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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Masters in

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Speaker 1: Business with Barry Ritholts on Bloomberg Radio.

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Speaker 2: This week on the podcast What a delight extra special

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Speaker 2: guest Jim O'Shaughnessy. His book that I came to know

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Speaker 2: him with first was What Works on Wall Street, which

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Speaker 2: has been just a perennial seller. I think it's in

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Speaker 2: its fourth or its sixth edition and really influenced several

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Speaker 2: generations of quants. On finance, O'Shaughnessey Asset Management became a

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Speaker 2: leader indirect indexing eventually was bought by Franklin Templeton, leading

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Speaker 2: him to launch O'Shaughnessy Ventures, O'Shaughnessy Fellowships, Infinite Loops podcast,

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Speaker 2: just so many different things. New book is delightfully titled

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Speaker 2: Two Thoughts, a timeless collection of infinite wisdom, and reflects

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Speaker 2: many of the insights and just thoughtfulness that Jim shows

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Speaker 2: in everything he does. I always find it delightful to

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Speaker 2: have him on the show, and you can tell how

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Speaker 2: much I appreciate him just by the conversation meanders wherever

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Speaker 2: it goes, and I occasionally look at my list of questions,

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Speaker 2: but really I just want to see where Jim's mind

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Speaker 2: is going to take it and come along for the ride.

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Speaker 2: I thought this was delightful and I think you will

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Speaker 2: also with no further ado my conversation with Jim O'Shaughnessy Barry.

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Speaker 3: I am always looking forward to these conversations. That's great

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Speaker 3: to be back.

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Speaker 2: It's a pleasure for me. Also, you and I.

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Speaker 3: Go way back, way way back.

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Speaker 2: And it's kind of funny, Like twenty five years later,

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Speaker 2: I was like, oh, how do you know Jim. Oh,

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Speaker 2: we met in the green room of TV, you know,

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Speaker 2: right after the dot com crash. It was kind of

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Speaker 2: it was kind of funny. But let's talk a little

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Speaker 2: bit about all the different businesses and ventures that you're

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Speaker 2: you're involved with. So I knew you right around the

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Speaker 2: time you were getting ready to depart bear Sterns. You

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Speaker 2: at bear Stearns for like.

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Speaker 3: A decade or so, no, about five and a half years.

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Speaker 2: Okay, so the in the mid two thousands, and you

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Speaker 2: had the great insight and business acumen to tap out

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Speaker 2: of bear Sterns in two thousand and seven with all

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Speaker 2: of those options that you had and exercise the option

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Speaker 2: sell them and launch your showing. Essy asset management. So

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Speaker 2: you went on the way out, you went on the

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Speaker 2: way into starting the new firm. Tell us a little

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Speaker 2: bit about the early days leaving bear Stearns and setting

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Speaker 2: up OSAM.

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Speaker 3: So first, let me correct everyone assumes that I saw

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Speaker 3: the Great financial crisis coming and therefore wanted to spin

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Speaker 3: out of bear Stearns. Yeah, what do they say if

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Speaker 3: the story conflicts with the legend, print the legend. The

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Speaker 3: legend really isn't correct. Though, we had begun conversations with

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Speaker 3: bear Stearns folks months and months before the financial crisis

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Speaker 3: came on the scene, and it was essentially a very

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Speaker 3: amicable parting. As you note, when we spun out, we

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Speaker 3: kept all of our bear Stearns accounts, continued to work

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Speaker 3: with all their private client service people over there, So

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Speaker 3: it was very very amicable. But of course, because the

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Speaker 3: Great financial crisis came along and bear had those CDO

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Speaker 3: funds that had a little bit of a problem. Was

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Speaker 3: it was just irresistible for Newspece people to say. I

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Speaker 3: had one reporter sit with me for an hour and

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Speaker 3: a half and all she kept doing was, come on,

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Speaker 3: tell me the truth, tell me the truth, tell me

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Speaker 3: the truth.

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Speaker 2: You know, It's funny because when we look at certain

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Speaker 2: books that get the timing of things right or completely wrong.

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Speaker 2: People forget a book just doesn't appear wholesale out of

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Speaker 2: thin cloth. It's the idea has to come along, and

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Speaker 2: then then you got to get a publisher that wants

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Speaker 2: and unless you're gonna self publish, then you got to

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Speaker 2: write it so that it's like a one or two

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Speaker 2: year lag. I would imagine pulling out a substantial division

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Speaker 2: from a major brokerage firm doesn't happen overnight. It's going

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Speaker 2: to be like a six or twelve month.

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Speaker 3: Process, absolutely, because you have to have everyone with the

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Speaker 3: oars going in the same direction. You want to make

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Speaker 3: sure that it is agreeable and everyone is whether they're

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Speaker 3: unhappy that you're going, they're happy with the deal that allowed.

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Speaker 2: You to go.

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Speaker 3: And so I took extra time to make sure that

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Speaker 3: that happened because I loved the folks over at Bear

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Speaker 3: and it was really just my own desire to be

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Speaker 3: an entrepreneur again, and they really got that and so

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Speaker 3: very amicable. But as you know, those things take a

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Speaker 3: long time to get negotiated out.

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Speaker 2: Yeah, you know, to me, the thing I'm I was

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Speaker 2: always kind of sad about with the fall of Bear

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Speaker 2: Stones eventually picked up for pennies by Jamie Diamond and

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Speaker 2: JP Morgan Chase and then even Lehman brothers. I know

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Speaker 2: a lot of great people in a lot of different divisions.

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Speaker 2: You know, we all have mentors all over the street

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Speaker 2: that even if they're a counterparty or if they're a salesperson,

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Speaker 2: there were things to learn from folks. And Bear and

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Speaker 2: Lehman were two like giant storied names. And I mean,

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Speaker 2: obviously there was a massive disruption throughout society, but the

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Speaker 2: tragedy that a lot of lay people don't know are

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Speaker 2: really good people doing really good work get they're the

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Speaker 2: collateral damage from someone else's screw up.

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Speaker 3: Totally agree, and the you know, obviously just my personal opinion,

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Speaker 3: but I think at that particular point in time, all

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Speaker 3: of the investment banks were bankrupt or insolvent.

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Speaker 2: And well some were a little more insolvent than others.

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Speaker 3: Yeah, I agree, I agree, And so it was almost

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Speaker 3: a bit like luck of the draw that Lehman and

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Speaker 3: Bear were the ones to go.

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Speaker 2: Down there went down early enough that would be salvageable.

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Speaker 2: And then a little known story that a lot of

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Speaker 2: people are unaware of. When I was writing Bail Out

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Speaker 2: Nation and doing my homework, it turned out that JP

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Speaker 2: Morgan Chase had a little derivatives flare up like years earlier.

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Speaker 2: And I don't remember if it was Jamie Diamond or

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Speaker 2: one of his lieutenanenans, but someone said, hey, this is

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Speaker 2: a mess, and this is really potentially damaging. And it

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Speaker 2: might have been Diamond who said, sell it all. I

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Speaker 2: don't care the price, if you have to take a

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Speaker 2: ten or twenty percent haircut. I want all this, well

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Speaker 2: of the books. And that's what they did. And so

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Speaker 2: when the world went to hell, they were They picked

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Speaker 2: up Washington Mutual, they picked up Bear Sterns. They got

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Speaker 2: to cherry pick the best of the best at pennies

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Speaker 2: on the dollar. And that's why JP Morgan is the

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Speaker 2: monster success it is today.

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Speaker 3: Well, Jamie is a super smart guy, and that does

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Speaker 3: not surprise me at all. You know, the joke around

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Speaker 3: Bear Stearns at the time was that Jamie really the

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Speaker 3: real reason he wanted to buy Bear.

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Speaker 2: Was he wanted the building right right, which is now

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Speaker 2: overshadowed by their brand new headquarter no park. But that

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Speaker 2: was a great octagonical building which we could see out

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Speaker 2: from our farm's windows on Brian Park with the glass.

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Speaker 3: It was a beautiful.

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Speaker 2: And and you walk in and it's like, you know,

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Speaker 2: they used to be Wall Street and then there was

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Speaker 2: you know, the Morgan, Stanley and Lehman brothers sort of

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Speaker 2: off of Midtown. Yeah where, and then this was just

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Speaker 2: all right, so very prescient before Vanderbilt was even a thing.

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Speaker 2: That's right, And there they are now when Vanderbilt is

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Speaker 2: a monster. So so let's bring it back to to

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Speaker 2: what you're doing. So you leave there you launch. Oh, Sam,

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Speaker 2: you've already had great success with what works on Wall Street?

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Speaker 2: What made you think? I think we're gonna develop a

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Speaker 2: series of quantitative approaches to managing money?

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Speaker 3: Wow? Uh so that was a dinner when I was

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Speaker 3: a teenager. My grandfather had been very successful. He was

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Speaker 3: an oil speculator, uh huh, and he kind of beat

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Speaker 3: the pledge guys by about seven years. He proceeded to

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Speaker 3: give away the vast portion of his fortune during his

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Speaker 3: own lifetime.

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Speaker 2: What was it really a fortune?

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Speaker 3: It really was, no kidd. And what he couldn't give

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Speaker 3: away he put into a foundation, the Iao'shaughnessy Foundation, which

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Speaker 3: I think today is still about one hundred million dollar foundation,

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Speaker 3: No kidd, but he made his five kids the trustees,

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Speaker 3: and so once a quarter there would be a dinner

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Speaker 3: and it would rotate. I was brought up at Saint Paul,

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Speaker 3: and so during the Saint Paul rotation, I got lucky

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Speaker 3: enough at I think I was sixteen to get invited

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Speaker 3: to the adult table. And of course, like i'd want

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Speaker 3: it to be an adult, I loved going to my parents'

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Speaker 3: cocktail parties and talking to adults, and so I was

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Speaker 3: really excited. And literally I was put down next to

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Speaker 3: my uncle John and my dad, and I'm listening and

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Speaker 3: they're talking about IBM, but they're just talking about the CEO.

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Speaker 3: They're not talking about how.

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Speaker 2: Much do they make?

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Speaker 3: How much do you have to pay for every dollar

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Speaker 3: of earnings or sales or evida? And I kind of

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Speaker 3: raised my hand and said, Dad, Uncle John, don't you

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Speaker 3: think it might be a better idea to look at

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Speaker 3: it by the numbers? And they dismissed me. This is

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Speaker 3: nineteen seventy six, right, So I got yeah, exactly, well exactly,

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Speaker 3: and so I decided, you know what, I'm going to

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Speaker 3: go look into this. So I took myself down to

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Speaker 3: the James J. Hill Research Library in downtown Saint Paul,

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Speaker 3: and I thought I was going to be really ambitious,

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Speaker 3: but I am potentially the world's laziest man. So when

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Speaker 3: I saw the five hundred of the S and P,

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Speaker 3: the S and P tear sheet book, I'm like, oh,

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Speaker 3: I'm not gonna be able to do that. So I

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Speaker 3: alighted on the Dow thirty sucks right? Did the research

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Speaker 3: found very compelling evidence that what it's pe is really

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Speaker 3: matters to your returns going forward. Very very high valuations

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Speaker 3: tended to crash and burn, Very very cheap valuations tended

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Speaker 3: to do well. But of course, you know Barry, I

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Speaker 3: was sixteen seventeen, much more interested in girls, and so

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Speaker 3: after college, got married young, I was like, I've got

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Speaker 3: to revisit all this, and got the data set from

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Speaker 3: Compu's stat and essentially that became what works on Wall Street.

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Speaker 2: So wait, would you study in college?

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Speaker 3: So the reason I am an economics I have a

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Speaker 3: degree in economics. The reason for that was I had

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Speaker 3: maybe six more credits, four to six more credits in

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Speaker 3: economics than I had in history. So history absolutely well, listen,

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Speaker 3: I think a good knowledge of history is absolutely vital

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Speaker 3: if you want to be a good investor, right yeah.

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Speaker 3: I mean, like one of the Roman wits said, he

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Speaker 3: who does not understand what happened before they were born

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Speaker 3: remains forever a child, And essentially I didn't want to

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Speaker 3: remain a child. If you look back at the market's history,

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Speaker 3: guess what. History doesn't repeat itself.

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Speaker 2: But it rhymes.

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Speaker 3: I mean, you go back to Isaac Newton losing a

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Speaker 3: fortune in the south Sea bubble, and like, literally I

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Speaker 3: always do this joke because people get it. It's like

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Speaker 3: people were so in love with that stock. Poets wrote

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Speaker 3: poetry about it. One went fill the south Sea goblet

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Speaker 3: ful the God's shill of our stocks. Take care europea

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Speaker 3: please accepts the bull, but Jove with joy puts off

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Speaker 3: the bear. And I used to when I was still

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Speaker 3: at OSAM, I used to say, I'm totally a quant

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Speaker 3: but if if somebody writes a poem about a stock

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Speaker 3: you owned.

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Speaker 2: That's a high. That's amazing, and it's funny. You and

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Speaker 2: I both have a love of quotations. And the I

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Speaker 2: tried repeatedly to track down the source of history doesn't repeat,

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Speaker 2: but it rhymes. It's always attributed to Mark Twain or

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Speaker 2: someone else, and I've never been able to really verify that.

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Speaker 3: Yeah, quote investigator.

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Speaker 2: I love that site.

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Speaker 3: Yeah, it's pretty good. They can normally get you to

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Speaker 3: the original sighting of the text. What's funny about that, though,

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Speaker 3: is almost inevitably it's somebody you've absolutely never heard of.

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Speaker 3: That's right, And I think that's why people like when

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Speaker 3: that sounds like something Mark Twain would say.

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Speaker 2: Right.

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Speaker 3: But then there's also the Mark Twain Oscar wild I

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Speaker 3: mean there's a bunch of them. Like any quote that

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Speaker 3: you really love and you don't know who did it,

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Speaker 3: people tend to say Mark Twain Oscar.

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Speaker 2: The one from Twain that stands out is and I'm

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Speaker 2: gonna mangle this. It's not the things we know that

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Speaker 2: get us into trouble. It's the things we know for

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Speaker 2: sure that just ain't show.

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Speaker 3: Yeah. That was actually a character of Mark Twain's, Oh really,

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Speaker 3: And he spoke like a Southerner of the late a

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Speaker 3: nineteen hundreds, and I think his last name was Ward.

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Speaker 3: The character's last name was Ward Twain. I mean, he

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Speaker 3: has some of the great actual quotes that are really his.

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Speaker 3: What I love is like if you pick up a

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Speaker 3: dog in the street that is starving and feed it.

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Speaker 3: It will love you. If you do the same for

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Speaker 3: a human, it will bite you. This is the principal

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Speaker 3: difference between a dog and a man, which A.

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Speaker 2: Is true and B leads to the newer line, if

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Speaker 2: you want a friend on Wall Street, get a dog. Yeah,

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Speaker 2: it's really true. We're going to talk more about quotes

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Speaker 2: and books in a moment. Before we do that, I

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Speaker 2: just want to bring up the first book, What Works

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Speaker 2: on Wall Street. That book not only has been through

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Speaker 2: multiple editions, it's had legs, It's influenced an entire generation

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Speaker 2: or two of quants. What was the most surprising thing

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Speaker 2: about what you found in the book and then its

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Speaker 2: subsequent reception in finance?

