this idea that they censor hacked information is nonsense.

01:27:15.660 | The lives of TikTok account just got docs by Taylor Lorenz look, whether you think that was a

01:27:20.540 | good idea or not.

01:27:21.660 | The point is these principles are invoked very selectively when there's a story they

01:27:25.500 | want to suppress and the New York times and the Washington post have both not come out

01:27:29.820 | and said that the laptop was real.

01:27:31.420 | It's been authenticated.

01:27:32.620 | The story was real.

01:27:33.580 | And this whole idea that it was disinformation that was just invented.

01:27:37.500 | I mean, it was just invented.

01:27:39.020 | Well, no hacked.

01:27:40.060 | It wasn't that it was just a ratio that it was potentially hacked and you, and Trump

01:27:43.340 | nothing was hacked.

01:27:44.620 | Here's the thing.

01:27:45.180 | Trump set the stage for that.

01:27:46.620 | And the, uh, the, the people at Twitter and Facebook.

01:27:50.460 | Who also made these decisions.

01:27:51.980 | They were informed by three later agencies, department of justice and, and FBI, et cetera.

01:27:56.540 | Hey, this is potentially hack material designed to interfere with the election.

01:27:59.420 | Listen, it also is true that Biden is a jank events and other democratic party operatives

01:28:04.940 | just made up out a whole cloth.

01:28:07.180 | That the hunter Biden's story was disinformation.

01:28:09.260 | It was true.

01:28:09.980 | It's been acknowledged as true.

01:28:11.420 | The Washington post is true.

01:28:12.460 | I mean, I think this is true.

01:28:13.980 | So hold on.

01:28:14.620 | So it goes to my point.

01:28:15.580 | Can improve.

01:28:16.620 | No, it's not about improving it.

01:28:17.980 | Look, well, no, no, I, you didn't fear my sentence.

01:28:19.820 | I think this is where.

01:28:20.380 | Social media can improve, which is if they had to explain every one of these decisions,

01:28:24.780 | they make in full in transparency.

01:28:27.020 | I think that's something Elon could bring to this party, which is if you're going to

01:28:30.620 | block something, we need to know why.

01:28:33.340 | And they'd never explain why and who made the decision.

01:28:37.500 | And I think that that transparency would benefit situations like this.

01:28:41.340 | If the DOJ or FBI told them, this is hacked material.

01:28:45.660 | Then they got to go to the DOJ and say, Hey, you got to give us cover here.

01:28:48.460 | If this is in fact hack material, you

01:28:50.300 | told us not to print it.

01:28:51.260 | We're not going to print it, but it was just bizarre that one publication

01:28:55.260 | got dinged like the New York post.

01:28:56.540 | It didn't.

01:28:57.020 | It screamed on the old newspaper in America, the oldest newspaper in America.

01:29:00.700 | It's also not the bastion of like, it doesn't matter.

01:29:03.100 | That's not for you to decide.

01:29:04.140 | It's not for Twitter to decide.

01:29:05.180 | It's a legitimate publication that had a true story.

01:29:07.340 | And I don't disagree.

01:29:07.900 | And it was relevant to the election and the American people should have been able to take

01:29:10.540 | that into account.

01:29:11.500 | And people like Nina Jankovic or whatever, our new czar of the ministry of truth.

01:29:16.460 | She was out in the forefront, basically calling that story disinformation.

01:29:20.220 | Meanwhile, she's pushing the steel dossier, which really was.

01:29:22.860 | I think if that story was confirmed, would Biden have won?

01:29:25.020 | I don't know.

01:29:26.380 | I don't know the answer to that, but the point is that it shouldn't have been suppressed.

01:29:29.980 | That was, that was election interference.

01:29:31.900 | Now, Elon came out this week and specifically tweeted that, that that was basically a mistake.

01:29:39.100 | Bad call.

01:29:39.980 | Jack also said it was a bad call.

01:29:41.100 | Jack said it was a mistake too.

01:29:42.140 | And Elon repeated the same thing that they shouldn't have done that.

01:29:44.780 | I think everybody can agree it's a bad call in hindsight.

01:29:46.940 | Yeah, of course.

01:29:47.740 | In hindsight.

01:29:49.340 | Right.

01:29:50.140 | But what was the reaction to what Elon said?

01:29:52.300 | He was accused by virtue of criticizing the policy decision that Twitter made,

01:29:58.940 | that that was supposedly targeted harassment of the legal counsel at Twitter who made the decision

01:30:04.540 | who gets paid $17 million a year to make those decisions.

01:30:07.340 | Do you guys see this debate?

01:30:08.300 | This happened last year, this last week.

01:30:10.700 | So the point is that if you criticize somebody who's on a certain side of the debate,

01:30:17.100 | that's harassment, but he'd even mentioned her

01:30:20.060 | by name.

01:30:20.860 | This is how absurd this discourse has gotten.

01:30:23.100 | Can I make a prediction?

01:30:24.220 | Yes.

01:30:25.500 | Prediction's great.

01:30:26.220 | I think people misunderstand Elon's incentives for buying Twitter.

01:30:32.300 | I haven't talked to him about this, so I'm just making a complete subjective prediction.

01:30:37.420 | I think he's going to buy Twitter.

01:30:40.300 | I think he's going to clean it up.

01:30:43.660 | I think he's probably going to generate something like a 2x on this.

01:30:48.460 | We talked about how that's like a 2x.

