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So how many of you guys have seen the book,
or sorry, seen the movie 21
or read the book, Bringing Down the House.
Okay, you'll know what I like to call Hollywood magic, and I mean, true Hollywood magic is how you turn an average looking Asian American male into a dashing British white guy, which is what they did in that movie.
It was 2001 and a friend of mine by the name of Ben Merrick had written six books, but it's fair to say that his career was, um, at a crossroads.
He was contemplating not being a writer anymore.
He had business school applications out.
And I went up to him and I said, Ben, I've got a great idea for your next book.
And he says, what is it? I said, me and my buddies from MIT, we go to Vegas.
We use math to beat the casinos.
And this sort of like glossy, dull look went over his face and he goes, you know what?
I don't think I want anyone wants to read a book about a bunch of MIT nerds.
And, um, you know, then about three months later, we took him out with us to Vegas and he goes, oh my God, this is so cool.
We should write a book about this.
And I said, oh, great idea, Ben.
So then we approached this publisher and we talked to his publisher and said, we have a great idea for Ben's next book.
And she says, what is it?
We said, well, me and my friends from MIT we go to Vegas and we use math to be at the casinos.
And again, this is in 2001.
So being a nerd wasn't very cool then.
But now it's obviously much cooler, right?
Like MX is an example of like how powerful being a nerd is, right?
And so, you know, she basically finally said, fine, write the book.
We wrote a book called Bringing Down the House.
It was a New York Times bestseller for over a year.
Eventually got turned into a movie called 21, which was No. 1 in the box office for two weeks, made $150 million off a $35 million budget.
So essentially we won, the Nerds won, which was cool.
Ben went on to write a book called The Accidental Billionaires, which got turned into a movie called The Social Network, which won an Oscar.
So Ben got to go on stage when he won his Oscar.
You want me over this way?
I'm getting hand signals.
Oh, you want me to walk this side so they can - got it.
But these mountains are so beautiful.
So, anyway, so he and then he won an Oscar, but I can now say I made Ben Merrick who he is today.
So there we go. All right.
So I like to tell a few stories that weren't in the book and weren't in the movie just for some fun.
The first one comes from the opening of the Bellagio Casino in the late 1990s.
Um, you know, there's always three types of people at the opening of any casino.
There's card counters like ourselves 'cause those were our emerging markets.
There are celebrities who want to see and be seen, anyone guess the third type of person at every opening of every casino.
You can tell a lot about a crowd by how quickly they get this answer.
I was at a real estate conference in Orange County — no sooner had I said it than a woman from the back row screams, hookers.
So it's card counters, celebrities, and prostitutes.
And usually in a corporate setting, there's one guy that can't resist saying it.
So I make him stand up.
Everyone kind of looks at him and then he realizes that was his career limiting maneuver.
So I had the pleasure of playing blackjack with Kevin Costner.
Kevin Costner was a good blackjack player.
He had his posse of friends around.
He was doing the right thing. We were all winning together.
It was great. And then for about 15 minutes, he just started losing and he lost every hand and every hand he lost, his friends would look at me and say, God, this is like Water World all over again.
My second favorite story comes from the NBA lockout in the late nineties You know, the NBA locked out their players.
And where do you think NBA players go when they can't play basketball? Where they often go to is casinos And I had the pleasure of playing blackjack with a bunch of the New York Knicks at Foxwoods Casino in Connecticut.
So this was Patrick Ewing and Alan Houston and John Starks.
John Starks went through this like, you know, he sits down, he is sort of this tough guy.
I was like excited to play.
He orders a bottle of Merlot, which I thought was like a strange thing for an NBA player to drink.
Fast forward four to five hours later drunk John Starks goes through this transformation that I'm sure many of you guys have seen your friends go through, where you start as a normal, intelligent human being and then four hours later, you're a drunk degenerate gambler.
John puts his last $500 down in the betting circle.
The dealer deals him an 11 and the dealer has a 5 showing.
So anyone who plays blackjack, what do you do there? Double.
You gotta double down. You gotta put another $500 down.
John doesn't have $500.
So I take a $500 chip outta my pocket, hand it to him, say, pay me back when you win.
The dealer gives him a 5 to make 16.
And then he looks at me and he goes, man, you just jinxed me.
And of course I'm counting cards.
So I still think there's a pretty good chance that John's gonna win.
So I said, don't worry, still a good chance.
I think you're gonna win. The dealer flips a 10 to make 15, gets another 10 to make 25.
John wins his, uh, you know, a thousand dollars pays me back my $500 without a word of thank you.
And it was that day I decided I would never have John Starks on my fantasy basketball team.
So I really showed him.
Okay, final story before we get into the real stuff comes from the filming of 21.
So those of you guys that have seen 21, you know that I'm in the movie, correct?
So it was like the most awkward period of my life.
I play a dealer named Jeffrey, the guy that plays me.
Jim Sturgis walks up to me and says, Jeffrey, my brother from another mother, we have a witty back.
This is not ringing any bells to you guys.
A lot of people, people said, you saw the movie and now you're not even, well, this wonderful scene that none of you seem to remember is at about 59 minutes and three seconds.
So if you wanna go back and watch it, you can.
It took three days to film and the second day, we're out there filming, the cast comes up to me and this is like Lawrence Fishburne and like, uh, Josh Gad, like really good actors.
And they said, Hey Jeff, we want to uh, take you to dinner and thank you for letting us tell your story on the big screen.