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Speaker 3: So, I think the most surprising thing was a number

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Speaker 3: of people at various firms that I was investigating working

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Speaker 3: for before starting my own I mean, I had my

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Speaker 3: own company, but I was getting a lot of offers,

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Speaker 3: primarily because they knew the book was coming right many

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Speaker 3: of them when they saw the galleys of the book,

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Speaker 3: the manuscript, the first thing they said to me, Bary

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Speaker 3: was we would love to hire you, but you cannot

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Speaker 3: publish this view you're giving it away, right exactly, going

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Speaker 3: to go there exactly. And I was like, no, no, no, no, no,

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Speaker 3: you you can have the greatest truth in the world.

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Speaker 3: You can scream it from all the rooftops, you can

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Speaker 3: take full page ads in the Wall Street Journal. Most

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Speaker 3: people are just gonna go, eh, they're not gonna do it.

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Speaker 2: It's so true. You know. My takeaway from my first book,

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Speaker 2: which is now fifteen years ago, was there would be

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Speaker 2: these debates about what led to the crisis, what were

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Speaker 2: the factors? What were And I'm like, no, no, We've

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Speaker 2: solved that. I've addressed that. Let's let's move beyond that.

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Speaker 2: And the arguments didn't stop. People just kept on debating it.

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Speaker 2: And my takeaway was, oh, you could just drop a

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Speaker 2: truth bomb on people's laps and if they don't want

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Speaker 2: to believe it, they're not gonna believe it. And that

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Speaker 2: was like, maybe I was naive, but you're one hundred

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Speaker 2: percent right. The fact that they thought you were giving

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Speaker 2: the secret away you could here's a secret to investing.

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Speaker 2: Not maybe you'll do okay with it, but nobody's going

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Speaker 2: to really adapt.

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Speaker 3: Well, you know what's funny is I would say to

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Speaker 3: these people It was one of the like when I

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Speaker 3: started out, and actually What Works wasn't my first book,

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Speaker 3: invest Like the best was, which showed you really how

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Speaker 3: to clone your favorite money managers right by looking at

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Speaker 3: the biggest difference between their portfolio factor distribution and then

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Speaker 3: using those as screens to get a portfolio much like

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Speaker 3: your manager. Note we used to update the clones versus

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Speaker 3: the manager. Last time we did it was years and

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Speaker 3: years ago. But the thing that I found really interesting

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Speaker 3: was all of the clones were beating the managers that

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Speaker 3: they cloned.

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Speaker 2: Was that case of the fee or was that cos

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Speaker 2: they're not great sellers?

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Speaker 3: It was because of our very human emotional decision makings.

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Speaker 3: Almost always under extreme stress, models don't get stressed, you know,

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Speaker 3: they don't get hungover, They never fight with their spouse.

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Speaker 3: They just keep applying those criteria. You're in, you're out.

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Speaker 3: And I think that the you know, we went through

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Speaker 3: some tough times after that book came out, and and

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Speaker 3: people have different ways of dealing with stress, and one

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Speaker 3: of them is not being good at selling.

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Speaker 2: So there's been a number of studies and I don't

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Speaker 2: want to talk about my book, We're going to talk

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Speaker 2: about your book, But some really fascinating things you learn

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Speaker 2: are when you look at the academic research fund manager.

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Speaker 2: Fund managers are actually surprisingly good buyers, yes, but they're

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Speaker 2: terrible sellers. And part of the reason is the emotionality

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Speaker 2: of the sale. They tend to panic out when they shouldn't,

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Speaker 2: or through the opposite, hold on right to the bitter

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Speaker 2: end when they.

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Speaker 3: Really should well. And also it's just because it's just

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Speaker 3: part of our human os, part of our human operator system.

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Speaker 3: I remember when Enron was going through difficulties and I

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Speaker 3: was set to speak with a classic manager, right, a

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Speaker 3: fundamental guy, and we were going to share the stage.

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Speaker 3: And the first question went to me and it was like,

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Speaker 3: are you do you own Enron? And my answer was no,

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Speaker 3: the numbers are pretty bad and so we don't. And

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Speaker 3: he looked at me kind of you know, with the

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Speaker 3: chuckle ugh you quants, you know, and then he launched

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Speaker 3: into this description of not only did he hold, he

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Speaker 3: bought more and then he gave this as the explanation.

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Speaker 3: I went to a barbecue at the cfo's house. The

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Speaker 3: CEO was there, the CFO, and I looked them in

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Speaker 3: the eye and I said, is there trouble? And they

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Speaker 3: assured me there wasn't and I'm just kind of like

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Speaker 3: sitting over there with Oh, okay, just don't touch this one.

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Speaker 2: Maybe we could get a short put on this that

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Speaker 2: just like I'll tell you something, it's really funny. And

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Speaker 2: this just goes to how naive and stupid I am,

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Speaker 2: or especially was early in my career. I would listen

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Speaker 2: in on quarterly calls, and I would believe every word

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Speaker 2: I heard, like, these guys aren't going to lie to

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Speaker 2: their investors. Everything's gonna be great. And I very quickly learned, oh,

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Speaker 2: you're a terrible judge of people. You'll buy anything that

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Speaker 2: a slick salesman is selling you. You just have to stop.

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Speaker 2: And I just stopped listening to calls because I'm an idiot.

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Speaker 2: I believe what they say. I would rather look at

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Speaker 2: the numbers and yeah, I know the numbers can lie,

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Speaker 2: but not as easily as you know that.

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Speaker 3: That's also a really big part of human os default

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Speaker 3: to trust.

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Speaker 2: Well, we're social.

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Speaker 3: Right, right, were domesticated primates. We grew up in groups

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Speaker 3: where trust was really really important. So your average human

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Speaker 3: defaults to trust. And by the way, that's not a

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Speaker 3: bad default for the vast majority of people. It probably

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Speaker 3: works better to trust who you're listening to, right, And

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Speaker 3: so one of the things that we're looking at in

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Speaker 3: one of our divisions at O'Shaughnessy Adventures right now is

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Speaker 3: voice software AI that does stress analysis on any type

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Speaker 3: of media. So obviously earning calls present themselves as kind

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Speaker 3: of number one. Yeah really and I got to tell you,

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Speaker 3: Barry Wow.

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Speaker 2: Exciting way stuff.

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Speaker 3: Oh my god.

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Speaker 2: Now how much of that is nervousness about speaking to

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Speaker 2: a large audience and nervousness because they know something and

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Speaker 2: they don't want to disclose it.

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Speaker 3: So, as you might guess, you do baselines. You take

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Speaker 3: a recording where clearly either you know, you get some

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Speaker 3: tape that was before the call or you know, a

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Speaker 3: speech that had nothing to do with earnings, and that

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Speaker 3: creates your baseline, and then you get to see very

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Speaker 3: very quickly, like Spike, we don't have any worries.

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Speaker 2: Spike, Wow, that sounds like fun.

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Speaker 3: Yeah, it is fun, And we're not sure how we're

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Speaker 3: gonna do it because we don't offer asset management services

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Speaker 3: to people outside of O'shaughna's Adventures. That was a deal

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Speaker 3: that we made with Franklin Templeton that we would not launch, but.

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Speaker 2: You could still do a little Come on, don't don't

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Speaker 2: you get the itch sometimes to say, hey, x y

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Speaker 2: Z stock is wildly overvalued and the CFO is full

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Speaker 2: of it. Let's put on some let's buy some deep

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Speaker 2: out of the money puts. We'd see where this goes.

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Speaker 3: You know, if you can keep a secret, we might

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Speaker 3: try that with some of our internal capital.

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Speaker 2: Let me know, I'm right there with you. I love

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Speaker 2: the idea of that. Where did the title come from?

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Speaker 3: So it came from a group of my teammates at OSV.

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Speaker 3: Essentially I have been a quote junkie all of my life.

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Speaker 3: Same so I have kept I Barry have notebooks filled

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Speaker 3: with oh really, from way back when I I think

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Speaker 3: the first time I started it, I was twenty one.

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Speaker 3: And so I just love them and I think that

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Speaker 3: you know, they can pack a lot of a punch

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Speaker 3: if you if you put them together right, if you

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Speaker 3: curate them right, et cetera. If you read what Works

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Speaker 3: on Wall Street, I open every chapter with it.

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Speaker 2: I do that a lot. Also, I writ it's fun.

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Speaker 2: Let me let me ask you one other question about

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Speaker 2: the title. So one of the things that's fascinating if

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Speaker 2: you're if you like music or poetry or even I'm

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Speaker 2: gonna go into the weed Shakespearean iamic pentameter. Okay, so

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Speaker 2: there is a rhythm too, and I'm gonna write this

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Speaker 2: down so you know, even if if you get this,

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Speaker 2: I want you to know there is a rhythm to

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Speaker 2: the phrase A timeless collection of infinite wisdom. That reminds

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Speaker 2: me of another book title. And I'm curious if it

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Speaker 2: was in your mind when you came out with this.

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Speaker 3: Oh you got me on that one.

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Speaker 2: A heartbreaking work of staggering genies, A timeless collection of

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Speaker 2: infinite wisdom. It just leaves off in that same rhythm.

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Speaker 3: I don't know if that was a wasn't purpose behind

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Speaker 3: recause I've always loved that title.

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Speaker 2: Heartbreaking work, stagger and and it's like you could go

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Speaker 2: with you a different It's a staggering work of heartbreaking

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Speaker 2: gene It's like you could flip it around, but this

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Speaker 2: phrase theology just left that left right out.

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Speaker 3: I am incredibly lucky to have just extraordinarily talented teammates.

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Speaker 3: We have a lot of writers on the team, we

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Speaker 3: have a lot of editors, and you know they would

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Speaker 3: just go at it like, what about this title? What

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Speaker 3: about because we had to call it two thoughts because

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Speaker 3: this started very on a whim.

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Speaker 2: Well, I know you have been tweeting for I don't

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Speaker 2: know ten years, not just a quote. And I was

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Speaker 2: doing that for a long time, just throwing a quote

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Speaker 2: up that I thought was relevant. Sometimes I would stagger

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Speaker 2: them out, like you can plan a tweet six months

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Speaker 2: in advance. Hey, I don't know what's going to be happening

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Speaker 2: in August, but I think this is relevant. You have

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Speaker 2: been doing two tweets for forever.

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Speaker 3: Yeah, And so it was kind of like, you know

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Speaker 3: Ken Stanley's book Greatness can't be planned, This is a

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Speaker 3: perfect example of that. So I just thought, you know,

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Speaker 3: what the heck, I'm going to put up two thoughts

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Speaker 3: and I'll see if I like it, if I keep

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Speaker 3: doing it, I'll just keep doing it right. And then

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Speaker 3: all of a sudden, like the people that got attracted

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Speaker 3: to it were there was a lot of people, and

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Speaker 3: then I started getting dms on Twitter basically saying hey,

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Speaker 3: if you would do this in a newsletter, I would subscribe.

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Speaker 3: And then one of my colleagues was like, well, let's

435
00:26:25,119 --> 00:26:28,960
Speaker 3: do the newsletter, and in the newsletter, why don't we say, hey,

436
00:26:28,960 --> 00:26:32,840
Speaker 3: would you like a book? And that's what happened. Literally,

437
00:26:33,000 --> 00:26:37,760
Speaker 3: we iterated, iterated, iterated, and ended up publishing the book.

438
00:26:38,200 --> 00:26:41,879
Speaker 2: Huh. So that's really interesting that that's the genesis of

439
00:26:41,960 --> 00:26:46,320
Speaker 2: the two thoughts. When you're picking a pair of thoughts

440
00:26:46,320 --> 00:26:49,600
Speaker 2: from the same author, are you looking for things that

441
00:26:49,760 --> 00:26:54,119
Speaker 2: compliment each other? Are you looking for their most to

442
00:26:54,320 --> 00:26:58,520
Speaker 2: most profound statements? How are you selecting A and B

443
00:26:58,840 --> 00:26:59,679
Speaker 2: for this author?

444
00:27:00,400 --> 00:27:05,200
Speaker 3: Yeah, it's a little bit messy to be really honest,

445
00:27:06,560 --> 00:27:09,520
Speaker 3: because I'll usually start with the notebooks that have all

446
00:27:09,560 --> 00:27:12,600
Speaker 3: my handwritten quotes out when I copied the quote over,

447
00:27:14,240 --> 00:27:18,159
Speaker 3: and sometimes I'll think, Ooh, I found like the perfect

448
00:27:18,400 --> 00:27:21,760
Speaker 3: one quote from this author, And then I'll spend some

449
00:27:21,880 --> 00:27:25,639
Speaker 3: time going through the rest of their work, etc. Finding

450
00:27:25,640 --> 00:27:29,800
Speaker 3: one that would compliment it. But then sometimes some of

451
00:27:29,840 --> 00:27:34,560
Speaker 3: the best two quotes that work the best they don't

452
00:27:34,720 --> 00:27:39,080
Speaker 3: compliment each other. In other words, it's kind of like, hey,

453
00:27:39,160 --> 00:27:43,320
Speaker 3: you know history rhymes, But then the second quote is

454
00:27:43,880 --> 00:27:47,320
Speaker 3: but always keep your eyes on the horizon, right, Like.

455
00:27:47,680 --> 00:27:51,640
Speaker 2: Hmmm, two very different, two very different things.

456
00:27:51,720 --> 00:27:56,880
Speaker 3: And so I wasn't precious about it at all, literally,

457
00:27:56,920 --> 00:27:59,280
Speaker 3: because it just grew out of me thrown. Two quotes

458
00:27:59,320 --> 00:28:01,840
Speaker 3: from the same author are up on Twitter, and so

459
00:28:02,760 --> 00:28:05,680
Speaker 3: you know, after the fact, people start asking like, well,

460
00:28:05,720 --> 00:28:08,000
Speaker 3: did you plan it that way? And the honest to

461
00:28:08,040 --> 00:28:12,160
Speaker 3: God truth is no, I did not organically grew up ratically. Hey,

462
00:28:12,200 --> 00:28:16,320
Speaker 3: if you do something, my experience has been tacking into

463
00:28:16,359 --> 00:28:20,760
Speaker 3: what works. Yeah, and you know it's not quite direct mail,

464
00:28:21,240 --> 00:28:23,560
Speaker 3: no where. Hey, we're getting a response from this, but

465
00:28:23,680 --> 00:28:27,160
Speaker 3: not that. It's not exactly an ab test, but hey,

466
00:28:27,160 --> 00:28:29,680
Speaker 3: people seem to like this, Let's give them more. Yeah,

467
00:28:29,760 --> 00:28:32,199
Speaker 3: and that's what happened here. You know, like one of

468
00:28:32,240 --> 00:28:37,200
Speaker 3: the best growth factors in investing is momentum, and if

469
00:28:37,240 --> 00:28:40,280
Speaker 3: you see something gaining momentum, this is this is a

470
00:28:40,440 --> 00:28:44,600
Speaker 3: really important idea for me. I always listen to the

471
00:28:44,720 --> 00:28:48,600
Speaker 3: market because if I have one opinion and the market

472
00:28:48,600 --> 00:28:52,440
Speaker 3: has a different opinion, I'm wrong probably most of the time.