01:30:49.980 | I think he's going to do something like a good terminal valuation in six or seven years

01:30:53.900 | that basically puts that asset worth at around $100 billion.

01:30:56.940 | In the meantime, he's going to open source as much as possible.

01:31:01.580 | I think he's going to make it very difficult for misinformation and disinformation to get very far.

01:31:06.140 | He said he's going to authenticate every human being that uses the platform.

01:31:10.380 | He said all of these things publicly already.

01:31:12.140 | Then here is the masterstroke, and again, this is just me speculating.

01:31:16.220 | I think he's going to donate it into a foundation and a trust.

01:31:19.900 | I think he's going to do something like a 2x.

01:31:21.580 | I think he's going to do something like a 2x.

01:31:22.940 | I think he's going to do something like a 2x.

01:31:23.980 | I think he's going to do something like a 2x.

01:31:24.940 | I think he's going to do something like a 2x.

01:31:25.980 | I think he's going to do something like a 2x.

01:31:26.940 | I think he's going to do something like a 2x.

01:31:27.980 | I think he's going to do something like a 2x.

01:31:28.940 | I think he's going to do something like a 2x.

01:31:29.980 | I think he's going to do something like a 2x.

01:31:30.940 | I think he's going to do something like a 2x.

01:31:31.980 | I think he's going to do something like a 2x.

01:31:33.020 | I think he's going to do something like a 2x.

01:31:34.060 | I think he's going to do something like a 2x.

01:31:35.020 | I think he's going to do something like a 2x.

01:31:35.980 | I think he's going to do something like a 2x.

01:31:37.020 | I think he's going to do something like a 2x.

01:31:38.060 | I think he's going to do something like a 2x.

01:31:39.020 | I think he's going to do something like a 2x.

01:31:40.060 | I think he's going to do something like a 2x.

01:31:41.100 | I think he's going to do something like a 2x.

01:31:42.140 | I think he's going to do something like a 2x.

01:31:43.180 | I think he's going to do something like a 2x.

01:31:44.300 | I think he's going to do something like a 2x.

01:31:45.420 | I think he's going to do something like a 2x.

01:31:46.540 | I think he's going to do something like a 2x.

01:31:47.660 | I think he's going to do something like a 2x.

01:31:48.780 | I think he's going to do something like a 2x.

01:31:50.060 | I think he's going to do something like a 2x.

01:31:52.060 | I think he's going to do something like a 2x.

01:31:54.060 | I think he's going to do something like a 2x.

01:31:56.060 | I think he's going to do something like a 2x.

01:31:58.060 | I think he's going to do something like a 2x.

01:32:00.060 | I think he's going to do something like a 2x.

01:32:02.060 | I think he's going to do something like a 2x.

01:32:04.060 | I think he's going to do something like a 2x.

01:32:06.060 | I think he's going to do something like a 2x.

01:32:08.060 | I think he's going to do something like a 2x.

01:32:10.060 | I think he's going to do something like a 2x.

01:32:12.060 | I think he's going to do something like a 2x.

01:32:14.060 | I think he's going to do something like a 2x.

01:32:16.060 | I think he's going to do something like a 2x.

01:32:18.060 | I think he's going to do something like a 2x.

01:32:20.060 | I think he's going to do something like a 2x.

01:32:22.060 | I think he's going to do something like a 2x.

01:32:24.060 | I think he's going to do something like a 2x.

01:32:26.060 | I think he's going to do something like a 2x.

01:32:28.060 | I think he's going to do something like a 2x.

01:32:30.060 | I think he's going to do something like a 2x.

01:32:32.060 | I think he's going to do something like a 2x.

01:32:34.060 | I think he's going to do something like a 2x.

01:32:36.060 | I think he's going to do something like a 2x.

01:32:38.060 | I think he's going to do something like a 2x.

01:32:40.060 | I think he's going to do something like a 2x.

01:32:42.060 | I think he's going to do something like a 2x.

01:32:44.060 | I think he's going to do something like a 2x.

01:32:46.060 | I think he's going to do something like a 2x.

01:32:48.060 | I think he's going to do something like a 2x.

01:32:50.060 | I think he's going to do something like a 2x.

01:32:52.060 | I think he's going to do something like a 2x.

01:32:54.060 | I think he's going to do something like a 2x.

01:32:56.060 | I think he's going to do something like a 2x.

01:32:58.060 | I think he's going to do something like a 2x.

01:33:00.060 | I think he's going to do something like a 2x.

01:33:02.060 | I think he's going to do something like a 2x.

01:33:04.060 | I think he's going to do something like a 2x.

01:33:06.060 | I think he's going to do something like a 2x.

01:33:08.060 | I think he's going to do something like a 2x.

01:33:10.060 | I think he's going to do something like a 2x.

01:33:12.060 | I think he's going to do something like a 2x.

01:33:14.060 | I think he's going to do something like a 2x.

01:33:16.060 | I think he's going to do something like a 2x.

01:33:18.060 | I think he's going to do something like a 2x.

01:33:20.060 | I think he's going to do something like a 2x.

01:33:22.060 | I think he's going to do something like a 2x.

01:33:24.060 | I think he's going to do something like a 2x.

01:33:26.060 | I think he's going to do something like a 2x.

01:33:28.060 | I think he's going to do something like a 2x.

01:33:30.060 | I think he's going to do something like a 2x.

01:33:32.060 | I think he's going to do something like a 2x.

01:33:34.060 | I think he's going to do something like a 2x.