I said, oh, that'd be fun. So we head over to dinner and on the way over to dinner, and keep in mind I'm like 30 and single at the time, Kate Bosworth pulls me aside and she says, Hey Jeff, I've got a great idea for what you and I can do after dinner.
I said, okay, Kate, tell me more.
And she says, I think it'll be really fun if we all go play blackjack after dinner.
You can coach us and we can win lots of money.
I like, first of all, that's not what I was hoping for Kate, but like, seems like a bad idea.
And she said fine. I said, well, we're gonna to The Palms, they know me very well there, they're not gonna let me play blackjack.
And she said, it's okay, you'll be with me. I'm a big star.
They won't bother you. I said, Kate, it's been a long time since Blue Crush.
I don't think you are a big star anymore.
But after seven or eight bottles of wine, it seemed like a great idea.
And we go and we start playing blackjack at the Palms Casino.
And I try to sit down and the floor person comes up to me, he says, Jeff, what are you doing?
And I said, I, you know, I'm here to play blackjack with Kate Bosworth, Blue Crush, big star, no big deal, right?
And he says, let me see. And he calls upstairs and he says, Hey, not only are you not allowed to play blackjack with Kate, but if she's at the table, you're not allowed to be within 20 feet of the table.
What was cool is that gave me a lot of street cred with Kate.
She thought I was dangerous at that point.
She went back and told them I was dangerous.
Didn't get me anywhere with her, but at least it gave me a lot of street cred.
Okay, so we're talk a little bit about being data-driven and we're gonna talk a little bit about the lessons that we learned from the world of blackjack.
And I'm gonna take you through a little bit of a journey that will hopefully leave you guys understanding how to make better decisions using data, how to win with data, all through the lens of beating blackjack and what I've done in my life.
So, uh, rewind, I'm 21 years old, had just graduated from MIT, had learned the system to use math to beat the casinos.
So this is in 1994.
And you know, everything we do at the tables is 100% objective, right?
It's like the first version of big data before there was such a thing.
So every decision is data driven.
So I walk up to the table and I bet two hands of $10,000 at Caesar's Palace in Las Vegas because that's what the numbers tell me to do.
On the first hand, I get a pair of 9s and the second hand I get 11 and a dealer has a 5.
Showing a pair of 9s is a hand that I wanna split.
So I gotta put another $10,000 down.
I get to play each 9 separately.
And this is all some governed by something called basic strategy.
On the first 9, I get a 2 to make 11, so I gotta double that down and I get an 8 to make 19.
And the 9 I hit and I get a jack to make 19.
So I have 19, 19 on the 11 is another hand that I do what?
Double. Double. So I double again and I get an 8 to make 19.
So I have 19, 19 19 against the dealers 5, how much money I have on the table?
Come on. $50,000. No one ever gets this right.
And you guys are like a smart crowd.
I was at the National Accountants Association speaking to like the most, the best accountants in the country, and I get to this and none of them got it right either.
And I'm like, this is why we're in such a deficit as a, as a country.
Math is hard for us.
Okay, 19, 19, 19 against a dealer's 5, the dealer flips a 6 to make 11 and then gets a king to make 21.
I'm crushed, lost $50,000.
Uh, this woman behind me screams, oh my God, that's my entire mortgage.
And I turn around and go, where the hell do you live?
Because I live in San Francisco and that's a cardboard box in the Tenderloin.
So like 19, 19, 19, lose this $50,000.
Now the math actually calls for me to bet 300 to $10,000 and 21 years old believing data, but also a real crisis in terms of what I believe in.
So I always think about this moment as like a reflection, and I'll talk a little bit about how did I get here.
Um, I graduated from MIT in 1994 with a mechanical engineering degree that I've never used once in my life.
Um, it makes my parents or made my parents immensely happy.
I went into finance right after college and then I went and started a few different companies.
And what what's interesting, I started a fintech company called Circle Lending, which was doing like peer-to-peer lending before there was such a thing as like and, uh, Lending Tree and all those types of things.
Um, I started a sports media company, which the goal was to allow people to trade athletes like stocks.
Um, I started a data and analytics company to try to help people better measure the performance of their employees or better motivate their employees via metrics.
And then eventually I I went to Twitter where I ran data science and analytics at Twitter.
And what's interesting is this whole like career arc where I think from my standpoint, I was doing a lot of stuff in the world of like data-driven thinking and like I was kind of doing it all in the world Of blackjack.
And I was also very interested in doing it in the world of sports.
Um, when … this is an advancing, but maybe it's okay.
Okay. When Michael Lewis wrote the book Moneyball, I realized that a lot of what I could do could be applied to other parts of the world.
And so that really captured my fancy.
But one of the interesting things I think a little bit about, and I was listening to you guys talk a little bit about the, the work you guys would do at data.
I usually when I have like a longer talk, talk a little bit about how to build an analytics organization and one of the things I talk about is this foundational layer moat of data and how important that getting that data or having data that no one else has.
And then I also talk a little bit about the ethical nature of using data.
And a lot of that I developed when we were at Twitter.
Um, what was funny is the reason we were so far behind places like Facebook and you know, uh, Google, is that we, we didn't use a lot of the user data for bad — meaning, like we only wanted to use the data.
Like we had like this rule where we'd only use the data if it really enhanced the customer's experience.
And my analogy to this is you can feel good about using data, customer data when you're building value for the customer.