473
00:28:53,120 --> 00:28:57,080
Speaker 3: And so momentum in this regard. You see all the

474
00:28:57,200 --> 00:28:59,560
Speaker 3: dms increasing, Hey, when are you going to do the

475
00:28:59,560 --> 00:29:04,280
Speaker 3: book for the Hey, where's the newsletter? Etc. And I'm like, Okay,

476
00:29:04,360 --> 00:29:09,160
Speaker 3: this is truly emerging from beneath, not from me saying

477
00:29:09,560 --> 00:29:11,760
Speaker 3: you know what I'm gonna do a two quotes book

478
00:29:11,880 --> 00:29:15,200
Speaker 3: and it's gonna be great. No, this was all others

479
00:29:15,280 --> 00:29:18,200
Speaker 3: in the marketplace saying to me, hey, Jim, do a

480
00:29:18,280 --> 00:29:19,400
Speaker 3: two thoughts book.

481
00:29:19,600 --> 00:29:24,680
Speaker 2: A grassroots groundswell. So let's talk about knowing that you've

482
00:29:24,720 --> 00:29:28,040
Speaker 2: had all these quotes over the decades, how did you

483
00:29:28,120 --> 00:29:33,560
Speaker 2: begin to think about organizing this? Just quotes this Bartlett's

484
00:29:33,600 --> 00:29:36,960
Speaker 2: Book of Quotations, and that's alphabetical. Yeah, and you know

485
00:29:37,080 --> 00:29:39,600
Speaker 2: that's a research piece, but you're putting this out as

486
00:29:40,040 --> 00:29:45,200
Speaker 2: less of an encyclopedia more of a nonfiction. How'd you

487
00:29:45,240 --> 00:29:47,720
Speaker 2: think about how you wanted to structure it and organize it.

488
00:29:47,880 --> 00:29:50,960
Speaker 3: We went back and forth on that forever, and then

489
00:29:51,000 --> 00:29:59,520
Speaker 3: we decided, okay, let's separate it by broad groupings like thinkers, writers,

490
00:29:59,640 --> 00:30:05,360
Speaker 3: author you know, dynamos, people who founded companies and were

491
00:30:05,360 --> 00:30:10,680
Speaker 3: incredibly successful. And we in the hardcover of the book,

492
00:30:12,080 --> 00:30:16,320
Speaker 3: we made sure that each one was color quote coded,

493
00:30:17,120 --> 00:30:20,000
Speaker 3: because really, the book is not meant for you to

494
00:30:20,080 --> 00:30:23,480
Speaker 3: sit down and read all the quotes. It's really meant

495
00:30:23,560 --> 00:30:26,280
Speaker 3: to have on your coffee table, have on your desk

496
00:30:26,880 --> 00:30:30,120
Speaker 3: and just open it up randomly. It's what I do,

497
00:30:30,720 --> 00:30:33,800
Speaker 3: and just read the two quotes because you'll see two

498
00:30:33,880 --> 00:30:37,880
Speaker 3: quotes on each page and kind of think about them.

499
00:30:38,000 --> 00:30:41,040
Speaker 3: And because people are and by the way, that's the

500
00:30:41,040 --> 00:30:43,440
Speaker 3: way everyone I've ever talked to as a copy of

501
00:30:43,440 --> 00:30:47,440
Speaker 3: the book, that's the way they're using it. And so

502
00:30:48,080 --> 00:30:50,920
Speaker 3: it was the kind of the you know, a lot

503
00:30:50,960 --> 00:30:53,360
Speaker 3: of people do morning pages, do that kind of thing

504
00:30:53,360 --> 00:30:57,080
Speaker 3: in the morning they write. And the number of people

505
00:30:57,160 --> 00:31:00,040
Speaker 3: who've either emailed me, texted me, or dm me on

506
00:31:00,080 --> 00:31:05,680
Speaker 3: Twitter saying I absolutely love this for my morning writing,

507
00:31:05,960 --> 00:31:09,800
Speaker 3: right because they'll open it randomly, right, they'll they'll contemplate

508
00:31:09,800 --> 00:31:12,560
Speaker 3: the quote, they'll write it at the top of their

509
00:31:12,720 --> 00:31:15,600
Speaker 3: their morning writing and then that's what they talk about.

510
00:31:16,200 --> 00:31:19,480
Speaker 2: It inspires them. So based on that, let me suggest

511
00:31:20,000 --> 00:31:24,080
Speaker 2: we need a two quota day desktop calendar where you like,

512
00:31:24,200 --> 00:31:26,880
Speaker 2: do you remember those old ones where I just pull

513
00:31:27,400 --> 00:31:30,000
Speaker 2: you know, just it was almost like a giant pad

514
00:31:30,280 --> 00:31:31,640
Speaker 2: of mine. Mine.

515
00:31:31,880 --> 00:31:33,360
Speaker 3: Mine was a far side.

516
00:31:33,480 --> 00:31:36,520
Speaker 2: I was about to say that I still have this

517
00:31:36,960 --> 00:31:40,360
Speaker 2: in my head, this School for the Gifted where he's

518
00:31:40,400 --> 00:31:44,000
Speaker 2: pushing on the and the door says, well like from

519
00:31:44,040 --> 00:31:47,320
Speaker 2: that exact same exactly. I had one of those, and

520
00:31:47,360 --> 00:31:49,280
Speaker 2: I had a Calvin and Hobbes and it's just a

521
00:31:49,320 --> 00:31:52,480
Speaker 2: different one every other one of my favorites. Absolutely, that's

522
00:31:52,520 --> 00:31:56,600
Speaker 2: so funny. So let's talk about what are real quotes

523
00:31:56,640 --> 00:31:59,440
Speaker 2: and what or not. And I have a very vivid

524
00:31:59,480 --> 00:32:05,040
Speaker 2: recollection of putting a quote that supposedly was Thomas Jefferson

525
00:32:05,120 --> 00:32:09,280
Speaker 2: in Bailout Nation, and like a year after the book

526
00:32:09,400 --> 00:32:13,160
Speaker 2: was published, I got an email from someone saying they

527
00:32:13,240 --> 00:32:17,400
Speaker 2: liked the book. Ps, this is an urban legend. Thomas

528
00:32:17,480 --> 00:32:21,360
Speaker 2: Jefferson never said this. And that's how I ended up

529
00:32:21,440 --> 00:32:26,160
Speaker 2: eventually tracking down Quote Investigator because I was so horrified

530
00:32:26,880 --> 00:32:30,440
Speaker 2: and one person said something nobody ever mentioned it again,

531
00:32:30,960 --> 00:32:33,000
Speaker 2: and it was like, all right, so the good news

532
00:32:33,080 --> 00:32:35,680
Speaker 2: is the bad news is what a screw up. The

533
00:32:35,720 --> 00:32:39,480
Speaker 2: good news is nobody noticed. How did you go about

534
00:32:39,480 --> 00:32:43,880
Speaker 2: the process of validating and verifying that the quotes were

535
00:32:43,960 --> 00:32:47,640
Speaker 2: real and genuine. It's not just Mark Twain, it's Albert

536
00:32:47,680 --> 00:32:51,479
Speaker 2: Einstein and George Carlin apparently said all these things. They

537
00:32:51,560 --> 00:32:56,880
Speaker 2: never said compounding is the eighth wonder. Einstein never said, yeah,

538
00:32:57,080 --> 00:32:57,320
Speaker 2: I know.

539
00:32:58,560 --> 00:33:01,360
Speaker 3: So there. I was very lucky to have a very

540
00:33:01,440 --> 00:33:06,520
Speaker 3: diligent team, and they identified a host of sources. We

541
00:33:06,640 --> 00:33:11,680
Speaker 3: use Quote Investigator, but we used others as well. To

542
00:33:11,880 --> 00:33:16,040
Speaker 3: try to get the veracity of the author and the

543
00:33:16,120 --> 00:33:20,680
Speaker 3: quote right now. Having said that, I'm sure that there

544
00:33:20,680 --> 00:33:23,920
Speaker 3: are still some examples in there where we got it wrong,

545
00:33:24,560 --> 00:33:26,840
Speaker 3: and so we even put a little thing in there saying,

546
00:33:26,960 --> 00:33:34,440
Speaker 3: you know, yeah, all errors are our own, right. But philosophically,

547
00:33:34,600 --> 00:33:37,000
Speaker 3: I have a little bit of a different view of this.

548
00:33:37,760 --> 00:33:43,200
Speaker 3: I think that we all too often because we anthromorphize

549
00:33:43,240 --> 00:33:48,000
Speaker 3: things to the extent where if Albert Einstein said this,

550
00:33:48,160 --> 00:33:52,840
Speaker 3: then it's important I invert that and I say, it

551
00:33:52,840 --> 00:33:57,760
Speaker 3: doesn't matter who said this. Let's stay with the compounding

552
00:33:57,760 --> 00:33:59,720
Speaker 3: of the eighth wonder of the world. You know what,

553
00:33:59,800 --> 00:34:02,360
Speaker 3: you and I know that's true, actually is true. We

554
00:34:02,440 --> 00:34:06,720
Speaker 3: know that's true. And so what's more important that idea

555
00:34:06,840 --> 00:34:11,120
Speaker 3: getting into somebody's head, or that Barry Ridholts or Jim

556
00:34:11,120 --> 00:34:15,879
Speaker 3: O'Shaughnessy actually said that. To me, it doesn't really matter. Now.

557
00:34:15,920 --> 00:34:18,000
Speaker 3: I'm not trying to diss the people who want to

558
00:34:18,040 --> 00:34:21,160
Speaker 3: be exact. They should be. You want to be accurate,

559
00:34:21,320 --> 00:34:27,440
Speaker 3: absolutely correct, But with me, it's always more like I'm

560
00:34:27,680 --> 00:34:32,320
Speaker 3: fascinated by the thought or the message that's being communicated.

561
00:34:32,760 --> 00:34:35,719
Speaker 3: That's what I want people to focus on now, obviously,

562
00:34:35,800 --> 00:34:38,000
Speaker 3: we want it to be attributed to the right person.

563
00:34:38,400 --> 00:34:41,120
Speaker 3: You know, Banksy had a really funny quote. I don't

564
00:34:41,120 --> 00:34:42,600
Speaker 3: think we put it in the book, but I put

565
00:34:42,600 --> 00:34:46,440
Speaker 3: it up on Twitter a lot, And it's any kind

566
00:34:46,480 --> 00:34:50,520
Speaker 3: of philosophical statement sounds better if you put the name

567
00:34:50,560 --> 00:34:53,279
Speaker 3: of a dead famous philosopher after it. And he put

568
00:34:53,280 --> 00:34:56,800
Speaker 3: Plato and then and then waved beneath it he wrote,

569
00:34:56,960 --> 00:35:01,000
Speaker 3: no Banksy, And so I thought that was really funny.

570
00:35:01,000 --> 00:35:05,359
Speaker 3: But you know that's probably what's actually happening, right. It's like, Hm,

571
00:35:05,600 --> 00:35:08,960
Speaker 3: I want people to really take this seriously. So I'm

572
00:35:08,960 --> 00:35:12,640
Speaker 3: going to make sure that Einstein said this, so that

573
00:35:12,920 --> 00:35:16,200
Speaker 3: you know, it doesn't add to what the what the

574
00:35:16,320 --> 00:35:19,080
Speaker 3: thought is inspiring in you.

575
00:35:19,080 --> 00:35:21,800
Speaker 2: You know, that kind of reminds me of the Abe

576
00:35:21,840 --> 00:35:25,520
Speaker 2: Lincoln line, don't believe everything you read on the internet. Right,

577
00:35:25,640 --> 00:35:29,520
Speaker 2: But let me let me invert the question. In your

578
00:35:29,600 --> 00:35:33,200
Speaker 2: research process, did you find a quote that you knew

579
00:35:33,239 --> 00:35:35,279
Speaker 2: and loved and thought, oh, this is great and it

580
00:35:35,320 --> 00:35:39,120
Speaker 2: fits this person so well, and then subsequently you discover oh,

581
00:35:39,200 --> 00:35:42,040
Speaker 2: it wasn't by that person. Yes, and any come to mind.

582
00:35:43,760 --> 00:35:49,600
Speaker 3: Well, we had quite a few, actually, Eleanor Roosevelt quotes

583
00:35:49,960 --> 00:35:55,600
Speaker 3: that were not Eleanor Roosevelt, and we had a lot

584
00:35:55,719 --> 00:35:59,640
Speaker 3: of well, not going back over the obvious ones Einstein,

585
00:36:00,080 --> 00:36:07,719
Speaker 3: you know, TWAINN. Twayne, George Carlin, oscar Wilde, etc. And

586
00:36:08,520 --> 00:36:11,160
Speaker 3: if we love the quote, we would put it in

587
00:36:11,400 --> 00:36:15,440
Speaker 3: under the actual author's name. And I can't think of

588
00:36:15,480 --> 00:36:19,680
Speaker 3: one that's great right now where we did that. But

589
00:36:19,760 --> 00:36:23,480
Speaker 3: it's really funny too because the reaction we did this.

590
00:36:23,640 --> 00:36:26,839
Speaker 3: We did a test on our company slack. I put

591
00:36:26,880 --> 00:36:29,759
Speaker 3: the same quote when we found one of these and

592
00:36:30,120 --> 00:36:34,720
Speaker 3: it was originally attributed to Eleanor Roosevelt, and it actually

593
00:36:34,880 --> 00:36:38,200
Speaker 3: ended up being a woman who was a friend of

594
00:36:38,239 --> 00:36:41,880
Speaker 3: hers and often in the White House, but who no

595
00:36:41,960 --> 00:36:44,880
Speaker 3: one had ever heard of, at least no contemporary person

596
00:36:45,239 --> 00:36:47,680
Speaker 3: had ever heard of. So I put them both up

597
00:36:47,760 --> 00:36:51,040
Speaker 3: on our company slack and I said, what do you

598
00:36:51,080 --> 00:36:55,480
Speaker 3: guys think of the first one? Lots of emojis and everything,

599
00:36:55,880 --> 00:36:58,600
Speaker 3: And then I put it up with the other woman's name,

600
00:36:58,920 --> 00:37:05,680
Speaker 3: the less famous author, actual author crickets. And so to me,

601
00:37:06,280 --> 00:37:11,520
Speaker 3: there's obviously something being activated in our brain that says, ooh,

602
00:37:11,719 --> 00:37:15,560
Speaker 3: must be important because Eleanor Roosevelt or Albert Einstein said it,

603
00:37:15,880 --> 00:37:19,719
Speaker 3: and I always try myself to be neutral on that.

604
00:37:19,800 --> 00:37:23,520
Speaker 3: I always try to focus on what is being said,

605
00:37:24,040 --> 00:37:25,759
Speaker 3: not who is saying it.