01:33:36.060 | I think he's going to do something like a 2x.

01:33:38.060 | I think he's going to do something like a 2x.

01:33:40.060 | I think he's going to do something like a 2x.

01:33:42.060 | I think he's going to do something like a 2x.

01:33:44.060 | I think he's going to do something like a 2x.

01:33:46.060 | I think he's going to do something like a 2x.

01:33:48.060 | I think he's going to do something like a 2x.

01:33:50.060 | I think he's going to do something like a 2x.

01:33:52.060 | I think he's going to do something like a 2x.

01:33:54.060 | I think he's going to do something like a 2x.

01:33:56.060 | I think he's going to do something like a 2x.

01:33:58.060 | I think he's going to do something like a 2x.

01:34:00.060 | I think he's going to do something like a 2x.

01:34:02.060 | I think he's going to do something like a 2x.

01:34:04.060 | I think he's going to do something like a 2x.

01:34:06.060 | I think he's going to do something like a 2x.

01:34:08.060 | I think he's going to do something like a 2x.

01:34:10.060 | I think he's going to do something like a 2x.

01:34:12.060 | I think he's going to do something like a 2x.

01:34:14.060 | I think he's going to do something like a 2x.

01:34:16.060 | I think he's going to do something like a 2x.

01:34:18.060 | I think he's going to do something like a 2x.

01:34:20.060 | I think he's going to do something like a 2x.

01:34:22.060 | I think he's going to do something like a 2x.

01:34:24.060 | I think he's going to do something like a 2x.

01:34:26.060 | I think he's going to do something like a 2x.

01:34:28.060 | I think he's going to do something like a 2x.

01:34:30.060 | I think he's going to do something like a 2x.

01:34:32.060 | I think he's going to do something like a 2x.

01:34:34.060 | I think he's going to do something like a 2x.

01:34:36.060 | I think he's going to do something like a 2x.

01:34:38.060 | I think he's going to do something like a 2x.

01:34:40.060 | I think he's going to do something like a 2x.

01:34:42.060 | I think he's going to do something like a 2x.

01:34:44.060 | I think he's going to do something like a 2x.

01:34:46.060 | I think he's going to do something like a 2x.

01:34:48.060 | I think he's going to do something like a 2x.

01:34:50.060 | I think he's going to do something like a 2x.

01:34:52.060 | I think he's going to do something like a 2x.

01:34:54.060 | I think he's going to do something like a 2x.

01:34:56.060 | I think he's going to do something like a 2x.

01:34:58.060 | I think he's going to do something like a 2x.

01:35:00.060 | I think he's going to do something like a 2x.

01:35:02.060 | I think he's going to do something like a 2x.

01:35:04.060 | I think he's going to do something like a 2x.

01:35:06.060 | I think he's going to do something like a 2x.

01:35:08.060 | I think he's going to do something like a 2x.

01:35:10.060 | I think he's going to do something like a 2x.

01:35:12.060 | I think he's going to do something like a 2x.

01:35:14.060 | I think he's going to do something like a 2x.

01:35:16.060 | I think he's going to do something like a 2x.

01:35:18.060 | I think he's going to do something like a 2x.

01:35:20.060 | I think he's going to do something like a 2x.

01:35:22.060 | I think he's going to do something like a 2x.

01:35:24.060 | I think he's going to do something like a 2x.

01:35:26.060 | I think he's going to do something like a 2x.

01:35:28.060 | I think he's going to do something like a 2x.

01:35:30.060 | I think he's going to do something like a 2x.

01:35:32.060 | I think he's going to do something like a 2x.

01:35:34.060 | I think he's going to do something like a 2x.

01:35:36.060 | I think he's going to do something like a 2x.

01:35:38.060 | I think he's going to do something like a 2x.

01:35:40.060 | I think he's going to do something like a 2x.

01:35:42.060 | I think he's going to do something like a 2x.

01:35:44.060 | I think he's going to do something like a 2x.

01:35:46.060 | I think he's going to do something like a 2x.

01:35:48.060 | I think he's going to do something like a 2x.

01:35:50.060 | I think he's going to do something like a 2x.

01:35:52.060 | I think he's going to do something like a 2x.

01:35:54.060 | I think he's going to do something like a 2x.

01:35:56.060 | I think he's going to do something like a 2x.

01:35:58.060 | I think he's going to do something like a 2x.

01:36:00.060 | I think he's going to do something like a 2x.

01:36:02.060 | I think he's going to do something like a 2x.

01:36:04.060 | I think he's going to do something like a 2x.

01:36:06.060 | I think he's going to do something like a 2x.

01:36:08.060 | I think he's going to do something like a 2x.

01:36:10.060 | I think he's going to do something like a 2x.

01:36:12.060 | I think he's going to do something like a 2x.

01:36:14.060 | I think he's going to do something like a 2x.

01:36:16.060 | I think he's going to do something like a 2x.

01:36:18.060 | I think he's going to do something like a 2x.

01:36:20.060 | I think he's going to do something like a 2x.

01:36:22.060 | I think he's going to do something like a 2x.

01:36:24.060 | I think he's going to do something like a 2x.

01:36:26.060 | I think he's going to do something like a 2x.

01:36:28.060 | I think he's going to do something like a 2x.

01:36:30.060 | I think he's going to do something like a 2x.

01:36:32.060 | I think he's going to do something like a 2x.

01:36:34.060 | I think he's going to do something like a 2x.

01:36:36.060 | I think he's going to do something like a 2x.