And I always think about my wife who hates getting tracked around the internet, deletes cookies, uses Incognito browsers, but will literally say in delight, this is the third thing I bought on Facebook today.
They really know me, right?
And so there is value as long as there is value to that data, it's okay.
So what I really learned during that time was this concept of being data-driven.
Why should we be data-driven?
And I'm gonna take you through a few lessons in terms of how to be blackjack.
So you're gonna say, okay, how do these tie together?
That story I told from the beginning of the blackjack story and like, you know, the the different hands and what we did, that was something called basic strategy.
So at every hand of the blackjack table, there is a very basic answer of what you should do.
There's no subjectivity.
And if you learn basic strategy perfectly, it reduces the casino's edge from roughly the average blackjack player loses about 3% of the money they put on the table.
You learn basic strategy perfectly, you're gonna only lose about half a percent but people don't follow basic strategy.
And it highlights at many levels the challenges that people have with these sort of cognitive biases that are all inside of them.
One of the ones I talk a little bit about is this idea of omission bias.
We favor inaction over action when we fear it might lead to harm.
And again, a lot of these things have direct implications outside of just being data driven.
You can think about them in the lens of your business and how you grow your business and whatnot.
So again, the idea of omission bias is I have a 16, the dealer has an 8, showing what should I do?
You should hit. But if you get a 6, a 7 and 8, a 9, a 10, a jack of queen, a king, you know you're gonna lose right away.
So a lot of people would rather just kinda like sit back and hope the dealer flips, you know, a low card and then bust and you win that way.
And if they make their hand, well at least you weren't the product of your own demise.
And this became like a very, very personal story to me.
Um, when uh, you know, I was, I wrote a book called The House Advantage Playing the Odds Win Big in Business, which is available on Amazon if anyone's interested in it right now.
But when I wrote that book, one of the reasons I did is I wanted to write a mainstream book on data and analytics that everybody would read.
And so I was doing a PR tour and I was pitching Good Morning America about doing this.
And they said, well, you know, it's an interesting book, but can you tell us a story where this really affected you personally?
And I said, okay. And I didn't really have one.
But then that all changed. I don't know, like 15 years ago I was speaking at a conference in Lake Tahoe and I was about to go do a 10-city speaking tour of Asia.
And as I was driving home, my father called me and my parents were living on the East Coast at that time and they said, Hey, we have, I have some sad news.
I said, well what is this? Your mom just had a stroke.
And my mom was 71 at the time in incredible shape, worked out every day.
And I said, is she okay?
And he said, uh, not, it's not great.
And so I canceled my tour, I flew home and my mom, my dad wasn't exaggerating.
My mom could not speak, could not move the right side of her body, could not acknowledge me when I walked in the door and my sisters came home also and we sat down with a neurosurgeon and the neurosurgeon said, Hey, I wanna go over your options.
I said, well what are our options?
Well, normally a woman in this situation who has had this big of a bleed, we don't wanna do anything.
We don't wanna cause more damage, but your mom was actually in great shape before and we think we can remove the bleed.
I operate on tumors all the time, this should be easier, but it's risky.
And I said to him,, as we're he's saying this to me, I'm like, oh my God, this is just like hitting 16 versus An 8 in blackjack.
Like if we think this is the right thing to do, like we're trying to win, we're not trying to avoid losing.
And I stand up and start talking about it and these my sisters and my dad are like, oh my god, this blackjack s**t is going to his head.
But when they listened to what I had to say, they understood that I was right, like it’s the right decision to make, even if it was the risky decision.
And so we let him operate.
The next day she started to perk up.
Two days later, she started to speak.
Three days later I felt comfortable enough.
I'm like, I'm gonna go do the rest of my Asia tour.
And I was getting married nine months later I said to my mom, like, I just wanna make sure you and I can dance at my wedding.
And she said, that'll be easy.
And we, you know, nine months later I'm happy to say that my mom and I did dance at my wedding.
She lived another 10 years after that.
Um, she eventually passed away from another stroke.
But I think any of you guys ever had like that kind of like stay that extra 10 years.
It's incredibly valuable.
And it was a wonderful lesson where the application of this idea of omission bias has become very personal to me.
The idea of being data-driven, the idea of gut feeling versus being data-driven.
You know, I always joke about the most dangerous human being in the world being Malcolm Gladwell because he can take a wrong concept and convince you that it's true.
You don't blink to make better decisions.
You have to really, really focus on data and that's the way to make the best decisions.
And then ultimately right decision versus right outcome talk.
You guys talked a little bit about the process that you guys are going through and having the right process.
If we go, I don't know, I don't think there's any casinos in Utah, but if we drive across the border tonight and go somewhere and sit behind and you say, oh Jeff, I have 15 versus 8, what do you think I'm supposed to do here again?
And I was like, you gotta hit, if you met 6 to 21, you turn around and you high five me.
We're best friends forever. If you get 7 to make 22, you're like, why'd you ever have a book written about you or a movie made about you?
So it's the idea of decision versus outcome, trusting the process, right?
We hear this a lot in sports and like this is the ultimate thing where I think if any of you guys watch football, you know that there's been this tremendous, you know, move towards going for it more on fourth down.
That's very much supported by the data.
But you know, every time that it happens and it doesn't work, they think it was a bad decision and the decision the outcome should be completely separated there.
So real quickly, why is blackjack beatable?
Blackjack is the only game in the casino that's subject to something called conditional probability.