606
00:37:26,480 --> 00:37:31,880
Speaker 2: And to give you the behavioral finance spin on that,

607
00:37:31,880 --> 00:37:35,680
Speaker 2: that's the halo effect. You're giving credit to a person

608
00:37:35,800 --> 00:37:39,319
Speaker 2: for success in one area, and you're allowing that to

609
00:37:39,400 --> 00:37:41,719
Speaker 2: spill over to the quote, whether or not they said

610
00:37:41,719 --> 00:37:45,120
Speaker 2: it or not. It's not quite social proof, but hey,

611
00:37:45,160 --> 00:37:48,080
Speaker 2: if it's Oscar Wilde or Mark Twain, we know they

612
00:37:48,080 --> 00:37:51,760
Speaker 2: were wordsmith's and brilliant, and hey, if they said it,

613
00:37:51,760 --> 00:37:54,919
Speaker 2: it must be must be good, right, And I wonder

614
00:37:54,920 --> 00:37:58,560
Speaker 2: if that's why people, you know, attribute thing to George

615
00:37:58,600 --> 00:38:04,120
Speaker 2: Carlin and to say nothing of Einstein. So you co

616
00:38:04,200 --> 00:38:06,560
Speaker 2: wrote this book. Tell us a little bit about your

617
00:38:06,600 --> 00:38:12,400
Speaker 2: co author, Vatsill Kowshk. How did you guys handle the workload?

618
00:38:12,440 --> 00:38:16,200
Speaker 2: Did you? Was he more organizational and you're more philosophical.

619
00:38:16,280 --> 00:38:20,200
Speaker 2: I know you're deep down inside a philosopher. Tell us

620
00:38:20,719 --> 00:38:22,640
Speaker 2: how did you go about putting the work together.

621
00:38:22,800 --> 00:38:27,840
Speaker 3: So Vatsil was the first employee of Infinite Loops, my podcast,

622
00:38:29,200 --> 00:38:34,440
Speaker 3: and he is an amazing guy. He is multi talented.

623
00:38:35,480 --> 00:38:41,000
Speaker 3: He's a great builder of tech, but he also reads extensively,

624
00:38:41,840 --> 00:38:46,120
Speaker 3: And it was actually Vasil who came to me and said, okay, Jim,

625
00:38:46,120 --> 00:38:50,600
Speaker 3: you got all these guys and women texting you saying

626
00:38:50,680 --> 00:38:53,200
Speaker 3: we want a book. He goes, let's do the book.

627
00:38:53,920 --> 00:38:59,800
Speaker 3: And so what he handled was almost exclusively the vetting,

628
00:39:00,239 --> 00:39:03,880
Speaker 3: the process of making sure who I had attributed the

629
00:39:03,960 --> 00:39:08,120
Speaker 3: quote to was correct. But then he also did a

630
00:39:08,239 --> 00:39:14,719
Speaker 3: bit of curating. You know, he decided, with ultimately my approval,

631
00:39:15,120 --> 00:39:18,319
Speaker 3: you know, we don't think this group really goes in there.

632
00:39:18,520 --> 00:39:22,560
Speaker 3: We'd much prefer this group. So he was very instrumental

633
00:39:22,680 --> 00:39:27,560
Speaker 3: on the actual curation of the quotes. Where I was,

634
00:39:27,719 --> 00:39:31,399
Speaker 3: as you say, much more philosophical. If there was one

635
00:39:31,440 --> 00:39:35,960
Speaker 3: that I absolutely loved and he just wasn't finding a

636
00:39:36,000 --> 00:39:38,520
Speaker 3: place to fit it in, then I would say, well

637
00:39:38,560 --> 00:39:39,200
Speaker 3: try harder.

638
00:39:39,640 --> 00:39:43,160
Speaker 2: All right. So I know, I know there are certain

639
00:39:43,280 --> 00:39:49,280
Speaker 2: authors you really appreciate, but I'm curious what thinkers, what philosophers,

640
00:39:49,360 --> 00:39:55,560
Speaker 2: what books found their way into the gestalt of this book,

641
00:39:55,600 --> 00:39:58,520
Speaker 2: What really influenced your approach to this.

642
00:39:59,360 --> 00:40:05,920
Speaker 3: So it was not necessarily because hint, there'll probably be

643
00:40:05,960 --> 00:40:08,560
Speaker 3: another version of this book coming out. It could be

644
00:40:09,520 --> 00:40:13,880
Speaker 3: this book, right, So some I held in abeyance because

645
00:40:14,239 --> 00:40:16,520
Speaker 3: I really wanted them to go into the second book.

646
00:40:16,920 --> 00:40:22,840
Speaker 3: But you know, I admire greatly all of the Age

647
00:40:22,840 --> 00:40:26,759
Speaker 3: of Enlightenment authors and thinkers. You know, you're Adam Smith's,

648
00:40:26,920 --> 00:40:32,640
Speaker 3: You're you know, all the people who were like way

649
00:40:32,680 --> 00:40:36,200
Speaker 3: to tick. We could actually do things that we might

650
00:40:36,280 --> 00:40:40,320
Speaker 3: call the scientific method and really test all of our beliefs,

651
00:40:41,080 --> 00:40:44,480
Speaker 3: much to the chagrin of the ruling churches of the

652
00:40:44,520 --> 00:40:49,799
Speaker 3: time period. And so Voltaire always big, big fan of

653
00:40:49,880 --> 00:40:55,520
Speaker 3: his work, and you know, but I didn't go at

654
00:40:55,560 --> 00:41:00,040
Speaker 3: it from that vantage point. What I really want I

655
00:41:00,040 --> 00:41:02,800
Speaker 3: wanted to do because of the nature of the book.

656
00:41:03,080 --> 00:41:06,560
Speaker 3: In other words, I never expected anyone to sit and

657
00:41:06,640 --> 00:41:09,439
Speaker 3: go from the front page to the last page. If

658
00:41:09,480 --> 00:41:12,640
Speaker 3: I had, I would have done it differently. Then I

659
00:41:12,680 --> 00:41:16,280
Speaker 3: would have tried to tell a story, an overall story

660
00:41:16,760 --> 00:41:19,880
Speaker 3: with the quotes, something we might actually try with the

661
00:41:20,000 --> 00:41:22,160
Speaker 3: one of the next versions of the book, but with

662
00:41:22,320 --> 00:41:24,879
Speaker 3: this one, since I knew I wanted it to be

663
00:41:25,040 --> 00:41:27,640
Speaker 3: kind of a jumping off point for people to get

664
00:41:27,680 --> 00:41:32,120
Speaker 3: an idea to think about it, I just was very

665
00:41:32,239 --> 00:41:34,200
Speaker 3: much not you know, I'm not going to make it

666
00:41:34,200 --> 00:41:34,839
Speaker 3: obvious and.

667
00:41:34,760 --> 00:41:35,719
Speaker 2: I'm not gonna.

668
00:41:36,960 --> 00:41:40,560
Speaker 3: Follow them in sequential order or you know, this group

669
00:41:41,000 --> 00:41:45,360
Speaker 3: all are together and absent from other places in the book.

670
00:41:47,160 --> 00:41:50,600
Speaker 3: So yeah, I mean like you'll get a very good

671
00:41:50,640 --> 00:41:54,200
Speaker 3: idea for some of my favorite thinkers by just looking

672
00:41:54,280 --> 00:41:55,919
Speaker 3: at who I'm doing quotes by.

673
00:41:56,440 --> 00:41:59,279
Speaker 2: Why a book? Why not some other media? You're so,

674
00:42:00,160 --> 00:42:02,840
Speaker 2: you know, digital forward and have been for a long time.

675
00:42:04,280 --> 00:42:08,279
Speaker 2: I always find I like physical books. But you know

676
00:42:08,520 --> 00:42:12,360
Speaker 2: you and I are from an earlier generation. Everything seems

677
00:42:12,400 --> 00:42:14,600
Speaker 2: to be moving in a different direction.

678
00:42:14,960 --> 00:42:19,000
Speaker 3: It is, but number one, like if you look at

679
00:42:19,000 --> 00:42:24,680
Speaker 3: Ojenasy Ventures, it's everything that I love, like infinite books,

680
00:42:24,760 --> 00:42:30,919
Speaker 3: the publisher, infinite film, I love movies, the fellowships, which

681
00:42:30,960 --> 00:42:35,680
Speaker 3: you know all about. But I think that it's not

682
00:42:35,800 --> 00:42:40,400
Speaker 3: just people of our generation who like beautiful books. In fact,

683
00:42:41,000 --> 00:42:44,480
Speaker 3: the people who were the most excited about it were

684
00:42:44,560 --> 00:42:48,080
Speaker 3: younger people because we took a great deal of care

685
00:42:48,640 --> 00:42:53,120
Speaker 3: to make it beautiful, and we had the printer from

686
00:42:53,239 --> 00:42:58,040
Speaker 3: Italy do the printing, and it's got color and the

687
00:42:58,239 --> 00:43:02,960
Speaker 3: spine isn't glued. So the number of younger people, and

688
00:43:03,000 --> 00:43:07,440
Speaker 3: when I say younger, anyone probably under thirty five. The

689
00:43:07,520 --> 00:43:09,880
Speaker 3: notes that I would get saying this is the most

690
00:43:09,960 --> 00:43:14,680
Speaker 3: beautiful artifact and I heard that term more than once

691
00:43:15,400 --> 00:43:20,000
Speaker 3: artifact artifact. So there, so one was a friend and

692
00:43:20,080 --> 00:43:22,000
Speaker 3: so I called him and I'm like, why are you

693
00:43:22,040 --> 00:43:26,120
Speaker 3: calling this an artifact? And he goes because I'm beginning

694
00:43:26,160 --> 00:43:30,080
Speaker 3: to look at these hardcover books as works of art, right,

695
00:43:30,719 --> 00:43:35,960
Speaker 3: and so that was surprising to me. But I love

696
00:43:36,280 --> 00:43:40,640
Speaker 3: I love books, you know, I have big libraries at

697
00:43:40,640 --> 00:43:44,680
Speaker 3: my house. What I mostly by the way Berry read

698
00:43:44,960 --> 00:43:49,880
Speaker 3: on Kindle for iPad rightly, But if I love a book,

699
00:43:50,480 --> 00:43:54,760
Speaker 3: I always buy the hard copy. And if I really

700
00:43:54,800 --> 00:43:56,920
Speaker 3: love a book, I buy the hard copy for my

701
00:43:57,040 --> 00:44:01,920
Speaker 3: library and three paperbacks to give to and and so

702
00:44:02,280 --> 00:44:04,560
Speaker 3: one of the things, it's kind of like vinyl, right,

703
00:44:05,120 --> 00:44:07,279
Speaker 3: we grew up on vinyl. That's how we made our

704
00:44:07,320 --> 00:44:10,160
Speaker 3: mixtapes everything else. But guess what, a lot of young

705
00:44:10,200 --> 00:44:13,640
Speaker 3: people are going back and sampling vinyl. So I gues

706
00:44:13,680 --> 00:44:14,800
Speaker 3: everyone seems to like it.

707
00:44:15,080 --> 00:44:19,239
Speaker 2: There's there's a certain tactile, yeah, feel I used to

708
00:44:19,480 --> 00:44:23,319
Speaker 2: love the multi album art, which not only do you

709
00:44:23,440 --> 00:44:27,000
Speaker 2: not get with the same way with small CDs, but

710
00:44:27,080 --> 00:44:30,160
Speaker 2: when you move to streaming, you don't even know the

711
00:44:30,239 --> 00:44:33,799
Speaker 2: names of half the songs on an album because it

712
00:44:34,000 --> 00:44:36,719
Speaker 2: just all kind of comes through it's a different experience, Yeah,

713
00:44:36,840 --> 00:44:39,200
Speaker 2: very much so. So let's talk a little bit about

714
00:44:40,000 --> 00:44:44,600
Speaker 2: both O'shaughnessee Ventures and O SAM. I sort of look

715
00:44:44,640 --> 00:44:48,160
Speaker 2: at them as part of a continuum on your on

716
00:44:48,200 --> 00:44:52,879
Speaker 2: your career. You let your son Patrick take over as

717
00:44:53,000 --> 00:44:57,880
Speaker 2: CEO of O'Shaughnessy Asset Management. He was a key driver

718
00:44:58,239 --> 00:45:02,319
Speaker 2: of Canvas, which was built on top of a database

719
00:45:02,400 --> 00:45:06,040
Speaker 2: that you've been refining since the nineteen nineties. How do

720
00:45:06,120 --> 00:45:06,440
Speaker 2: I have that?

721
00:45:06,600 --> 00:45:10,719
Speaker 3: Yeah, yeah, And actually you might remember I started the

722
00:45:10,760 --> 00:45:15,200
Speaker 3: first online investment advisor called netfolio. That's right in nineteen

723
00:45:15,320 --> 00:45:19,400
Speaker 3: ninety nine, two thousand. I was just, you know, twenty

724
00:45:19,400 --> 00:45:22,520
Speaker 3: three years too early. And I also made the mistake

725
00:45:22,600 --> 00:45:26,719
Speaker 3: of making it B to C, whereas that was a

726
00:45:26,800 --> 00:45:30,400
Speaker 3: huge mistake. Should have gone B to B because I

727
00:45:30,680 --> 00:45:34,560
Speaker 3: later learned, you know, I was a level playing field guy,

728
00:45:34,800 --> 00:45:37,880
Speaker 3: and like people can just buy their no loads and everything.

729
00:45:38,360 --> 00:45:41,560
Speaker 3: But the more the data presented itself to me, the

730
00:45:41,560 --> 00:45:45,520
Speaker 3: more I came over to the side where advisors are

731
00:45:46,320 --> 00:45:50,160
Speaker 3: earning every dollar you pay them because the results, the

732
00:45:50,200 --> 00:45:55,960
Speaker 3: outcomes were just so much better. So we started building

733
00:45:56,880 --> 00:46:01,120
Speaker 3: the tools that became Canvas. During the Great Financial Crisis,

734
00:46:01,160 --> 00:46:03,960
Speaker 3: I'm like, okay, we're probably not going to sell another

735
00:46:04,080 --> 00:46:07,880
Speaker 3: long only US stock portfolio over the next three years,

736
00:46:08,400 --> 00:46:13,120
Speaker 3: so let's really attack the data. Let's clean it. By

737
00:46:13,160 --> 00:46:16,160
Speaker 3: the way, really hate it by my research team for

738
00:46:16,239 --> 00:46:18,879
Speaker 3: that entire period, right because it's really.

739
00:46:18,680 --> 00:46:20,280
Speaker 2: My numbering bad.