01:36:38.060 | I think he's going to do something like a 2x.

01:36:40.060 | I think he's going to do something like a 2x.

01:36:42.060 | I think he's going to do something like a 2x.

01:36:44.060 | I think he's going to do something like a 2x.

01:36:46.060 | I think he's going to do something like a 2x.

01:36:48.060 | I think he's going to do something like a 2x.

01:36:50.060 | I think he's going to do something like a 2x.

01:36:52.060 | I think he's going to do something like a 2x.

01:36:54.060 | I think he's going to do something like a 2x.

01:36:56.060 | I think he's going to do something like a 2x.

01:36:58.060 | I think he's going to do something like a 2x.

01:37:00.060 | I think he's going to do something like a 2x.

01:37:02.060 | I think he's going to do something like a 2x.

01:37:04.060 | I think he's going to do something like a 2x.

01:37:06.060 | I think he's going to do something like a 2x.

01:37:08.060 | I think he's going to do something like a 2x.

01:37:10.060 | I think he's going to do something like a 2x.

01:37:12.060 | I think he's going to do something like a 2x.

01:37:14.060 | I think he's going to do something like a 2x.

01:37:16.060 | I think he's going to do something like a 2x.

01:37:18.060 | I think he's going to do something like a 2x.

01:37:20.060 | I think he's going to do something like a 2x.

01:37:22.060 | I think he's going to do something like a 2x.

01:37:24.060 | I think he's going to do something like a 2x.

01:37:26.060 | I think he's going to do something like a 2x.

01:37:28.060 | I think he's going to do something like a 2x.

01:37:30.060 | I think he's going to do something like a 2x.

01:37:32.060 | I think he's going to do something like a 2x.

01:37:34.060 | I think he's going to do something like a 2x.

01:37:36.060 | I think he's going to do something like a 2x.

01:37:38.060 | I think he's going to do something like a 2x.

01:37:40.060 | I think he's going to do something like a 2x.

01:37:42.060 | I think he's going to do something like a 2x.

01:37:44.060 | I think he's going to do something like a 2x.

01:37:46.060 | I think he's going to do something like a 2x.

01:37:48.060 | I think he's going to do something like a 2x.

01:37:50.060 | I think he's going to do something like a 2x.

01:37:52.060 | I think he's going to do something like a 2x.

01:37:54.060 | I think he's going to do something like a 2x.

01:37:56.060 | I think he's going to do something like a 2x.

01:37:58.060 | I think he's going to do something like a 2x.

01:38:00.060 | I think he's going to do something like a 2x.

01:38:02.060 | I think he's going to do something like a 2x.

01:38:04.060 | I think he's going to do something like a 2x.

01:38:06.060 | I think he's going to do something like a 2x.

01:38:08.060 | I think he's going to do something like a 2x.

01:38:10.060 | I think he's going to do something like a 2x.

01:38:12.060 | I think he's going to do something like a 2x.

01:38:14.060 | I think he's going to do something like a 2x.

01:38:16.060 | I think he's going to do something like a 2x.

01:38:18.060 | I think he's going to do something like a 2x.

01:38:20.060 | I think he's going to do something like a 2x.

01:38:22.060 | I think he's going to do something like a 2x.

01:38:24.060 | I think he's going to do something like a 2x.

01:38:26.060 | I think he's going to do something like a 2x.

01:38:28.060 | I think he's going to do something like a 2x.

01:38:30.060 | I think he's going to do something like a 2x.

01:38:32.060 | I think he's going to do something like a 2x.

01:38:34.060 | I think he's going to do something like a 2x.

01:38:36.060 | I think he's going to do something like a 2x.

01:38:38.060 | I think he's going to do something like a 2x.

01:38:40.060 | I think he's going to do something like a 2x.

01:38:42.060 | I think he's going to do something like a 2x.

01:38:44.060 | I think he's going to do something like a 2x.

01:38:46.060 | I think he's going to do something like a 2x.

01:38:48.060 | I think he's going to do something like a 2x.

01:38:50.060 | I think he's going to do something like a 2x.

01:38:52.060 | I think he's going to do something like a 2x.

01:38:54.060 | I think he's going to do something like a 2x.

01:38:56.060 | I think he's going to do something like a 2x.

01:38:58.060 | I think he's going to do something like a 2x.

01:39:00.060 | I think he's going to do something like a 2x.

01:39:02.060 | I think he's going to do something like a 2x.

01:39:04.060 | I think he's going to do something like a 2x.

01:39:06.060 | I think he's going to do something like a 2x.

01:39:08.060 | I think he's going to do something like a 2x.

01:39:10.060 | I think he's going to do something like a 2x.

01:39:12.060 | I think he's going to do something like a 2x.

01:39:14.060 | I think he's going to do something like a 2x.

01:39:16.060 | I think he's going to do something like a 2x.

01:39:18.060 | I think he's going to do something like a 2x.

01:39:20.060 | I think he's going to do something like a 2x.

01:39:22.060 | I think he's going to do something like a 2x.

01:39:24.060 | I think he's going to do something like a 2x.

01:39:26.060 | I think he's going to do something like a 2x.

01:39:28.060 | I think he's going to do something like a 2x.

01:39:30.060 | I think he's going to do something like a 2x.

01:39:32.060 | I think he's going to do something like a 2x.

01:39:34.060 | I think he's going to do something like a 2x.

01:39:36.060 | I think he's going to do something like a 2x.