Meaning what you see impacts what you're gonna see.
If you contrast that to uh, roulette, walk up to a roulette wheel, see, you know, six reds in a row, you better bet black.
Correct? No, same thing, true.
I've always walk up to craps tables because that's the only thing I'm allowed to play in the casino. I can't play blackjack.
And I say, how's this table been?
Everyone's always like, oh, you know, great blah blah or bad, you know, but they're all the same.
There's a lot of sevens, there's not many elevens, but blackjack is different.
If I take all 4 aces out of deck of cards and hand you that deck of cards, what do you think the chance of you dealing yourself blackjack are zero, right?
There's, there's no more chance of blackjack.
So blackjack is a game with a memory like an elephant and the other games are like fish, hence the iconography.
Okay, so what is counting cards?
Counting cards is a very simple concept.
When there are a lot of, when you've seen a lot of high cards, that means there's a lot of low cards left.
Okay? That's bad for the player.
When you've seen a lot of low cards, that means there's a lot of high cards left that's good for the player.
And all you're doing is tracking these as they come by and adjusting your bet.
Obviously there's a little more math to this.
I could teach anyone in this room how to do this in an hour.
You would just actually have to like practice, practice, practice to get a good at it.
But I could teach you the concept in an hour.
So it's not like you need to be Rainman to do this.
You just need to practice and you need to learn this system.
So there I am Jeffrey, the dealer, in case she didn't believe me.
Uh, I always have this up as kind of a joke, but it's funny because I always have it up there to talk about one of the most difficult decisions I made, um, at the blackjack table.
So how many of you guys that have played uh, blackjack have ever split 10s?
Raise your hand if you split 10s or maybe mentally raise your hand.
'cause I don't want to be embarrassed about you raising your hand if you're not counting cards.
There's never a reason to split 10s, but I just told you that counting cards was the knowledge of how many 10s, face cards and aces remain versus low cards.
So let's say you have a pair of 10s and the dealer has a 6 showing and you know, almost every card that you have not seen is a 10 or a face card or an ace, then maybe is that a time you would split 10s?
'cause the expected value or the opportunity is higher.
It is. And there's math that will support this.
And so this is sort of an advanced thing you learn.
And I remember I walked into the MGM Grand, um, with this knowledge and I was excited and I sat down at a table where I, um, bet two hands of $8,000 and it was a really high number of high cards left in the deck.
And the dealer gives me a blackjack on one and a pair of 10s on the second one and the dealer has a 6 showing.
So the blackjack, she pays me my $12,000 and then she starts to go buy my 20 because who's gonna split 10s with $8,000 on the table?
And I said, excuse me ma'am, I want to split those.
And she said, you want to what those? And I said I want to.
And then all of a sudden I was like, eh, maybe I don't wanna split those.
And I started thinking about why I didn't wanna split those.
And I realized that the predominant reason that I didn't wanna split those is I am looking around this table and everyone at this table thinks I am a moron.
If I split these 10s, everyone will be angry with me.
If I split these 10s, they will disagree with that decision.
But if they had the technology, the data, the knowledge that I had, would they maybe agree with me?
And so what I'm doing here is falling for something called group think, which I'm sure you guys see in all your businesses.
And as you think about working with new technologies like MX and new ways of doing business, anytime you have advances in technology and data, you're gonna have to do unconventional things.
And anytime you do something unconventional, it's gonna p**s some people off.
So you can't make decisions based on group think or avoiding conflict, right?
That's the ultimate — making a decision to avoid conflict.
'cause good decisions, progressive decisions are always gonna create conflict.
Okay? I don't care about these people.
I decide like I don't know any of 'em.
I'm never gonna see any of them again.
I don't care about group think, but I still don't wanna split these 10s.
And why is that? And I realize that I am afraid of losing.
I have banked this $8,000 in my head because I have 20 and the dealer has a 6.
This is a great situation for me, but again, this is the wrong way of thinking about things.
I'm being loss averse right now where I'm fearing loss more than I am embracing gain, right?
I know the expected value is higher to do this.
So why should I be afraid of losing?
Losing is figured into that expected value.
And ultimately there are many, you know, companies that are great lessons of this, right?
When I was one of the first times I spoke at Facebook, I've spoken there twice, they had 30 million users.
Then I went back there, I think two years later they had 500 million users.
It was the day they're announcing that they had 500 million users.
And I was saying this whole spiel and I got to it and I go, you guys are a perfect example.
Now that you have 500 million users, are you gonna take the same kind of risks that you took?
And before the words were outta my mouth, an executive from the back row named Chamath Palihapitiya, who I'm sure some of you guys know now from his all in podcast, he screams hell yeah.
And what he meant is he knew that for them to continue to grow, get stronger in business, they were gonna have to continue to take risks.
And they went on to buy a company called Instagram for a billion dollars, which was risky at the time, but now looks like one of the biggest bargains in history.
They bought WhatsApp, they bought Oculus.
Like they've, they've taken risks and they've grown from that.
Um, okay, don't pay attention to this title.
It didn't get changed for this, but it, it's, it's applicable.
It should say something like what I've learned or learnings.
So just mentally say learnings 'cause it doesn't make sense.
If you don't see it now you're like, wait, what, what does that even mean?
Somehow I didn't get changed when I was updating my slides.
Okay, so let's go back to, wait a minute.
Hmm. These are outta order. Okay, there we go.