740
00:46:20,960 --> 00:46:24,240
Speaker 3: But by the way, now that's a great use case

741
00:46:24,280 --> 00:46:28,439
Speaker 3: for AI. It can do it much faster. It can

742
00:46:28,520 --> 00:46:32,160
Speaker 3: do it. You know, you can free your staff to

743
00:46:32,280 --> 00:46:36,960
Speaker 3: not have to do that laborious, mind numbingly dull type

744
00:46:36,960 --> 00:46:40,000
Speaker 3: of work so that they can work on better research,

745
00:46:40,440 --> 00:46:45,080
Speaker 3: more interesting topics. But yeah, and as we were doing it,

746
00:46:45,400 --> 00:46:49,960
Speaker 3: and Patrick walked into my office and he's like, you know, Dad,

747
00:46:51,080 --> 00:46:53,719
Speaker 3: we he actually did say this to me. I know

748
00:46:53,800 --> 00:46:57,680
Speaker 3: it became lower, but he goes, we built the death

749
00:46:57,719 --> 00:47:00,640
Speaker 3: star to kill a mouse here. I'm like, what do

750
00:47:00,640 --> 00:47:05,400
Speaker 3: you mean. He goes, Well, our clients, the rich Holts

751
00:47:05,520 --> 00:47:09,319
Speaker 3: wealth managements of the world could could use this and

752
00:47:09,360 --> 00:47:13,760
Speaker 3: it would be amazing for their business. Now, obviously, because

753
00:47:13,960 --> 00:47:18,120
Speaker 3: I had already tried with metfolio, I was like, let's

754
00:47:18,200 --> 00:47:23,800
Speaker 3: do it. So yeah. Building out the actual technology though,

755
00:47:24,239 --> 00:47:26,920
Speaker 3: that was a multi year effort. It took us a

756
00:47:26,960 --> 00:47:27,439
Speaker 3: long time.

757
00:47:27,600 --> 00:47:32,000
Speaker 2: But what you know, our mutual friend Dave Knadig has

758
00:47:32,080 --> 00:47:36,680
Speaker 2: been a supporter of direct indexing and ETFs obviously for

759
00:47:36,680 --> 00:47:41,080
Speaker 2: a long time, and my complaints were always, yeah, but

760
00:47:41,520 --> 00:47:44,880
Speaker 2: it's cludgy. Yeah, but I get these two hundred page,

761
00:47:45,440 --> 00:47:49,759
Speaker 2: you know, quarterly appointments and it's not very fine tunable.

762
00:47:49,920 --> 00:47:53,719
Speaker 2: And and I'll never forget when Batana came back to

763
00:47:53,760 --> 00:47:58,000
Speaker 2: the office having seen a demo. If he had hair,

764
00:47:58,239 --> 00:48:01,000
Speaker 2: it would have been on fire. That's what it was.

765
00:48:01,200 --> 00:48:02,920
Speaker 2: That's what it was like. He was jumping up and

766
00:48:02,960 --> 00:48:06,040
Speaker 2: down and just the demo is like, oh, wow, this

767
00:48:06,200 --> 00:48:10,040
Speaker 2: is slick, and wow, this really looks good. I can't

768
00:48:10,080 --> 00:48:14,840
Speaker 2: believe it's that definable. It's that user and like the

769
00:48:15,160 --> 00:48:18,040
Speaker 2: deeper you went into it, it was just every step

770
00:48:18,040 --> 00:48:20,560
Speaker 2: along the way there was a ton of stuff. What

771
00:48:20,800 --> 00:48:25,000
Speaker 2: was the vision when you originally were building this, was it, Hey,

772
00:48:25,080 --> 00:48:27,680
Speaker 2: let's pump this up and sell it, because I know

773
00:48:27,800 --> 00:48:30,480
Speaker 2: you guys never were really shopping this around. Yeah, it

774
00:48:30,640 --> 00:48:31,720
Speaker 2: kind of fell out of the blue.

775
00:48:31,880 --> 00:48:34,440
Speaker 3: Yeah, No, we it was not to pup it up

776
00:48:34,440 --> 00:48:37,719
Speaker 3: and sell it at all. It was we wanted to

777
00:48:37,800 --> 00:48:42,600
Speaker 3: have the absolute best software for the way we managed money.

778
00:48:43,360 --> 00:48:47,160
Speaker 3: And there was really nothing off the shelf that suited

779
00:48:47,160 --> 00:48:52,000
Speaker 3: our needs, and so we put on a pretty significant

780
00:48:52,400 --> 00:48:59,040
Speaker 3: developer team that had background in portfolio management. This is

781
00:48:59,160 --> 00:49:03,520
Speaker 3: key the problem with just a technologist trying to come

782
00:49:03,520 --> 00:49:07,200
Speaker 3: into our industry and build a platform like this. They

783
00:49:07,239 --> 00:49:11,600
Speaker 3: don't know all of the junk that goes on underneath.

784
00:49:11,760 --> 00:49:15,760
Speaker 3: We do because that's what we do, right. They don't

785
00:49:15,800 --> 00:49:19,880
Speaker 3: think about, well, who's the clearance agent, who's the custodian,

786
00:49:20,000 --> 00:49:23,280
Speaker 3: all of those types of things. So by actually having

787
00:49:23,360 --> 00:49:28,200
Speaker 3: people very very with very deep domain knowledge in asset

788
00:49:28,320 --> 00:49:31,920
Speaker 3: management the way it really works, that was a huge

789
00:49:31,960 --> 00:49:34,680
Speaker 3: help in us building out the software. But the original

790
00:49:34,680 --> 00:49:37,600
Speaker 3: thing Barry was, we wanted to serve you our clients

791
00:49:37,680 --> 00:49:42,560
Speaker 3: better and faster. And then when we saw that the customization,

792
00:49:43,360 --> 00:49:47,200
Speaker 3: that the tax management, that all of that would be

793
00:49:47,280 --> 00:49:52,520
Speaker 3: really appealing to not only our advisors but to our advisors' clients,

794
00:49:53,080 --> 00:49:57,200
Speaker 3: that's when it clicked Wow, like kind of our aws

795
00:49:57,280 --> 00:50:01,120
Speaker 3: moment was huh, we think other people might really like

796
00:50:01,160 --> 00:50:01,680
Speaker 3: this too.

797
00:50:02,120 --> 00:50:05,640
Speaker 2: No. Absolutely, the tax side of it was a game changer.

798
00:50:06,360 --> 00:50:10,440
Speaker 2: And when I was doing some recent research for another project,

799
00:50:10,920 --> 00:50:14,640
Speaker 2: I just started going through the list of trillion dollar

800
00:50:14,760 --> 00:50:18,960
Speaker 2: asset managers that either bought or built a direct index, sir.

801
00:50:19,400 --> 00:50:21,720
Speaker 2: And when you see ten or twenty of the largest

802
00:50:21,760 --> 00:50:25,319
Speaker 2: farms in the world or moving in the same direction, hey,

803
00:50:25,400 --> 00:50:26,359
Speaker 2: pay attention to something.

804
00:50:26,600 --> 00:50:28,800
Speaker 3: Customization is the future.

805
00:50:28,680 --> 00:50:29,520
Speaker 2: We are leaving.

806
00:50:29,680 --> 00:50:34,360
Speaker 3: We are leaving one size fits all, and the ability

807
00:50:34,520 --> 00:50:40,360
Speaker 3: to customize your client's portfolio down to their specific needs

808
00:50:40,640 --> 00:50:44,359
Speaker 3: is really it really is a game changer, especially on

809
00:50:44,520 --> 00:50:47,320
Speaker 3: the tax alfa that you can generate.

810
00:50:48,440 --> 00:50:51,839
Speaker 2: So you mentioned your AI earlier. I know you've been

811
00:50:51,880 --> 00:50:55,200
Speaker 2: appointed chairman of the board at Stability AI. Up to

812
00:50:55,760 --> 00:50:58,400
Speaker 2: I was, so that's no longer. So let me rephrase

813
00:50:58,440 --> 00:51:02,560
Speaker 2: that question mentioned AI earlier. How do you see AI

814
00:51:02,680 --> 00:51:08,560
Speaker 2: transforming either the investment management industry or venture capital? What

815
00:51:08,719 --> 00:51:11,120
Speaker 2: is the role of AI going to be going forward?

816
00:51:12,120 --> 00:51:16,920
Speaker 3: I truly believe that AI is the most powerful technology

817
00:51:17,120 --> 00:51:20,760
Speaker 3: that has ever come on the scene during my career, wow,

818
00:51:21,239 --> 00:51:30,800
Speaker 3: and it is going to be used primarily for replacing arduous, boring,

819
00:51:31,160 --> 00:51:36,080
Speaker 3: mind numbing type activities that humans are currently doing the

820
00:51:36,200 --> 00:51:39,680
Speaker 3: AI can do. Let me give you an example in

821
00:51:39,760 --> 00:51:44,399
Speaker 3: our publisher. If you work with a legacy publisher, you're

822
00:51:44,400 --> 00:51:46,800
Speaker 3: done with your manuscript, you sent it and you probably

823
00:51:46,840 --> 00:51:51,880
Speaker 3: had this experience right typos, typos, typos, but it didn't

824
00:51:51,920 --> 00:51:54,400
Speaker 3: get back to you, probably for a couple of months.

825
00:51:55,560 --> 00:51:58,719
Speaker 3: With infinite books, it'll probably get back to you the

826
00:51:58,760 --> 00:52:03,560
Speaker 3: next day because we have an AI that takes all

827
00:52:03,600 --> 00:52:08,600
Speaker 3: of those typos, fixes them, it prints it in Galley format.

828
00:52:08,680 --> 00:52:12,240
Speaker 3: Because non authors might not believe this, but an author,

829
00:52:12,320 --> 00:52:14,640
Speaker 3: when they see their work in the way it's going

830
00:52:14,719 --> 00:52:17,200
Speaker 3: to look as a book, it kind of freaks you out.

831
00:52:17,560 --> 00:52:20,799
Speaker 3: You start reading it differently, very much so. And so

832
00:52:21,120 --> 00:52:23,480
Speaker 3: we'll have that that will go back to the author.

833
00:52:23,640 --> 00:52:27,960
Speaker 3: All the typos will be gone, and any incongruity in

834
00:52:28,080 --> 00:52:31,760
Speaker 3: the manuscript will be noted. We won't touch it because

835
00:52:31,760 --> 00:52:33,879
Speaker 3: we want to leave it to the author to make

836
00:52:33,920 --> 00:52:37,240
Speaker 3: whatever changes they want. But if it says, hey, Barry,

837
00:52:37,680 --> 00:52:41,239
Speaker 3: in chapter one you said this, but in chapter four

838
00:52:41,360 --> 00:52:45,200
Speaker 3: you said the exact opposite thing, which one do you want?

839
00:52:45,400 --> 00:52:51,160
Speaker 3: And then finally we have plagiarize of routines where you know,

840
00:52:51,280 --> 00:52:54,200
Speaker 3: a million little pieces where you have to go on

841
00:52:54,320 --> 00:52:58,880
Speaker 3: and get scolded by Oprah. Will should never happen again

842
00:52:59,360 --> 00:53:05,839
Speaker 3: because some times people aren't pleasiarizing intentionally. They are maybe

843
00:53:05,920 --> 00:53:08,400
Speaker 3: doing it for a memory something they read, et cetera.

844
00:53:09,000 --> 00:53:12,719
Speaker 3: And wouldn't it be far better for everyone concerned if

845
00:53:12,760 --> 00:53:15,120
Speaker 3: you just bring that to the author's attention and they

846
00:53:15,120 --> 00:53:15,759
Speaker 3: can fix it.

847
00:53:16,000 --> 00:53:18,560
Speaker 2: So you have a lot of interest. So it's not

848
00:53:18,760 --> 00:53:25,520
Speaker 2: just venture investing, it's AI, it's publishing, it's fellowships where

849
00:53:25,560 --> 00:53:30,080
Speaker 2: you find somebody who you sponsor for a year and

850
00:53:30,560 --> 00:53:33,799
Speaker 2: you know, sort of a MacArthur genius grant. Where can

851
00:53:33,840 --> 00:53:35,880
Speaker 2: you go? What can you do with this? You know,

852
00:53:36,680 --> 00:53:38,960
Speaker 2: where do you really focus your time and effort? What

853
00:53:39,280 --> 00:53:40,319
Speaker 2: most interests you?

854
00:53:41,640 --> 00:53:45,320
Speaker 3: So I'm going to cop out and give you the answer.

855
00:53:45,440 --> 00:53:48,920
Speaker 3: All of it interests me, Barrier, Okay, we have it true.

856
00:53:49,440 --> 00:53:52,760
Speaker 3: But I'm very lucky in that we have a senior

857
00:53:52,800 --> 00:53:55,320
Speaker 3: person at the head of each one of these verticals,

858
00:53:56,640 --> 00:54:00,000
Speaker 3: and so I let them. I'm very big on higher

859
00:54:00,040 --> 00:54:04,000
Speaker 3: vring people with super high agency and who are really

860
00:54:04,000 --> 00:54:07,640
Speaker 3: really bright, mostly brighter than me, and I let them

861
00:54:08,520 --> 00:54:11,680
Speaker 3: run with what they want to do. They always keep

862
00:54:11,680 --> 00:54:14,799
Speaker 3: me informed as to hey, we might be trying this

863
00:54:14,960 --> 00:54:19,840
Speaker 3: big change, and then I sign off there. But I mean, basically,

864
00:54:19,920 --> 00:54:24,200
Speaker 3: the verticals were all areas that I loved. I love movies,

865
00:54:24,320 --> 00:54:28,360
Speaker 3: I love books, I love media, I love podcasts, etc.

866
00:54:29,400 --> 00:54:32,640
Speaker 3: And they were also areas where I felt that there

867
00:54:32,719 --> 00:54:37,200
Speaker 3: was a lot of arbitrage opportunity available. For instance, like

868
00:54:37,440 --> 00:54:41,919
Speaker 3: most legacy publishers are operating under best principles, but they're

869
00:54:41,960 --> 00:54:45,960
Speaker 3: operating under the best principles from nineteen twenty five, not

870
00:54:46,160 --> 00:54:50,680
Speaker 3: twenty twenty five. And so there is so much that

871
00:54:50,760 --> 00:54:54,880
Speaker 3: can be improved in the process to make the author

872
00:54:55,040 --> 00:54:58,480
Speaker 3: a good deal, happier, to make the reading public have

873
00:54:59,000 --> 00:55:02,840
Speaker 3: access to their own authors work sooner than they might otherwise.

874
00:55:03,280 --> 00:55:08,799
Speaker 3: But also because of the technology, we are able to

875
00:55:08,960 --> 00:55:13,120
Speaker 3: offer a much better deal to our authors. Our authors

876
00:55:13,200 --> 00:55:18,920
Speaker 3: typically will take seventy percent of the royalties after the

877
00:55:18,960 --> 00:55:23,600
Speaker 3: costs have been cleared, so we can still make a

878
00:55:23,719 --> 00:55:27,240
Speaker 3: great deal of money at the thirty percent that we maintain.