01:39:38.060 | I think he's going to do something like a 2x.

01:39:40.060 | I think he's going to do something like a 2x.

01:39:42.060 | I think he's going to do something like a 2x.

01:39:44.060 | I think he's going to do something like a 2x.

01:39:46.060 | I think he's going to do something like a 2x.

01:39:48.060 | I think he's going to do something like a 2x.

01:39:50.060 | I think he's going to do something like a 2x.

01:39:52.060 | I think he's going to do something like a 2x.

01:39:54.060 | I think he's going to do something like a 2x.

01:39:56.060 | I think he's going to do something like a 2x.

01:39:58.060 | I think he's going to do something like a 2x.

01:40:00.060 | I think he's going to do something like a 2x.

01:40:02.060 | I think he's going to do something like a 2x.

01:40:04.060 | I think he's going to do something like a 2x.

01:40:06.060 | I think he's going to do something like a 2x.

01:40:08.060 | I think he's going to do something like a 2x.

01:40:10.060 | I think he's going to do something like a 2x.

01:40:12.060 | I think he's going to do something like a 2x.

01:40:14.060 | I think he's going to do something like a 2x.

01:40:16.060 | I think he's going to do something like a 2x.

01:40:18.060 | I think he's going to do something like a 2x.

01:40:20.060 | I think he's going to do something like a 2x.

01:40:22.060 | I think he's going to do something like a 2x.

01:40:24.060 | I think he's going to do something like a 2x.

01:40:26.060 | I think he's going to do something like a 2x.

01:40:28.060 | I think he's going to do something like a 2x.

01:40:30.060 | I think he's going to do something like a 2x.

01:40:32.060 | I think he's going to do something like a 2x.

01:40:34.060 | I think he's going to do something like a 2x.

01:40:36.060 | I think he's going to do something like a 2x.

01:40:38.060 | I think he's going to do something like a 2x.

01:40:40.060 | I think he's going to do something like a 2x.

01:40:42.060 | I think he's going to do something like a 2x.

01:40:44.060 | I think he's going to do something like a 2x.

01:40:46.060 | I think he's going to do something like a 2x.

01:40:48.060 | I think he's going to do something like a 2x.

01:40:50.060 | I think he's going to do something like a 2x.

01:40:52.060 | I think he's going to do something like a 2x.

01:40:54.060 | I think he's going to do something like a 2x.

01:40:56.060 | I think he's going to do something like a 2x.

01:40:58.060 | I think he's going to do something like a 2x.

01:41:00.060 | I think he's going to do something like a 2x.

01:41:02.060 | I think he's going to do something like a 2x.

01:41:04.060 | I think he's going to do something like a 2x.

01:41:06.060 | I think he's going to do something like a 2x.

01:41:08.060 | I think he's going to do something like a 2x.

01:41:10.060 | I think he's going to do something like a 2x.

01:41:12.060 | I think he's going to do something like a 2x.

01:41:14.060 | I think he's going to do something like a 2x.

01:41:16.060 | I think he's going to do something like a 2x.

01:41:18.060 | I think he's going to do something like a 2x.

01:41:20.060 | I think he's going to do something like a 2x.

01:41:22.060 | I think he's going to do something like a 2x.

01:41:24.060 | I think he's going to do something like a 2x.

01:41:26.060 | I think he's going to do something like a 2x.

01:41:28.060 | I think he's going to do something like a 2x.

01:41:30.060 | I think he's going to do something like a 2x.

01:41:32.060 | I think he's going to do something like a 2x.

01:41:34.060 | I think he's going to do something like a 2x.

01:41:36.060 | I think he's going to do something like a 2x.

01:41:38.060 | I think he's going to do something like a 2x.

01:41:40.060 | I think he's going to do something like a 2x.

01:41:42.060 | I think he's going to do something like a 2x.

01:41:44.060 | I think he's going to do something like a 2x.

01:41:46.060 | I think he's going to do something like a 2x.

01:41:48.060 | I think he's going to do something like a 2x.

01:41:50.060 | I think he's going to do something like a 2x.

01:41:52.060 | I think he's going to do something like a 2x.

01:41:54.060 | I think he's going to do something like a 2x.

01:41:56.060 | I think he's going to do something like a 2x.

01:41:58.060 | I think he's going to do something like a 2x.

01:42:00.060 | I think he's going to do something like a 2x.

01:42:02.060 | I think he's going to do something like a 2x.

01:42:04.060 | I think he's going to do something like a 2x.

01:42:06.060 | I think he's going to do something like a 2x.

01:42:08.060 | I think he's going to do something like a 2x.

01:42:10.060 | I think he's going to do something like a 2x.

01:42:12.060 | I think he's going to do something like a 2x.

01:42:14.060 | I think he's going to do something like a 2x.

01:42:16.060 | I think he's going to do something like a 2x.

01:42:18.060 | I think he's going to do something like a 2x.

01:42:20.060 | I think he's going to do something like a 2x.

01:42:22.060 | I think he's going to do something like a 2x.

01:42:24.060 | I think he's going to do something like a 2x.

01:42:26.060 | I think he's going to do something like a 2x.

01:42:28.060 | I think he's going to do something like a 2x.

01:42:30.060 | I think he's going to do something like a 2x.

01:42:32.060 | I think he's going to do something like a 2x.

01:42:34.060 | I think he's going to do something like a 2x.

01:42:36.060 | I think he's going to do something like a 2x.

01:42:38.060 | I think he's going to do something like a 2x.