We can just ignore that one then. Perfect.
Okay, so that was just a superfluous slide.
All right. You guys are all wondering like, oh my god, that moment in time, right?
Oh, I didn't actually finish telling that story.
So anyways, I split, I was so confused 'cause I was looking at the previous slide.
So of course I split the 10s, right?
I put down another $8,000, the dealer flips 'em, gives me an ace on one and a 9.
On the second one, the dealer flips the 10 to make, uh, 16 and then another 10 to make 26.
I win my $16,000, grab my other 12,000, the show's over and everyone at the table does not want to kill me.
So I basically just kinda like run away from the table with my money.
But that ability to overcome those biases to make these difficult decisions is, is uh, is a real thing.
Okay? So now back to that one story.
You guys are all like, oh my God, what happened with him and God, I'm not gonna be able to sleep tonight.
And if I know what so well of course I believe in numbers, right?
And of course I kept betting, right?
And I, you know, had that test the table, got the woman behind me screaming about her mortgage and I got these, all these people looking at me like, this kid just lost $50,000.
What's he gonna do? So I put three hands of $10,000 down, which is what the math tells me to do. On the first one I get a 9.
On the second one I get a 19 on the first one, third one I get a soft 15 and the dealer has a 6.
Showing the 9 against a 6 is a hand that I want to do what?
Double. So I put another $10,000 on that and I get a queen to make 19.
And then the ace against a 6 is the nother hand that I want to double and I do and I get a 4 on that to make 19.
So very circular now 19, 19, 19 against the dealer's.
16, right? So dealer flips the king to make 16.
And I'm in this situation to basically win back everything I just lost.
The only reason I'm in this situation is 'cause I believe in numbers and I have this like stick to it in my gut and the dealer flips a 5 to make 21.
So I lose another $50,000, the show's over and I have no money left.
So I grab no money and walk up to my room at Caesar's Palace, collapse on the floor, stare up at the ceiling, wondering myself, why is there a mirror up there?
But once I get over that, I mean I'm 21 years old, graduate from MIT I'm like, do people lie in bed and get ready?
It seems weird. Okay.
So I, I think a little bit about what do I do next in this moment in time I evaluate what do I do next?
And you know, first thing I think about is this idea of of, well maybe I'll just quit for a little while.
I'll go back to MIT and evaluate the decision.
And well that's bias to inaction.
That's not making a decision, which is the same thing as making a decision.
And then I think a lot, a little bit about this and you talked about this, this kind of concept of a long-term perspective and having MX as a partner for the long term.
I think that's so important in business.
'cause I had done quite well at blackjack up until then.
And also so much of what we were based on was a, a lot playing a lot of hands, right?
We have a small edge with variance and I need to have that same long-term perspective as I'm thinking about myself and my own career.
And it's one of the hardest things we do like at, at Twitter, I always used to say like one of our challenges, one of the smartest things that Elon did with Twitter was making it private.
Because when you're a publicly traded company and you've gotta make quarterly decisions for shareholder meetings, you're making bad decisions often.
So having a long-term perspective is incredibly important.
And then I think about this idea of losing, right?
If we have like a 51% chance to win, that means we have a 49% chance to lose, which means we are going to lose sometimes. That's okay and I can't be afraid of losing.
And then I think about trusting the process.
Had I had a bad outcome, uh, had I had a bad process or I just gotten unlucky and I'm pretty sure I had had a strong process, I feel very comfortable about that, right?
And so I think a lot about this in the moment in time that I thought about this.
And when I've told this story before, I was speaking at an event that a guy made him put on sort of legendary VC in Silicon Valley.
And the speaker before me that day was a guy by the name of Bill Gates.
So it was very intimidating to be on that stage.
And as I was speaking, you know, I got to this part of the speech and um, OD looks at me and stands up and he says, Jeff, I don't believe you.
I said, what do you mean? He says, how could you, how could you have doubted the math?
How could you have questioned what you're doing?
And I sort of like looked at him at the time and I'm like, please just sit down.
But when I got by that idea of he was right, I mean I think I always will believe in that math and I always have that stubbornness to continue going.
And my personal mentor is a guy by the name of Kevin Compton.
Kevin was the operating and managing partner at Kleiner Perkins during their heyday.
Legendary VC has been the first money in about 13 different companies that have had multi-billion dollar market caps.
And I've heard him do, he is very modest.
He's not one of those guys that will beat his chest about anything he has ever done.
But I found a small interview he did online and they ask him about VC as an asset class.
And he says, well, I, I don't know what this asset class is, but I know we do really well.
And I know the reason we do really well is we stick with our entrepreneurs.
We know the reason that they, or we believe the reason they fail is not 'cause they're not good or they don't work hard or they don't have good ideas, so they run outta capital.
And so we like to stay with them so they have a chance to succeed.
And so I think a lot about my own life where I've started four companies that have all I'm lucky to have like somewhat successful exits from, and I don't think I'm the smartest or I don't think I'm like the hardest working, but I do think I might be one of the most stubborn.
So it was that moment in time I galvanized the stubbornness and I went back down and I kept playing and over the next day I won back the hundred thousand and the last day there I won $70,000.
So I ended up leaving up $70,000.
And I do think that was a very seminal moment for me to understand the value of one being data-driven, but two being determined.
And if you think about in all the things we do in business and like MX I'm sure there's been moments in time where that determination to get to being here, having an event like this at like, it's funny because I do, you know, I've never started a company that had a, a beautiful event like this.