879
00:55:27,719 --> 00:55:32,879
Speaker 3: But there's also cross polonization. Right, there's a great podcaster

880
00:55:33,239 --> 00:55:36,120
Speaker 3: who is going to be a great author. There is

881
00:55:36,200 --> 00:55:39,600
Speaker 3: a great author who might be a great podcaster or

882
00:55:40,080 --> 00:55:42,279
Speaker 3: will do the whole thing for them. We'll set them

883
00:55:42,320 --> 00:55:45,600
Speaker 3: up on a sub stack, we'll give them a podcast,

884
00:55:45,800 --> 00:55:50,040
Speaker 3: we'll publish their book. What we really want to focus

885
00:55:50,120 --> 00:55:54,640
Speaker 3: on is ideas that ended up in slush piles in

886
00:55:54,800 --> 00:55:58,280
Speaker 3: days of yore. A lot of great writing is there

887
00:55:58,880 --> 00:56:01,720
Speaker 3: and so we want to be able to not only

888
00:56:01,760 --> 00:56:03,680
Speaker 3: see that, but publish the best of it.

889
00:56:03,960 --> 00:56:08,720
Speaker 2: So you're publishing books, you're hosting your own podcast, Infinite Loops.

890
00:56:09,280 --> 00:56:14,600
Speaker 2: I'm kind of intrigued by the idea of investing in movies,

891
00:56:15,320 --> 00:56:19,920
Speaker 2: which tend to be a black hole of losses. You know,

892
00:56:20,000 --> 00:56:24,839
Speaker 2: it's like restaurants, plays, and films tell us what you're

893
00:56:24,840 --> 00:56:26,400
Speaker 2: doing cinematically.

894
00:56:26,480 --> 00:56:32,080
Speaker 3: So cinematically we started our little mantra is Crawl Walk Run,

895
00:56:32,840 --> 00:56:36,360
Speaker 3: and so, you know, it was odd for me because

896
00:56:36,480 --> 00:56:39,480
Speaker 3: you know, I had a very established reputation in asset management,

897
00:56:39,880 --> 00:56:44,200
Speaker 3: and here I'm the total underdog. I mean, like we

898
00:56:44,400 --> 00:56:48,000
Speaker 3: are the rebel Alliance, if you will, going up against

899
00:56:48,040 --> 00:56:52,680
Speaker 3: some very very tough competitors. So on the film side,

900
00:56:52,800 --> 00:56:57,360
Speaker 3: we started with documentaries. Uh huh. One of our first

901
00:56:57,400 --> 00:57:01,920
Speaker 3: Flip Side, actually premiered at the Toronto Film Festival, got

902
00:57:02,000 --> 00:57:07,879
Speaker 3: amazing reviews, got bought out by a distributor, and so

903
00:57:08,000 --> 00:57:11,680
Speaker 3: that went very very well. We are now commissioning documentaries

904
00:57:12,320 --> 00:57:16,120
Speaker 3: with some younger talent that isn't really bound up by

905
00:57:16,120 --> 00:57:19,560
Speaker 3: the way Hollywood currently does things.

906
00:57:19,960 --> 00:57:22,320
Speaker 2: And get a little more nimble, like.

907
00:57:23,880 --> 00:57:27,600
Speaker 3: Much more nimble, much faster, much more responsive.

908
00:57:27,880 --> 00:57:31,680
Speaker 2: Someone had shot a film on an iPhone sort of

909
00:57:31,800 --> 00:57:35,040
Speaker 2: is a little bit of a publicity stunt, I want

910
00:57:35,040 --> 00:57:38,680
Speaker 2: to say, eight or ten years ago, But that's really

911
00:57:39,040 --> 00:57:40,280
Speaker 2: very feasible today, isn't.

912
00:57:40,360 --> 00:57:43,800
Speaker 3: Oh absolutely, And when you add in all of the

913
00:57:44,040 --> 00:57:47,840
Speaker 3: things that ai I mentioned, all of the laborious stuff

914
00:57:47,840 --> 00:57:50,919
Speaker 3: that you get rid of with publishing, same is true

915
00:57:50,920 --> 00:57:54,520
Speaker 3: in film. So this is going to sound weird, but

916
00:57:54,760 --> 00:57:58,000
Speaker 3: you know what eats up like huge amounts of time

917
00:57:58,480 --> 00:58:03,800
Speaker 3: and is ridiculous boring color matching. Well, when things are

918
00:58:04,040 --> 00:58:07,840
Speaker 3: filmed over a variety of days or locations or what

919
00:58:08,040 --> 00:58:12,280
Speaker 3: have you. One day's cloudy, one day's sunny, you've got

920
00:58:12,360 --> 00:58:15,880
Speaker 3: to have that match up so that your film appears

921
00:58:16,000 --> 00:58:19,880
Speaker 3: of a piece. So it's more than just continuity. Absolutely,

922
00:58:19,920 --> 00:58:24,200
Speaker 3: the next step they step beyond that, and there's just

923
00:58:24,360 --> 00:58:29,320
Speaker 3: so much that can be done with the visual part,

924
00:58:29,400 --> 00:58:33,960
Speaker 3: with the editing ais that we have always going to

925
00:58:33,960 --> 00:58:37,240
Speaker 3: have a human editor, but we are giving them tools

926
00:58:37,640 --> 00:58:42,040
Speaker 3: that just makes them able to do their job in

927
00:58:42,440 --> 00:58:44,920
Speaker 3: a much more creative way because they don't have to

928
00:58:44,920 --> 00:58:48,520
Speaker 3: take that hour or two hour and do the Niggadly,

929
00:58:49,040 --> 00:58:51,120
Speaker 3: I've got to move this to here, and that to

930
00:58:51,200 --> 00:58:55,040
Speaker 3: their They literally can press a button and it happens.

931
00:58:55,680 --> 00:59:00,080
Speaker 3: So what we're finding is a great amount of the

932
00:59:00,160 --> 00:59:07,360
Speaker 3: workflows in these industries are time consuming, boring, and just

933
00:59:07,920 --> 00:59:12,120
Speaker 3: like they take forever, and we can fix that to

934
00:59:12,160 --> 00:59:16,160
Speaker 3: the point where they no longer take forever. And the

935
00:59:16,200 --> 00:59:20,040
Speaker 3: people were working with absolutely love it because they can

936
00:59:20,040 --> 00:59:24,840
Speaker 3: spend their time making that edit like supreme right, we're

937
00:59:24,840 --> 00:59:29,280
Speaker 3: giving them back time that they can use artistically.

938
00:59:30,160 --> 00:59:36,160
Speaker 2: So so many people have been pessimistic about AI. It's

939
00:59:36,200 --> 00:59:40,280
Speaker 2: gonna kill jobs, it's gonna damage society. You won't know

940
00:59:40,280 --> 00:59:43,320
Speaker 2: what to do to believe, to trust, we'll all be

941
00:59:43,360 --> 00:59:45,720
Speaker 2: out of work. I don't get the sense that you're

942
00:59:45,760 --> 00:59:48,840
Speaker 2: looking at AI that way. You seem to think that

943
00:59:49,000 --> 00:59:52,680
Speaker 2: this or sounds like you're finding this is just an

944
00:59:52,720 --> 00:59:56,040
Speaker 2: incredibly useful tool and it's gonna make all of us

945
00:59:56,200 --> 00:59:57,800
Speaker 2: more productive and more creative.

946
00:59:57,840 --> 01:00:02,160
Speaker 3: Precisely, you know, we always frightened when some new technology

947
01:00:02,200 --> 01:00:04,600
Speaker 3: comes on the scene. And by the way, this goes

948
01:00:04,640 --> 01:00:08,000
Speaker 3: back forever, like when the Latites right, the Ludites right,

949
01:00:08,040 --> 01:00:11,520
Speaker 3: It goes back to Ned Ludd and who broke up

950
01:00:11,560 --> 01:00:13,960
Speaker 3: all the machines because they were going to take their jobs.

951
01:00:14,040 --> 01:00:16,320
Speaker 3: While he ended up working on one of those looms,

952
01:00:16,320 --> 01:00:19,640
Speaker 3: and he vastly preferred his new job because he didn't

953
01:00:19,640 --> 01:00:22,600
Speaker 3: have to do it the old horrible way. Same thing's

954
01:00:22,640 --> 01:00:25,720
Speaker 3: going to happen here, but it happens all the time, right,

955
01:00:25,840 --> 01:00:30,000
Speaker 3: So when records first came out, you know that symphony

956
01:00:30,160 --> 01:00:35,680
Speaker 3: orchestras took full page ads in newspapers saying that isn't

957
01:00:35,760 --> 01:00:39,640
Speaker 3: real music. Real music is live and you have to

958
01:00:39,760 --> 01:00:44,200
Speaker 3: hear it live or you're listening to a counterfeit. Right,

959
01:00:44,360 --> 01:00:49,360
Speaker 3: So when this type of advance comes along, you always

960
01:00:49,520 --> 01:00:55,040
Speaker 3: axiomatically people get freaked out. I think, you know, AI

961
01:00:55,320 --> 01:00:58,080
Speaker 3: is not going to take your job. A human being

962
01:00:58,360 --> 01:01:02,520
Speaker 3: using the AI tool will because they are going to

963
01:01:02,560 --> 01:01:06,280
Speaker 3: be so much more proficient at what they're doing. They're

964
01:01:06,280 --> 01:01:09,240
Speaker 3: going to have so much more time to focus on

965
01:01:09,320 --> 01:01:13,040
Speaker 3: the really high value stuff and not have to worry

966
01:01:13,160 --> 01:01:15,880
Speaker 3: with all the stuff that you know they had to

967
01:01:15,880 --> 01:01:18,760
Speaker 3: do in the past. But now we can automate it

968
01:01:18,800 --> 01:01:24,040
Speaker 3: through AI workflows. So I subscribe to what they call

969
01:01:24,120 --> 01:01:28,160
Speaker 3: the Sentataur model. You remember the mythical be sure half horse,

970
01:01:28,200 --> 01:01:32,240
Speaker 3: half man. That's what is going to happen with AI.

971
01:01:32,520 --> 01:01:37,400
Speaker 3: It's going to be AI plus human being. That's where

972
01:01:37,440 --> 01:01:40,360
Speaker 3: all the great stuff is going to come. Right now,

973
01:01:40,840 --> 01:01:44,360
Speaker 3: we're going to see a tsunami of slop that's going

974
01:01:44,440 --> 01:01:47,200
Speaker 3: to be just AI generated and people will think, oh,

975
01:01:47,200 --> 01:01:51,960
Speaker 3: that's good enough, right, and so going forward, you can

976
01:01:52,080 --> 01:01:56,880
Speaker 3: create a huge edge by having good taste and curating

977
01:01:56,920 --> 01:02:00,280
Speaker 3: itll but I can guarantee you almost all of that

978
01:02:00,520 --> 01:02:05,360
Speaker 3: is going to be human using AI as a tool

979
01:02:05,840 --> 01:02:10,200
Speaker 3: to make their jobs better, easier, more creative. The way

980
01:02:10,240 --> 01:02:12,480
Speaker 3: I look at it is, you know, Steve Jobs famously

981
01:02:12,600 --> 01:02:16,240
Speaker 3: said computers were bicycles for your mind. AI is a

982
01:02:16,480 --> 01:02:18,320
Speaker 3: rocket ship for your mind. Huh.

983
01:02:18,760 --> 01:02:21,640
Speaker 2: I like the way you phrase that. You know. Someone

984
01:02:21,840 --> 01:02:24,800
Speaker 2: once asked me, you know what's the secret to putting

985
01:02:24,880 --> 01:02:30,760
Speaker 2: out the daily reads? And my answer was curate viciously exactly.

986
01:02:30,800 --> 01:02:33,600
Speaker 2: And you you know, AI. I don't think in our

987
01:02:33,720 --> 01:02:37,240
Speaker 2: lifetime and probably not our kids' lifetime, is going to

988
01:02:37,280 --> 01:02:40,280
Speaker 2: reach the point where it can be a taste maker.

989
01:02:40,720 --> 01:02:44,520
Speaker 3: We believe, passionately believe that if you have good taste

990
01:02:44,680 --> 01:02:50,040
Speaker 3: and you are a great curator, your future looks incredible

991
01:02:50,640 --> 01:02:53,520
Speaker 3: because you'll be able to use these tools. You won't

992
01:02:53,520 --> 01:02:55,560
Speaker 3: have to spend all the time that you used to

993
01:02:56,360 --> 01:02:58,480
Speaker 3: and that's going to even make It's going to be

994
01:02:58,520 --> 01:03:01,280
Speaker 3: the rocket ship to give you get you to the

995
01:03:01,320 --> 01:03:03,640
Speaker 3: next level of your good taste and curation.

996
01:03:03,960 --> 01:03:06,360
Speaker 2: So a couple more questions before we get to our

997
01:03:06,480 --> 01:03:11,360
Speaker 2: final question, and that is first, I have to ask

998
01:03:11,480 --> 01:03:16,120
Speaker 2: you about the O'Shaughnessy Fellowship, what I've been calling your

999
01:03:16,320 --> 01:03:20,520
Speaker 2: MacArthur Reward. Tell us a little bit about the support

1000
01:03:20,760 --> 01:03:25,240
Speaker 2: you offer for young entrepreneurs. What inspired you to start

1001
01:03:25,320 --> 01:03:29,080
Speaker 2: this program. I know we've had at least one O'shaughnessee

1002
01:03:29,520 --> 01:03:33,280
Speaker 2: Fellowship person, Kyle Scanlon, as a guest on the show,

1003
01:03:34,320 --> 01:03:37,720
Speaker 2: maybe one other. I'll have to go through the list

1004
01:03:38,240 --> 01:03:41,600
Speaker 2: and see what motivated you to create this program and

1005
01:03:41,880 --> 01:03:42,840
Speaker 2: how has it been running.

1006
01:03:43,280 --> 01:03:48,760
Speaker 3: So it's running really, really well. We have the applications.

1007
01:03:48,880 --> 01:03:52,960
Speaker 3: We're now in our third year. The applications are much

1008
01:03:53,000 --> 01:03:56,240
Speaker 3: more numerous and the quality of the applicant I mean

1009
01:03:56,880 --> 01:04:01,880
Speaker 3: very literally. If I could, would give most of our fellowships.

1010
01:04:02,840 --> 01:04:06,720
Speaker 3: But the real reason that I did it was because

1011
01:04:06,840 --> 01:04:11,160
Speaker 3: I had become convinced that geography, time and space have

1012
01:04:11,240 --> 01:04:14,320
Speaker 3: all collapsed and in the old days, you know, you

1013
01:04:14,400 --> 01:04:16,840
Speaker 3: and I would know each other still because we both

1014
01:04:16,920 --> 01:04:19,000
Speaker 3: live here in New York and we both are in

1015
01:04:19,080 --> 01:04:23,920
Speaker 3: the same business. But other than that, like prior to

1016
01:04:24,160 --> 01:04:27,560
Speaker 3: the Internet, prior to what I call the human Colossus,

1017
01:04:27,800 --> 01:04:32,960
Speaker 3: we couldn't find those geniuses elsewhere. We can now, and

1018
01:04:33,400 --> 01:04:37,920
Speaker 3: I believe that it is absolutely imperative to show the

1019
01:04:37,960 --> 01:04:42,240
Speaker 3: world that there are a ton of brilliant people in

1020
01:04:42,320 --> 01:04:46,320
Speaker 3: this world, many of them young, who don't have an

1021
01:04:46,360 --> 01:04:50,720
Speaker 3: opportunity to demonstrate what they have to offer to the world.