01:42:40.060 | I think he's going to do something like a 2x.

01:42:42.060 | I think he's going to do something like a 2x.

01:42:44.060 | I think he's going to do something like a 2x.

01:42:46.060 | I think he's going to do something like a 2x.

01:42:48.060 | I think he's going to do something like a 2x.

01:42:50.060 | I think he's going to do something like a 2x.

01:42:52.060 | I think he's going to do something like a 2x.

01:42:54.060 | I think he's going to do something like a 2x.

01:42:56.060 | I think he's going to do something like a 2x.

01:42:58.060 | I think he's going to do something like a 2x.

01:43:00.060 | I think he's going to do something like a 2x.

01:43:02.060 | I think he's going to do something like a 2x.

01:43:04.060 | I think he's going to do something like a 2x.

01:43:06.060 | I think he's going to do something like a 2x.

01:43:08.060 | I think he's going to do something like a 2x.

01:43:10.060 | I think he's going to do something like a 2x.

01:43:12.060 | I think he's going to do something like a 2x.

01:43:14.060 | I think he's going to do something like a 2x.

01:43:16.060 | I think he's going to do something like a 2x.

01:43:18.060 | I think he's going to do something like a 2x.

01:43:20.060 | I think he's going to do something like a 2x.

01:43:22.060 | I think he's going to do something like a 2x.

01:43:24.060 | I think he's going to do something like a 2x.

01:43:26.060 | I think he's going to do something like a 2x.

01:43:28.060 | I think he's going to do something like a 2x.

01:43:30.060 | I think he's going to do something like a 2x.

01:43:32.060 | I think he's going to do something like a 2x.

01:43:34.060 | I think he's going to do something like a 2x.

01:43:36.060 | I think he's going to do something like a 2x.

01:43:38.060 | I think he's going to do something like a 2x.

01:43:40.060 | I think he's going to do something like a 2x.

01:43:42.060 | I think he's going to do something like a 2x.

01:43:44.060 | I think he's going to do something like a 2x.

01:43:46.060 | I think he's going to do something like a 2x.

01:43:48.060 | I think he's going to do something like a 2x.

01:43:50.060 | I think he's going to do something like a 2x.

01:43:52.060 | I think he's going to do something like a 2x.

01:43:54.060 | I think he's going to do something like a 2x.

01:43:56.060 | I think he's going to do something like a 2x.

01:43:58.060 | I think he's going to do something like a 2x.

01:44:00.060 | I think he's going to do something like a 2x.

01:44:02.060 | I think he's going to do something like a 2x.

01:44:04.060 | I think he's going to do something like a 2x.

01:44:06.060 | I think he's going to do something like a 2x.

01:44:08.060 | I think he's going to do something like a 2x.

01:44:10.060 | I think he's going to do something like a 2x.

01:44:12.060 | I think he's going to do something like a 2x.

01:44:14.060 | I think he's going to do something like a 2x.

01:44:16.060 | I think he's going to do something like a 2x.

01:44:18.060 | I think he's going to do something like a 2x.

01:44:20.060 | I think he's going to do something like a 2x.

01:44:22.060 | I think he's going to do something like a 2x.

01:44:24.060 | I think he's going to do something like a 2x.

01:44:26.060 | I think he's going to do something like a 2x.

01:44:28.060 | I think he's going to do something like a 2x.

01:44:30.060 | I think he's going to do something like a 2x.

01:44:32.060 | I think he's going to do something like a 2x.

01:44:34.060 | I think he's going to do something like a 2x.

01:44:36.060 | I think he's going to do something like a 2x.

01:44:38.060 | I think he's going to do something like a 2x.

01:44:40.060 | I think he's going to do something like a 2x.

01:44:42.060 | I think he's going to do something like a 2x.

01:44:44.060 | I think he's going to do something like a 2x.

01:44:46.060 | I think he's going to do something like a 2x.

01:44:48.060 | I think he's going to do something like a 2x.

01:44:50.060 | I think he's going to do something like a 2x.

01:44:52.060 | I think he's going to do something like a 2x.

01:44:54.060 | I think he's going to do something like a 2x.

01:44:56.060 | I think he's going to do something like a 2x.

01:44:58.060 | I think he's going to do something like a 2x.

01:45:00.060 | I think he's going to do something like a 2x.

01:45:02.060 | I think he's going to do something like a 2x.

01:45:04.060 | I think he's going to do something like a 2x.

01:45:06.060 | I think he's going to do something like a 2x.

01:45:08.060 | I think he's going to do something like a 2x.

01:45:10.060 | I think he's going to do something like a 2x.

01:45:12.060 | I think he's going to do something like a 2x.

01:45:14.060 | I think he's going to do something like a 2x.

01:45:16.060 | I think he's going to do something like a 2x.

01:45:18.060 | I think he's going to do something like a 2x.

01:45:20.060 | I think he's going to do something like a 2x.

01:45:22.060 | I think he's going to do something like a 2x.

01:45:24.060 | I think he's going to do something like a 2x.

01:45:26.060 | I think he's going to do something like a 2x.

01:45:28.060 | I think he's going to do something like a 2x.

01:45:30.060 | I think he's going to do something like a 2x.

01:45:32.060 | I think he's going to do something like a 2x.

01:45:34.060 | I think he's going to do something like a 2x.

01:45:36.060 | I think he's going to do something like a 2x.

01:45:38.060 | I think he's going to do something like a 2x.