I can only, I look at this, I'm like, how much does this cost?
These guys can't even imagine.
But, um, anyways, if I had given up, which I probably wanted to at some times, I never would've got written a book or had a movie made about me or been able to come have a wonderful time in Park City with all of you guys.
So thank you guys.
How to Win with Data
Data is king, especially in the finance industry. Jeffrey Ma, with years of experience in data analytics, shows how data can be the turning point that enables financial institutions to win big.
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Transcript
Okay, you'll know what I like to call Hollywood magic, and I mean, true Hollywood magic is how you turn an average looking Asian American male into a dashing British white guy, which is what they did in that movie.
It was 2001 and a friend of mine by the name of Ben Merrick had written six books, but it's fair to say that his career was, um, at a crossroads.
He was contemplating not being a writer anymore.
He had business school applications out.
And I went up to him and I said, Ben, I've got a great idea for your next book.
And he says, what is it? I said, me and my buddies from MIT, we go to Vegas.
We use math to beat the casinos.
And this sort of like glossy, dull look went over his face and he goes, you know what?
I don't think I want anyone wants to read a book about a bunch of MIT nerds.
And, um, you know, then about three months later, we took him out with us to Vegas and he goes, oh my God, this is so cool.
We should write a book about this.
And I said, oh, great idea, Ben.
So then we approached this publisher and we talked to his publisher and said, we have a great idea for Ben's next book.
And she says, what is it?
We said, well, me and my friends from MIT we go to Vegas and we use math to be at the casinos.
And again, this is in 2001.
So being a nerd wasn't very cool then.
But now it's obviously much cooler, right?
Like MX is an example of like how powerful being a nerd is, right?
And so, you know, she basically finally said, fine, write the book.
We wrote a book called Bringing Down the House.
It was a New York Times bestseller for over a year.
Eventually got turned into a movie called 21, which was No. 1 in the box office for two weeks, made $150 million off a $35 million budget.
So essentially we won, the Nerds won, which was cool.
Ben went on to write a book called The Accidental Billionaires, which got turned into a movie called The Social Network, which won an Oscar.
So Ben got to go on stage when he won his Oscar.
You want me over this way?
I'm getting hand signals.
Oh, you want me to walk this side so they can - got it.
But these mountains are so beautiful.
So, anyway, so he and then he won an Oscar, but I can now say I made Ben Merrick who he is today.
So there we go. All right.
So I like to tell a few stories that weren't in the book and weren't in the movie just for some fun.
The first one comes from the opening of the Bellagio Casino in the late 1990s.
Um, you know, there's always three types of people at the opening of any casino.
There's card counters like ourselves 'cause those were our emerging markets.
There are celebrities who want to see and be seen, anyone guess the third type of person at every opening of every casino.
You can tell a lot about a crowd by how quickly they get this answer.
I was at a real estate conference in Orange County — no sooner had I said it than a woman from the back row screams, hookers.
So it's card counters, celebrities, and prostitutes.
And usually in a corporate setting, there's one guy that can't resist saying it.
So I make him stand up.
Everyone kind of looks at him and then he realizes that was his career limiting maneuver.
So I had the pleasure of playing blackjack with Kevin Costner.
Kevin Costner was a good blackjack player.
He had his posse of friends around.
He was doing the right thing. We were all winning together.
It was great. And then for about 15 minutes, he just started losing and he lost every hand and every hand he lost, his friends would look at me and say, God, this is like Water World all over again.
My second favorite story comes from the NBA lockout in the late nineties You know, the NBA locked out their players.
And where do you think NBA players go when they can't play basketball? Where they often go to is casinos And I had the pleasure of playing blackjack with a bunch of the New York Knicks at Foxwoods Casino in Connecticut.
So this was Patrick Ewing and Alan Houston and John Starks.
John Starks went through this like, you know, he sits down, he is sort of this tough guy.
I was like excited to play.
He orders a bottle of Merlot, which I thought was like a strange thing for an NBA player to drink.
Fast forward four to five hours later drunk John Starks goes through this transformation that I'm sure many of you guys have seen your friends go through, where you start as a normal, intelligent human being and then four hours later, you're a drunk degenerate gambler.
John puts his last $500 down in the betting circle.
The dealer deals him an 11 and the dealer has a 5 showing.
So anyone who plays blackjack, what do you do there? Double.
You gotta double down. You gotta put another $500 down.
John doesn't have $500.
So I take a $500 chip outta my pocket, hand it to him, say, pay me back when you win.
The dealer gives him a 5 to make 16.
And then he looks at me and he goes, man, you just jinxed me.
And of course I'm counting cards.
So I still think there's a pretty good chance that John's gonna win.
So I said, don't worry, still a good chance.
I think you're gonna win. The dealer flips a 10 to make 15, gets another 10 to make 25.
John wins his, uh, you know, a thousand dollars pays me back my $500 without a word of thank you.
And it was that day I decided I would never have John Starks on my fantasy basketball team.
So I really showed him.
Okay, final story before we get into the real stuff comes from the filming of 21.
So those of you guys that have seen 21, you know that I'm in the movie, correct?
So it was like the most awkward period of my life.
I play a dealer named Jeffrey, the guy that plays me.
Jim Sturgis walks up to me and says, Jeffrey, my brother from another mother, we have a witty back.
This is not ringing any bells to you guys.