1022
01:04:51,240 --> 01:04:54,960
Speaker 3: Now we can find and more importantly, fund them. And

1023
01:04:55,040 --> 01:04:58,920
Speaker 3: the way we do it is it's totally no strings funding.

1024
01:04:59,240 --> 01:05:02,320
Speaker 3: So if you're a fellow, you get one hundred thousand

1025
01:05:02,320 --> 01:05:05,520
Speaker 3: dollars over a one year period to work on your project.

1026
01:05:05,840 --> 01:05:08,360
Speaker 3: If you're a grantee, you get ten thousand. We have

1027
01:05:08,400 --> 01:05:14,120
Speaker 3: obviously many more grantees than we have fellows, but just

1028
01:05:14,240 --> 01:05:18,840
Speaker 3: the blossoming of the way the groups work together. Like

1029
01:05:19,040 --> 01:05:22,320
Speaker 3: I thought that it would take us at least five

1030
01:05:22,400 --> 01:05:27,040
Speaker 3: years to build like a really cool network of super smart,

1031
01:05:27,120 --> 01:05:31,800
Speaker 3: switched on people, it's already happened. We have we have

1032
01:05:32,280 --> 01:05:36,360
Speaker 3: in person meetings once a year, and the last one

1033
01:05:36,400 --> 01:05:39,320
Speaker 3: we had I'll just give you a quick example. We

1034
01:05:39,680 --> 01:05:42,720
Speaker 3: have a scientist who is developing an in home way

1035
01:05:42,760 --> 01:05:47,240
Speaker 3: to test your babies poop to make sure that it's okay.

1036
01:05:48,440 --> 01:05:52,200
Speaker 3: She had no idea how to market this. Another fellow

1037
01:05:52,280 --> 01:05:55,320
Speaker 3: was sitting right next to her. He's a writer, he's

1038
01:05:55,360 --> 01:05:59,160
Speaker 3: a thinker, and he knows all about this, and literally,

1039
01:06:00,120 --> 01:06:02,200
Speaker 3: or the course of an hour and a half, he

1040
01:06:02,320 --> 01:06:07,520
Speaker 3: gave her a completely different marketing plan that she adored.

1041
01:06:07,560 --> 01:06:10,280
Speaker 3: She came over to me and she said, I can't

1042
01:06:10,320 --> 01:06:13,800
Speaker 3: believe that in an hour and a half he totally

1043
01:06:13,880 --> 01:06:15,600
Speaker 3: changed the way I'm going to bring this to market.

1044
01:06:15,840 --> 01:06:16,560
Speaker 2: Huh.

1045
01:06:16,600 --> 01:06:21,880
Speaker 3: So the cross polonization and the synthesis of these great

1046
01:06:21,920 --> 01:06:25,959
Speaker 3: minds is really a thing to behold. I'm just very,

1047
01:06:26,080 --> 01:06:27,680
Speaker 3: very excited about what's coming out.

1048
01:06:27,960 --> 01:06:30,760
Speaker 2: And before we get to our favorite questions, I want

1049
01:06:30,800 --> 01:06:32,400
Speaker 2: to throw you a curveball.

1050
01:06:32,800 --> 01:06:33,320
Speaker 3: Curveball.

1051
01:06:33,600 --> 01:06:38,080
Speaker 2: So, since we first met back in a CNBC green

1052
01:06:38,160 --> 01:06:41,960
Speaker 2: room in the early two thousands, so a few decades ago,

1053
01:06:42,880 --> 01:06:46,880
Speaker 2: you've had a fairly unique perch on the world of

1054
01:06:47,040 --> 01:06:53,080
Speaker 2: finance and investing in asset management. How has financial media

1055
01:06:53,960 --> 01:06:57,960
Speaker 2: and asset management changed over the course of your career.

1056
01:06:58,360 --> 01:07:03,000
Speaker 3: Well, at the beginning of my career, kind of squawk

1057
01:07:03,040 --> 01:07:07,440
Speaker 3: box on CNBC was the gold standard and the format

1058
01:07:07,520 --> 01:07:10,680
Speaker 3: they used at that time. I used to co host

1059
01:07:10,680 --> 01:07:12,080
Speaker 3: with Marcain's All the Time.

1060
01:07:12,120 --> 01:07:13,080
Speaker 2: I've done a few times.

1061
01:07:13,120 --> 01:07:17,800
Speaker 3: Back then it was a three hour program in which

1062
01:07:18,000 --> 01:07:21,880
Speaker 3: the portfolio manager or these strategists that we were talking to,

1063
01:07:22,560 --> 01:07:28,640
Speaker 3: was given like twenty minutes to actually articulate their thesis

1064
01:07:28,680 --> 01:07:32,040
Speaker 3: about why they were bullish or bearish, why they liked

1065
01:07:32,040 --> 01:07:35,880
Speaker 3: this particular group or that particular group. So one of

1066
01:07:35,920 --> 01:07:40,200
Speaker 3: the things that I saw happening when that changed was

1067
01:07:41,200 --> 01:07:47,200
Speaker 3: we were not giving the audience like that kind of treatment,

1068
01:07:47,240 --> 01:07:50,919
Speaker 3: which is really really incredible treatment. It was a three

1069
01:07:51,000 --> 01:07:54,240
Speaker 3: hour period that gave you enough time to actually talk

1070
01:07:54,320 --> 01:07:59,000
Speaker 3: things out. Now what's happened. Podcasts like yours really have

1071
01:07:59,120 --> 01:08:04,040
Speaker 3: come along and you've replaced that aspect, And so you know,

1072
01:08:04,160 --> 01:08:09,280
Speaker 3: I would bemoan when I saw that happening with Squawk especially, Oh,

1073
01:08:09,360 --> 01:08:11,800
Speaker 3: I would really wish that they could return to the

1074
01:08:11,840 --> 01:08:15,640
Speaker 3: old format. But then you and many many other my

1075
01:08:15,800 --> 01:08:19,759
Speaker 3: son with as absolutely came in and filled the void.

1076
01:08:20,160 --> 01:08:25,360
Speaker 3: So I think what investors are able to get access

1077
01:08:25,439 --> 01:08:30,360
Speaker 3: to now is just it. Dwarfs are the early days

1078
01:08:30,360 --> 01:08:33,080
Speaker 3: when you and I met in that green room. They

1079
01:08:33,160 --> 01:08:36,720
Speaker 3: have so many podcasts they can choose from the can

1080
01:08:37,000 --> 01:08:40,960
Speaker 3: they can still watch financial media. Then there's the YouTube people.

1081
01:08:42,080 --> 01:08:47,000
Speaker 3: But like everything, you've got to aggressively curate somebody like you.

1082
01:08:47,000 --> 01:08:49,080
Speaker 3: You know, you're way up here and you're kind of

1083
01:08:49,120 --> 01:08:52,400
Speaker 3: the gold standard. But how many shows have you done?

1084
01:08:52,560 --> 01:08:54,799
Speaker 3: You you have proof of work.

1085
01:08:55,240 --> 01:08:58,599
Speaker 2: I'll tell you a funny story. So we're July will

1086
01:08:58,600 --> 01:09:03,680
Speaker 2: be an years. It's five hundred and fifty shows. The

1087
01:09:04,000 --> 01:09:06,360
Speaker 2: Origin story. I don't know if I ever told this

1088
01:09:06,600 --> 01:09:10,160
Speaker 2: on my own podcast. I'm pretty sure i've told it elsewhere.

1089
01:09:10,479 --> 01:09:15,439
Speaker 2: It's coming back from a conference in Vancouver, Canada, and

1090
01:09:15,520 --> 01:09:18,040
Speaker 2: I had to either change planes in Chicago or Montreal.

1091
01:09:18,120 --> 01:09:21,759
Speaker 2: I and remember coming back to New York and I'm

1092
01:09:21,880 --> 01:09:24,559
Speaker 2: in the lounge and I want to say it was

1093
01:09:24,600 --> 01:09:30,120
Speaker 2: CNBC and they were interviewing Bill Ackman. I could be wrong.

1094
01:09:30,160 --> 01:09:32,360
Speaker 2: Maybe it was Einhorn. I don't remember, but it was

1095
01:09:32,880 --> 01:09:36,479
Speaker 2: a fund manager like that who back then was not

1096
01:09:36,800 --> 01:09:38,800
Speaker 2: There's no Twitter, they weren't doing a lot of TV.

1097
01:09:39,520 --> 01:09:44,840
Speaker 2: They like, you really don't go on TV unless you

1098
01:09:45,479 --> 01:09:49,040
Speaker 2: were marketing or had a really good quarter. And I

1099
01:09:49,400 --> 01:09:52,920
Speaker 2: just remember hearing the worst like it was a five

1100
01:09:52,960 --> 01:09:55,439
Speaker 2: minute hit, not a twenty minute hit. That's right, And

1101
01:09:55,479 --> 01:09:58,679
Speaker 2: when you have five minutes, it's what's your favorite stocks,

1102
01:09:58,720 --> 01:10:00,519
Speaker 2: when the head gonna cut, where the dew going to

1103
01:10:00,560 --> 01:10:03,280
Speaker 2: be next year? Thanks for coming by, and the moment

1104
01:10:03,320 --> 01:10:06,639
Speaker 2: that guy walks out of the building. Those answers are stale.

1105
01:10:06,720 --> 01:10:11,000
Speaker 2: And so I was flying back after you changed planes.

1106
01:10:11,040 --> 01:10:13,600
Speaker 2: I bumped into a friend and I was kind of

1107
01:10:13,640 --> 01:10:16,960
Speaker 2: like grinding my teeth and he's like, what's on your mind?

1108
01:10:17,000 --> 01:10:20,160
Speaker 2: You look like you're annoyed, and I relate the story,

1109
01:10:20,720 --> 01:10:24,000
Speaker 2: and he said, what questions would you ask? And the

1110
01:10:24,120 --> 01:10:27,880
Speaker 2: questions we're about to ask I'm about to ask you

1111
01:10:28,560 --> 01:10:31,280
Speaker 2: those were some of the questions. Who are you? How'd

1112
01:10:31,280 --> 01:10:34,880
Speaker 2: you get that way? What are you reading? Who your mentors?

1113
01:10:34,960 --> 01:10:38,200
Speaker 2: How did you develop your philosophy? If you were giving

1114
01:10:38,200 --> 01:10:40,439
Speaker 2: me advice as a college grad, what would you tell

1115
01:10:40,479 --> 01:10:42,439
Speaker 2: me if I wanted to go, like just off the

1116
01:10:42,479 --> 01:10:46,800
Speaker 2: top of my head, sure, just because I wanted the

1117
01:10:46,840 --> 01:10:49,759
Speaker 2: person to have to use the word you used earlier,

1118
01:10:49,840 --> 01:10:55,080
Speaker 2: agency and control over the story, but also express what

1119
01:10:55,120 --> 01:10:59,160
Speaker 2: they've learned over the decade exactly, and thirty seconds doesn't

1120
01:10:59,200 --> 01:11:02,840
Speaker 2: give you that. So on that note, let's let's jump

1121
01:11:02,920 --> 01:11:07,160
Speaker 2: to our speed rounds, to our favorite questions that we

1122
01:11:07,320 --> 01:11:09,360
Speaker 2: ask all of our guests. I think this is probably

1123
01:11:09,400 --> 01:11:12,040
Speaker 2: the third or fourth time I've had you do these.

1124
01:11:12,120 --> 01:11:13,639
Speaker 3: I hope I don't give answer.

1125
01:11:13,720 --> 01:11:16,000
Speaker 2: Hey, listen, We'll have AI go through it and find

1126
01:11:16,040 --> 01:11:18,439
Speaker 2: out how you're how you're thinking has evolved.

1127
01:11:18,520 --> 01:11:19,439
Speaker 3: Let's there we go.

1128
01:11:19,520 --> 01:11:23,920
Speaker 2: I love that, right, So starting with what's keeping you

1129
01:11:24,080 --> 01:11:26,600
Speaker 2: entertain these days? What are you watching or listening to?

1130
01:11:27,000 --> 01:11:27,160
Speaker 1: So?

1131
01:11:27,920 --> 01:11:32,960
Speaker 3: Uh, mostly listening to the normal group of podcasts that

1132
01:11:33,200 --> 01:11:36,040
Speaker 3: you would yours, my son's, my own.

1133
01:11:37,240 --> 01:11:40,920
Speaker 2: But do you find listening to your own is a

1134
01:11:41,360 --> 01:11:44,400
Speaker 2: challenge in that it sucks up time that you can't

1135
01:11:44,400 --> 01:11:48,200
Speaker 2: listen to others, or you don't want to listen to

1136
01:11:48,240 --> 01:11:50,000
Speaker 2: somebody you're going to interview and you don't want someone

1137
01:11:50,040 --> 01:11:50,759
Speaker 2: else's questions.

1138
01:11:50,800 --> 01:11:55,200
Speaker 3: So my dirty little secret is that I very very

1139
01:11:56,160 --> 01:11:59,840
Speaker 3: seldomly listen to my own. I do read the transcripts

1140
01:12:00,560 --> 01:12:02,559
Speaker 3: just to make sure, Oh I really screwed that up.

1141
01:12:02,600 --> 01:12:03,160
Speaker 3: I got to fix that.

1142
01:12:03,280 --> 01:12:05,040
Speaker 2: Transcripts don't come across the same way.

1143
01:12:05,200 --> 01:12:08,000
Speaker 3: I know, I know, I know, but I prefer to

1144
01:12:08,040 --> 01:12:11,639
Speaker 3: give my active listening time to like your podcast and

1145
01:12:11,640 --> 01:12:16,599
Speaker 3: and Patrick's. In terms of reading, I continue to read

1146
01:12:17,120 --> 01:12:21,280
Speaker 3: very very broadly My favorite, uh sort of literary fiction

1147
01:12:21,360 --> 01:12:24,960
Speaker 3: author is David Mitchell, who wrote Cloud Atlas. Oh really,

1148
01:12:25,680 --> 01:12:26,519
Speaker 3: and I've.

1149
01:12:26,320 --> 01:12:28,200
Speaker 2: Started Reade into a movie. Yeah.

1150
01:12:28,280 --> 01:12:33,439
Speaker 3: Yeah, the book's much better than the movie. And I

1151
01:12:33,479 --> 01:12:34,920
Speaker 3: love Howard Bloom's work.

1152
01:12:35,439 --> 01:12:38,000
Speaker 2: You know, the He's Closing of the American Mind.

1153
01:12:38,080 --> 01:12:42,320
Speaker 3: No, no different guy, sounds like right. Howard is a

1154
01:12:42,479 --> 01:12:47,680
Speaker 3: very fun, eccentric genius who sort of started life as

1155
01:12:47,720 --> 01:12:50,439
Speaker 3: a scientist and now takes all of what he learned

1156
01:12:50,479 --> 01:12:53,519
Speaker 3: there and applies it to the social world or the

1157
01:12:53,520 --> 01:12:54,479
Speaker 3: business world.

1158
01:12:54,320 --> 01:12:56,920
Speaker 2: Closing of the American Mind, entertaining ourselves.