01:45:40.060 | I think he's going to do something like a 2x.

01:45:42.060 | I think he's going to do something like a 2x.

01:45:44.060 | I think he's going to do something like a 2x.

01:45:46.060 | I think he's going to do something like a 2x.

01:45:48.060 | I think he's going to do something like a 2x.

01:45:50.060 | I think he's going to do something like a 2x.

01:45:52.060 | I think he's going to do something like a 2x.

01:45:54.060 | I think he's going to do something like a 2x.

01:45:56.060 | I think he's going to do something like a 2x.

01:45:58.060 | I think he's going to do something like a 2x.

01:46:00.060 | I think he's going to do something like a 2x.

01:46:02.060 | I think he's going to do something like a 2x.

01:46:04.060 | I think he's going to do something like a 2x.

01:46:06.060 | I think he's going to do something like a 2x.

01:46:08.060 | I think he's going to do something like a 2x.

01:46:10.060 | I think he's going to do something like a 2x.

01:46:12.060 | I think he's going to do something like a 2x.

01:46:14.060 | I think he's going to do something like a 2x.

01:46:16.060 | I think he's going to do something like a 2x.

01:46:18.060 | I think he's going to do something like a 2x.

01:46:20.060 | I think he's going to do something like a 2x.

01:46:22.060 | I think he's going to do something like a 2x.

01:46:24.060 | I think he's going to do something like a 2x.

01:46:26.060 | I think he's going to do something like a 2x.

01:46:28.060 | I think he's going to do something like a 2x.

01:46:30.060 | I think he's going to do something like a 2x.

01:46:32.060 | I think he's going to do something like a 2x.

01:46:34.060 | I think he's going to do something like a 2x.

01:46:36.060 | I think he's going to do something like a 2x.

01:46:38.060 | I think he's going to do something like a 2x.

01:46:40.060 | I think he's going to do something like a 2x.

01:46:42.060 | I think he's going to do something like a 2x.

01:46:44.060 | I think he's going to do something like a 2x.

01:46:46.060 | I think he's going to do something like a 2x.

01:46:48.060 | I think he's going to do something like a 2x.

01:46:50.060 | I think he's going to do something like a 2x.

01:46:52.060 | I think he's going to do something like a 2x.

01:46:54.060 | I think he's going to do something like a 2x.

01:46:56.060 | I think he's going to do something like a 2x.

01:46:58.060 | I think he's going to do something like a 2x.

01:47:00.060 | I think he's going to do something like a 2x.

01:47:02.060 | I think he's going to do something like a 2x.

01:47:04.060 | I think he's going to do something like a 2x.

01:47:06.060 | I think he's going to do something like a 2x.

01:47:08.060 | I think he's going to do something like a 2x.

01:47:10.060 | I think he's going to do something like a 2x.

01:47:12.060 | I think he's going to do something like a 2x.

01:47:14.060 | I think he's going to do something like a 2x.

01:47:16.060 | I think he's going to do something like a 2x.

01:47:18.060 | I think he's going to do something like a 2x.

01:47:20.060 | I think he's going to do something like a 2x.

01:47:22.060 | I think he's going to do something like a 2x.

01:47:24.060 | I think he's going to do something like a 2x.

01:47:26.060 | I think he's going to do something like a 2x.

01:47:28.060 | I think he's going to do something like a 2x.

01:47:30.060 | I think he's going to do something like a 2x.

01:47:32.060 | I think he's going to do something like a 2x.

01:47:34.060 | I think he's going to do something like a 2x.

01:47:36.060 | I think he's going to do something like a 2x.

01:47:38.060 | I think he's going to do something like a 2x.

01:47:40.060 | I think he's going to do something like a 2x.

01:47:42.060 | I think he's going to do something like a 2x.

01:47:44.060 | I think he's going to do something like a 2x.

01:47:46.060 | I think he's going to do something like a 2x.

01:47:48.060 | I think he's going to do something like a 2x.

01:47:50.060 | I think he's going to do something like a 2x.

01:47:52.060 | I think he's going to do something like a 2x.

01:47:54.060 | I think he's going to do something like a 2x.

01:47:56.060 | I think he's going to do something like a 2x.

01:47:58.060 | I think he's going to do something like a 2x.

01:48:00.060 | I think he's going to do something like a 2x.

01:48:02.060 | I think he's going to do something like a 2x.

01:48:04.060 | I think he's going to do something like a 2x.

01:48:06.060 | I think he's going to do something like a 2x.

01:48:08.060 | I think he's going to do something like a 2x.

01:48:10.060 | I think he's going to do something like a 2x.

01:48:12.060 | I think he's going to do something like a 2x.

01:48:14.060 | I think he's going to do something like a 2x.

01:48:16.060 | I think he's going to do something like a 2x.

01:48:18.060 | I think he's going to do something like a 2x.

01:48:20.060 | I think he's going to do something like a 2x.

01:48:22.060 | I think he's going to do something like a 2x.

01:48:24.060 | I think he's going to do something like a 2x.

01:48:26.060 | I think he's going to do something like a 2x.

01:48:28.060 | I think he's going to do something like a 2x.

01:48:30.060 | I think he's going to do something like a 2x.

01:48:32.060 | I think he's going to do something like a 2x.

01:48:34.060 | I think he's going to do something like a 2x.

01:48:36.060 | I think he's going to do something like a 2x.

01:48:38.060 | I think he's going to do something like a 2x.

01:48:40.060 | I think he's going to do something like a 2x.