A lot of people, people said, you saw the movie and now you're not even, well, this wonderful scene that none of you seem to remember is at about 59 minutes and three seconds.
So if you wanna go back and watch it, you can.
It took three days to film and the second day, we're out there filming, the cast comes up to me and this is like Lawrence Fishburne and like, uh, Josh Gad, like really good actors.
And they said, Hey Jeff, we want to uh, take you to dinner and thank you for letting us tell your story on the big screen.
I said, oh, that'd be fun. So we head over to dinner and on the way over to dinner, and keep in mind I'm like 30 and single at the time, Kate Bosworth pulls me aside and she says, Hey Jeff, I've got a great idea for what you and I can do after dinner.
I said, okay, Kate, tell me more.
And she says, I think it'll be really fun if we all go play blackjack after dinner.
You can coach us and we can win lots of money.
I like, first of all, that's not what I was hoping for Kate, but like, seems like a bad idea.
And she said fine. I said, well, we're gonna to The Palms, they know me very well there, they're not gonna let me play blackjack.
And she said, it's okay, you'll be with me. I'm a big star.
They won't bother you. I said, Kate, it's been a long time since Blue Crush.
I don't think you are a big star anymore.
But after seven or eight bottles of wine, it seemed like a great idea.
And we go and we start playing blackjack at the Palms Casino.
And I try to sit down and the floor person comes up to me, he says, Jeff, what are you doing?
And I said, I, you know, I'm here to play blackjack with Kate Bosworth, Blue Crush, big star, no big deal, right?
And he says, let me see. And he calls upstairs and he says, Hey, not only are you not allowed to play blackjack with Kate, but if she's at the table, you're not allowed to be within 20 feet of the table.
What was cool is that gave me a lot of street cred with Kate.
She thought I was dangerous at that point.
She went back and told them I was dangerous.
Didn't get me anywhere with her, but at least it gave me a lot of street cred.
Okay, so we're talk a little bit about being data-driven and we're gonna talk a little bit about the lessons that we learned from the world of blackjack.
And I'm gonna take you through a little bit of a journey that will hopefully leave you guys understanding how to make better decisions using data, how to win with data, all through the lens of beating blackjack and what I've done in my life.
So, uh, rewind, I'm 21 years old, had just graduated from MIT, had learned the system to use math to beat the casinos.
So this is in 1994.
And you know, everything we do at the tables is 100% objective, right?
It's like the first version of big data before there was such a thing.
So every decision is data driven.
So I walk up to the table and I bet two hands of $10,000 at Caesar's Palace in Las Vegas because that's what the numbers tell me to do.
On the first hand, I get a pair of 9s and the second hand I get 11 and a dealer has a 5.
Showing a pair of 9s is a hand that I wanna split.
So I gotta put another $10,000 down.
I get to play each 9 separately.
And this is all some governed by something called basic strategy.
On the first 9, I get a 2 to make 11, so I gotta double that down and I get an 8 to make 19.
And the 9 I hit and I get a jack to make 19.
So I have 19, 19 on the 11 is another hand that I do what?
Double. Double. So I double again and I get an 8 to make 19.
So I have 19, 19 19 against the dealers 5, how much money I have on the table?
Come on. $50,000. No one ever gets this right.
And you guys are like a smart crowd.
I was at the National Accountants Association speaking to like the most, the best accountants in the country, and I get to this and none of them got it right either.
And I'm like, this is why we're in such a deficit as a, as a country.
Math is hard for us.
Okay, 19, 19, 19 against a dealer's 5, the dealer flips a 6 to make 11 and then gets a king to make 21.
I'm crushed, lost $50,000.
Uh, this woman behind me screams, oh my God, that's my entire mortgage.
And I turn around and go, where the hell do you live?
Because I live in San Francisco and that's a cardboard box in the Tenderloin.
So like 19, 19, 19, lose this $50,000.
Now the math actually calls for me to bet 300 to $10,000 and 21 years old believing data, but also a real crisis in terms of what I believe in.
So I always think about this moment as like a reflection, and I'll talk a little bit about how did I get here.
Um, I graduated from MIT in 1994 with a mechanical engineering degree that I've never used once in my life.
Um, it makes my parents or made my parents immensely happy.
I went into finance right after college and then I went and started a few different companies.
And what what's interesting, I started a fintech company called Circle Lending, which was doing like peer-to-peer lending before there was such a thing as like and, uh, Lending Tree and all those types of things.
Um, I started a sports media company, which the goal was to allow people to trade athletes like stocks.
Um, I started a data and analytics company to try to help people better measure the performance of their employees or better motivate their employees via metrics.
And then eventually I I went to Twitter where I ran data science and analytics at Twitter.
And what's interesting is this whole like career arc where I think from my standpoint, I was doing a lot of stuff in the world of like data-driven thinking and like I was kind of doing it all in the world Of blackjack.
And I was also very interested in doing it in the world of sports.
Um, when … this is an advancing, but maybe it's okay.
Okay. When Michael Lewis wrote the book Moneyball, I realized that a lot of what I could do could be applied to other parts of the world.
And so that really captured my fancy.
But one of the interesting things I think a little bit about, and I was listening to you guys talk a little bit about the, the work you guys would do at data.
I usually when I have like a longer talk, talk a little bit about how to build an analytics organization and one of the things I talk about is this foundational layer moat of data and how important that getting that data or having data that no one else has.
And then I also talk a little bit about the ethical nature of using data.