1159
01:12:57,479 --> 01:13:02,120
Speaker 3: One of his would be the Lucifer principle, about how

1160
01:13:02,280 --> 01:13:06,360
Speaker 3: all of our evolutionary things that are driving a lot

1161
01:13:06,400 --> 01:13:12,160
Speaker 3: of our actions have profound implications for markets, for societies,

1162
01:13:12,280 --> 01:13:15,479
Speaker 3: for all of these things. And like, he's got a

1163
01:13:15,479 --> 01:13:22,240
Speaker 3: great book caming Reimagining the Beast where he talks about capitalism, saying, hey,

1164
01:13:22,280 --> 01:13:26,280
Speaker 3: capitalism is hands down the winner, but we can still

1165
01:13:26,439 --> 01:13:30,000
Speaker 3: improve it, and we should improve it. And here's how

1166
01:13:30,280 --> 01:13:35,599
Speaker 3: I think we should. So love his work. Read pretty

1167
01:13:35,680 --> 01:13:38,559
Speaker 3: much any paper I can get my hands on having

1168
01:13:38,640 --> 01:13:43,559
Speaker 3: to do with advances in AI and and that sort

1169
01:13:43,600 --> 01:13:47,120
Speaker 3: of thing. For fun. I just saw the new Bob

1170
01:13:47,200 --> 01:13:54,160
Speaker 3: Dylan movie. Loved it and Complete Unknown, And I also

1171
01:13:54,360 --> 01:13:58,519
Speaker 3: love the way Timothy Challow may the lead in that.

1172
01:13:59,040 --> 01:14:01,920
Speaker 3: I loved his speech when he got up and said,

1173
01:14:01,920 --> 01:14:05,240
Speaker 3: you know what, I could say, oh shucks, and I'm nothing,

1174
01:14:05,560 --> 01:14:08,440
Speaker 3: but I want to tell you something. I am aspiring

1175
01:14:08,560 --> 01:14:11,960
Speaker 3: to greatness. I want to be great. And I love

1176
01:14:12,120 --> 01:14:15,599
Speaker 3: actually seeing the younger generation start saying things like that,

1177
01:14:15,760 --> 01:14:19,320
Speaker 3: because it's so for so often, you know, we we

1178
01:14:19,800 --> 01:14:25,200
Speaker 3: you know, wasn't really anything. Come on, false humility, false humility,

1179
01:14:25,280 --> 01:14:29,479
Speaker 3: just like it stands out, doesn't it jar when you

1180
01:14:29,560 --> 01:14:32,040
Speaker 3: hear it? And it's like when I heard him give

1181
01:14:32,080 --> 01:14:33,000
Speaker 3: that speech, I'm.

1182
01:14:32,840 --> 01:14:33,760
Speaker 2: Like, right on.

1183
01:14:34,200 --> 01:14:37,479
Speaker 3: That's where I love hearing from a young actor or

1184
01:14:37,520 --> 01:14:41,080
Speaker 3: a writer or whatever. I Hey, I aspire to this.

1185
01:14:41,520 --> 01:14:44,920
Speaker 2: Don't we all aspire to greatness? Or we should, like

1186
01:14:44,960 --> 01:14:49,719
Speaker 2: you get one run, make it make it worth.

1187
01:14:49,520 --> 01:14:52,439
Speaker 3: Something, make it worthwhile. And so I was very happy

1188
01:14:52,479 --> 01:14:56,200
Speaker 3: to see that again just for total fun. I love

1189
01:14:56,280 --> 01:15:00,400
Speaker 3: Billy Bob Thornton. So we really enjoyed Land. Man.

1190
01:15:01,240 --> 01:15:03,360
Speaker 2: You know, you're like the third or fourth person who

1191
01:15:03,400 --> 01:15:05,280
Speaker 2: told me how much they love that, sir.

1192
01:15:05,520 --> 01:15:10,240
Speaker 3: It is so much. It's just fun and so You're

1193
01:15:10,240 --> 01:15:13,240
Speaker 3: probably not gonna learn a lot by watching it. Other

1194
01:15:13,360 --> 01:15:16,559
Speaker 3: than that Billie Bob Thornton choose up every scene that

1195
01:15:16,600 --> 01:15:19,040
Speaker 3: he appears in. He's such a good actor.

1196
01:15:19,000 --> 01:15:22,000
Speaker 2: Always is every time I see him me too. He's

1197
01:15:22,040 --> 01:15:25,880
Speaker 2: a delight. You know. You have such an interesting background.

1198
01:15:26,560 --> 01:15:30,759
Speaker 2: I'm curious if you had any mentors help shape your career.

1199
01:15:31,400 --> 01:15:35,720
Speaker 3: I did. I had a gentleman who was when I

1200
01:15:35,760 --> 01:15:39,200
Speaker 3: was very, very young. I'm not gonna mention his name

1201
01:15:39,320 --> 01:15:44,559
Speaker 3: because some of his kids might be listening, but we'll

1202
01:15:44,600 --> 01:15:48,920
Speaker 3: go with Jim. He was also a Jim and he

1203
01:15:49,000 --> 01:15:53,519
Speaker 3: probably did more for me when I was young and

1204
01:15:53,560 --> 01:15:59,360
Speaker 3: filled with you know, vinegar and very definitive beliefs. And

1205
01:15:59,720 --> 01:16:02,640
Speaker 3: I'll tell you all, I'm going to proselytize this is

1206
01:16:02,680 --> 01:16:05,519
Speaker 3: the way to do it. And he was really really

1207
01:16:05,560 --> 01:16:09,080
Speaker 3: good at saying, Uh, Jim, you might want to take

1208
01:16:09,120 --> 01:16:11,719
Speaker 3: that a step back, because what do you really want?

1209
01:16:12,160 --> 01:16:15,160
Speaker 3: I want people to know about this, Okay, but what's

1210
01:16:15,240 --> 01:16:19,559
Speaker 3: the broader implication here? Process over outcome? Okay, Well, why

1211
01:16:19,560 --> 01:16:21,760
Speaker 3: did you talk a little bit more about that? Why

1212
01:16:21,760 --> 01:16:24,320
Speaker 3: don't you talk about the way that people can actually

1213
01:16:24,479 --> 01:16:27,920
Speaker 3: take what you're saying to them and make them useful

1214
01:16:27,960 --> 01:16:32,639
Speaker 3: in their own life. So he was an amazing mentor

1215
01:16:32,720 --> 01:16:36,679
Speaker 3: to me because he was very patient, wicked sense of humor,

1216
01:16:38,240 --> 01:16:42,160
Speaker 3: and always good at reminding me that you might want

1217
01:16:42,200 --> 01:16:43,639
Speaker 3: to take it back an ouch or two.

1218
01:16:45,200 --> 01:16:48,599
Speaker 2: That's great. Let's you mention a few books, any other

1219
01:16:48,640 --> 01:16:50,840
Speaker 2: favorites you want to mention before we get to our

1220
01:16:51,560 --> 01:16:53,360
Speaker 2: favorite questions.

1221
01:16:53,240 --> 01:16:54,720
Speaker 1: The the what?

1222
01:16:55,040 --> 01:16:59,880
Speaker 3: Let me reference our infinite books. We have a list

1223
01:17:00,160 --> 01:17:02,599
Speaker 3: that you can get anywhere. You can go to Twitter,

1224
01:17:02,680 --> 01:17:05,519
Speaker 3: you can go to our substack, and it's kind of

1225
01:17:05,560 --> 01:17:08,720
Speaker 3: our seminal books, you know, books like the Beginning of

1226
01:17:08,760 --> 01:17:12,919
Speaker 3: Infinity by David Deutsch I think is a masterpiece. Beginning

1227
01:17:12,920 --> 01:17:16,840
Speaker 3: of Infinitinity by David Deutsch, who's a quantum physicist in

1228
01:17:16,880 --> 01:17:21,040
Speaker 3: the UK. I love all of his work, but I

1229
01:17:21,080 --> 01:17:25,440
Speaker 3: also think people should be reading things like my perennially

1230
01:17:25,560 --> 01:17:30,439
Speaker 3: read The Dowdy Jing by Lautsu. It packs a wallup man,

1231
01:17:30,479 --> 01:17:32,880
Speaker 3: because you can read the whole thing in an hour.

1232
01:17:33,520 --> 01:17:35,519
Speaker 3: But I used to joke, you know, I started reading

1233
01:17:35,520 --> 01:17:38,320
Speaker 3: that when I was eighteen, and I read it every year,

1234
01:17:38,600 --> 01:17:41,920
Speaker 3: sometimes multiple times every year, and I finally started to

1235
01:17:41,960 --> 01:17:43,719
Speaker 3: understand it when I was about fifty five.

1236
01:17:44,600 --> 01:17:46,439
Speaker 2: I was gonna say it's a different book each time

1237
01:17:46,439 --> 01:17:47,760
Speaker 2: you read it. It really is.

1238
01:17:47,920 --> 01:17:50,680
Speaker 3: It's like heraklitis. You know, no man steps in the

1239
01:17:50,720 --> 01:17:54,600
Speaker 3: same river twice because it's not the same man and

1240
01:17:54,640 --> 01:17:55,760
Speaker 3: it's not the same river.

1241
01:17:55,960 --> 01:17:58,880
Speaker 2: Absolutely, all right. Our final two questions that we ask

1242
01:17:59,000 --> 01:18:02,120
Speaker 2: all of our guests what sort of advice would you

1243
01:18:02,200 --> 01:18:05,960
Speaker 2: give to a recent college grad interested in a career

1244
01:18:06,600 --> 01:18:11,679
Speaker 2: in either investing, quantitative analytics, or venture capital.

1245
01:18:12,560 --> 01:18:17,360
Speaker 3: Understand the leverage that you get from all of the

1246
01:18:17,439 --> 01:18:24,280
Speaker 3: new AI tools. It gives you several advantages. The older

1247
01:18:24,360 --> 01:18:30,960
Speaker 3: people on those desks might not be rapidly adopting those tools.

1248
01:18:31,800 --> 01:18:36,280
Speaker 3: And if you walk into a job interview with some

1249
01:18:36,600 --> 01:18:40,080
Speaker 3: mastery of them, what they're doing in terms of what

1250
01:18:40,120 --> 01:18:45,880
Speaker 3: they can uncover for VC, for traditional long only or

1251
01:18:46,120 --> 01:18:52,719
Speaker 3: long short management is staggering. Get a deep domain knowledge

1252
01:18:52,760 --> 01:18:57,599
Speaker 3: there as it fits into your particular passion, be it

1253
01:18:57,800 --> 01:19:02,160
Speaker 3: investing or an analysis, etc. But that would be my

1254
01:19:02,400 --> 01:19:05,120
Speaker 3: number one piece of advice.

1255
01:19:05,280 --> 01:19:08,120
Speaker 2: Wow, And our final question, what do you know about

1256
01:19:08,160 --> 01:19:11,400
Speaker 2: the world of investing today that would have been helpful

1257
01:19:11,880 --> 01:19:14,639
Speaker 2: back in the nineteen nineties when you were first starting out.

1258
01:19:15,840 --> 01:19:24,120
Speaker 3: People don't change, markets change, And when I really really

1259
01:19:24,160 --> 01:19:29,600
Speaker 3: came to understand that was after actually the Great Financial Crisis.

1260
01:19:30,880 --> 01:19:34,439
Speaker 3: I went through the crash in nineteen eighty seven, I

1261
01:19:34,479 --> 01:19:38,200
Speaker 3: went through the other bear markets, but I didn't really

1262
01:19:38,439 --> 01:19:45,160
Speaker 3: lock in on the fact that markets change millisecond by millisecond,

1263
01:19:45,640 --> 01:19:52,280
Speaker 3: human behavior barely budgees millennia by millennia. Arbitraging human nature

1264
01:19:52,560 --> 01:19:58,559
Speaker 3: is the final moat. Arbitraging human nature is the final moat.

1265
01:19:59,080 --> 01:20:02,400
Speaker 3: That's fantastic place to end it. Jim, thank you so

1266
01:20:02,560 --> 01:20:05,640
Speaker 3: much for being so generous with your time and for

1267
01:20:05,880 --> 01:20:12,040
Speaker 3: being just such a great colleague, mentor source of wisdom.

1268
01:20:12,840 --> 01:20:16,439
Speaker 3: Like it's been my privilege to know you my whole career.

1269
01:20:17,400 --> 01:20:19,519
Speaker 2: I remember, I want to say it was like the

1270
01:20:19,600 --> 01:20:23,480
Speaker 2: late two thousands, sitting at an outdoor on a Starbucks.

1271
01:20:24,400 --> 01:20:27,720
Speaker 2: I remember one of my well don't we know each other?

1272
01:20:28,479 --> 01:20:31,479
Speaker 2: And it was it was just like one of those

1273
01:20:31,560 --> 01:20:36,799
Speaker 2: small world moments. And you've always been just so thoughtful,

1274
01:20:36,880 --> 01:20:43,120
Speaker 2: so inspiring, and your insights just I know so many

1275
01:20:43,120 --> 01:20:48,120
Speaker 2: people you've had such a positive impact on. It's just

1276
01:20:48,160 --> 01:20:49,519
Speaker 2: a delight and a pleasure to.

1277
01:20:49,479 --> 01:20:54,200
Speaker 3: Know you well right back at Youbury. It's been my

1278
01:20:54,320 --> 01:20:56,160
Speaker 3: great pleasure knowing you all of these.

1279
01:20:56,160 --> 01:20:59,880
Speaker 2: Years, so this mutual admiration society has to come to.

1280
01:20:59,840 --> 01:21:01,240
Speaker 3: An It's a bromance.

1281
01:21:03,000 --> 01:21:07,839
Speaker 2: We have been speaking with Jim O'Shaughnessy, founder and CEO

1282
01:21:08,439 --> 01:21:13,200
Speaker 2: of O'shaughnessee Ventures. If you enjoy this conversation, well check

1283
01:21:13,240 --> 01:21:15,759
Speaker 2: out any of the five hundred previous ones we've had

1284
01:21:16,160 --> 01:21:20,080
Speaker 2: over the past ten, almost eleven years. You can find

1285
01:21:20,120 --> 01:21:25,160
Speaker 2: those at iTunes, Spotify, YouTube, Bloomberg, or wherever you find

1286
01:21:25,600 --> 01:21:28,880
Speaker 2: your favorite podcast. Be sure and check out my new book,

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Speaker 2: How Not to Invest The Bad Ideas, numbers and Behaviors

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Speaker 2: that Destroy Wealth, coming wherever you get your favorite books

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Speaker 2: on March eighteenth, twenty twenty five. I would be remiss

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Speaker 2: if I did not thank the crack team that helps

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Speaker 2: put these conversations together. Anna Luke is my producer, Meredith

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Speaker 2: Frank is my audio engineer. Sage Bauman is the head

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Speaker 2: of podcasts at Bloomberg. Sean Russo is my researcher. I'm

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Speaker 2: Barry Rutults. You've been listening a Master's in Business on

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Speaker 2: Bloomberg Radio.