01:48:42.060 | I think he's going to do something like a 2x.

01:48:44.060 | I think he's going to do something like a 2x.

01:48:46.060 | I think he's going to do something like a 2x.

01:48:48.060 | I think he's going to do something like a 2x.

01:48:50.060 | I think he's going to do something like a 2x.

01:48:52.060 | I think he's going to do something like a 2x.

01:48:54.060 | I think he's going to do something like a 2x.

01:48:56.060 | I think he's going to do something like a 2x.

01:48:58.060 | I think he's going to do something like a 2x.

01:49:00.060 | I think he's going to do something like a 2x.

01:49:02.060 | I think he's going to do something like a 2x.

01:49:04.060 | I think he's going to do something like a 2x.

01:49:06.060 | I think he's going to do something like a 2x.

01:49:08.060 | I think he's going to do something like a 2x.

01:49:10.060 | I think he's going to do something like a 2x.

01:49:12.060 | I think he's going to do something like a 2x.

01:49:14.060 | I think he's going to do something like a 2x.

01:49:16.060 | I think he's going to do something like a 2x.

01:49:18.060 | I think he's going to do something like a 2x.

01:49:20.060 | I think he's going to do something like a 2x.

01:49:22.060 | I think he's going to do something like a 2x.

01:49:24.060 | I think he's going to do something like a 2x.

01:49:26.060 | I think he's going to do something like a 2x.

01:49:28.060 | I think he's going to do something like a 2x.

01:49:30.060 | I think he's going to do something like a 2x.

01:49:32.060 | I think he's going to do something like a 2x.

01:49:34.060 | I think he's going to do something like a 2x.

01:49:36.060 | I think he's going to do something like a 2x.

01:49:38.060 | I think he's going to do something like a 2x.

01:49:40.060 | I think he's going to do something like a 2x.

01:49:42.060 | I think he's going to do something like a 2x.

01:49:44.060 | I think he's going to do something like a 2x.

01:49:46.060 | I think he's going to do something like a 2x.

01:49:48.060 | I think he's going to do something like a 2x.

01:49:50.060 | I think he's going to do something like a 2x.

01:49:52.060 | I think he's going to do something like a 2x.

01:49:54.060 | I think he's going to do something like a 2x.

01:49:56.060 | I think he's going to do something like a 2x.

01:49:58.060 | I think he's going to do something like a 2x.

01:50:00.060 | I think he's going to do something like a 2x.

01:50:02.060 | I think he's going to do something like a 2x.

01:50:04.060 | I think he's going to do something like a 2x.

01:50:06.060 | I think he's going to do something like a 2x.

01:50:08.060 | I think he's going to do something like a 2x.

01:50:10.060 | I think he's going to do something like a 2x.

01:50:12.060 | I think he's going to do something like a 2x.

01:50:14.060 | I think he's going to do something like a 2x.

01:50:16.060 | I think he's going to do something like a 2x.

01:50:18.060 | I think he's going to do something like a 2x.

01:50:20.060 | I think he's going to do something like a 2x.

01:50:22.060 | I think he's going to do something like a 2x.

01:50:24.060 | I think he's going to do something like a 2x.

01:50:26.060 | I think he's going to do something like a 2x.

01:50:28.060 | I think he's going to do something like a 2x.

01:50:30.060 | I think he's going to do something like a 2x.

01:50:32.060 | I think he's going to do something like a 2x.

01:50:34.060 | I think he's going to do something like a 2x.

01:50:36.060 | I think he's going to do something like a 2x.

01:50:38.060 | I think he's going to do something like a 2x.

01:50:40.060 | I think he's going to do something like a 2x.

01:50:42.060 | I think he's going to do something like a 2x.

01:50:44.060 | I think he's going to do something like a 2x.

01:50:46.060 | I think he's going to do something like a 2x.

01:50:48.060 | I think he's going to do something like a 2x.

01:50:50.060 | I think he's going to do something like a 2x.

01:50:52.060 | I think he's going to do something like a 2x.

01:50:54.060 | I think he's going to do something like a 2x.

01:50:56.060 | I think he's going to do something like a 2x.

01:50:58.060 | I think he's going to do something like a 2x.

01:51:00.060 | I think he's going to do something like a 2x.

01:51:02.060 | I think he's going to do something like a 2x.

01:51:04.060 | I think he's going to do something like a 2x.

01:51:06.060 | I think he's going to do something like a 2x.

01:51:08.060 | I think he's going to do something like a 2x.

01:51:10.060 | I think he's going to do something like a 2x.

01:51:12.060 | I think he's going to do something like a 2x.

01:51:14.060 | I think he's going to do something like a 2x.

01:51:16.060 | I think he's going to do something like a 2x.

01:51:18.060 | I think he's going to do something like a 2x.

01:51:20.060 | I think he's going to do something like a 2x.

01:51:22.060 | I think he's going to do something like a 2x.

01:51:24.060 | I think he's going to do something like a 2x.

01:51:26.060 | I think he's going to do something like a 2x.

01:51:28.060 | I think he's going to do something like a 2x.

01:51:30.060 | I think he's going to do something like a 2x.

01:51:32.060 | I think he's going to do something like a 2x.

01:51:34.060 | I think he's going to do something like a 2x.

01:51:36.060 | I think he's going to do something like a 2x.

01:51:38.060 | I think he's going to do something like a 2x.

E78: VC fund metrics that matter, private market update, recession, student loans, Bill Hwang arrest

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