And a lot of that I developed when we were at Twitter.
Um, what was funny is the reason we were so far behind places like Facebook and you know, uh, Google, is that we, we didn't use a lot of the user data for bad — meaning, like we only wanted to use the data.
Like we had like this rule where we'd only use the data if it really enhanced the customer's experience.
And my analogy to this is you can feel good about using data, customer data when you're building value for the customer.
And I always think about my wife who hates getting tracked around the internet, deletes cookies, uses Incognito browsers, but will literally say in delight, this is the third thing I bought on Facebook today.
They really know me, right?
And so there is value as long as there is value to that data, it's okay.
So what I really learned during that time was this concept of being data-driven.
Why should we be data-driven?
And I'm gonna take you through a few lessons in terms of how to be blackjack.
So you're gonna say, okay, how do these tie together?
That story I told from the beginning of the blackjack story and like, you know, the the different hands and what we did, that was something called basic strategy.
So at every hand of the blackjack table, there is a very basic answer of what you should do.
There's no subjectivity.
And if you learn basic strategy perfectly, it reduces the casino's edge from roughly the average blackjack player loses about 3% of the money they put on the table.
You learn basic strategy perfectly, you're gonna only lose about half a percent but people don't follow basic strategy.
And it highlights at many levels the challenges that people have with these sort of cognitive biases that are all inside of them.
One of the ones I talk a little bit about is this idea of omission bias.
We favor inaction over action when we fear it might lead to harm.
And again, a lot of these things have direct implications outside of just being data driven.
You can think about them in the lens of your business and how you grow your business and whatnot.
So again, the idea of omission bias is I have a 16, the dealer has an 8, showing what should I do?
You should hit. But if you get a 6, a 7 and 8, a 9, a 10, a jack of queen, a king, you know you're gonna lose right away.
So a lot of people would rather just kinda like sit back and hope the dealer flips, you know, a low card and then bust and you win that way.
And if they make their hand, well at least you weren't the product of your own demise.
And this became like a very, very personal story to me.
Um, when uh, you know, I was, I wrote a book called The House Advantage Playing the Odds Win Big in Business, which is available on Amazon if anyone's interested in it right now.
But when I wrote that book, one of the reasons I did is I wanted to write a mainstream book on data and analytics that everybody would read.
And so I was doing a PR tour and I was pitching Good Morning America about doing this.
And they said, well, you know, it's an interesting book, but can you tell us a story where this really affected you personally?
And I said, okay. And I didn't really have one.
But then that all changed. I don't know, like 15 years ago I was speaking at a conference in Lake Tahoe and I was about to go do a 10-city speaking tour of Asia.
And as I was driving home, my father called me and my parents were living on the East Coast at that time and they said, Hey, we have, I have some sad news.
I said, well what is this? Your mom just had a stroke.
And my mom was 71 at the time in incredible shape, worked out every day.
And I said, is she okay?
And he said, uh, not, it's not great.
And so I canceled my tour, I flew home and my mom, my dad wasn't exaggerating.
My mom could not speak, could not move the right side of her body, could not acknowledge me when I walked in the door and my sisters came home also and we sat down with a neurosurgeon and the neurosurgeon said, Hey, I wanna go over your options.
I said, well what are our options?
Well, normally a woman in this situation who has had this big of a bleed, we don't wanna do anything.
We don't wanna cause more damage, but your mom was actually in great shape before and we think we can remove the bleed.
I operate on tumors all the time, this should be easier, but it's risky.
And I said to him,, as we're he's saying this to me, I'm like, oh my God, this is just like hitting 16 versus An 8 in blackjack.
Like if we think this is the right thing to do, like we're trying to win, we're not trying to avoid losing.
And I stand up and start talking about it and these my sisters and my dad are like, oh my god, this blackjack s**t is going to his head.
But when they listened to what I had to say, they understood that I was right, like it’s the right decision to make, even if it was the risky decision.
And so we let him operate.
The next day she started to perk up.
Two days later, she started to speak.
Three days later I felt comfortable enough.
I'm like, I'm gonna go do the rest of my Asia tour.
And I was getting married nine months later I said to my mom, like, I just wanna make sure you and I can dance at my wedding.
And she said, that'll be easy.
And we, you know, nine months later I'm happy to say that my mom and I did dance at my wedding.
She lived another 10 years after that.
Um, she eventually passed away from another stroke.
But I think any of you guys ever had like that kind of like stay that extra 10 years.
It's incredibly valuable.
And it was a wonderful lesson where the application of this idea of omission bias has become very personal to me.
The idea of being data-driven, the idea of gut feeling versus being data-driven.
You know, I always joke about the most dangerous human being in the world being Malcolm Gladwell because he can take a wrong concept and convince you that it's true.
You don't blink to make better decisions.
You have to really, really focus on data and that's the way to make the best decisions.
And then ultimately right decision versus right outcome talk.
You guys talked a little bit about the process that you guys are going through and having the right process.
If we go, I don't know, I don't think there's any casinos in Utah, but if we drive across the border tonight and go somewhere and sit behind and you say, oh Jeff, I have 15 versus 8, what do you think I'm supposed to do here again?
And I was like, you gotta hit, if you met 6 to 21, you turn around and you high five me.
We're best friends forever. If you get 7 to make 22, you're like, why'd you ever have a book written about you or a movie made about you?
So it's the idea of decision versus outcome, trusting the process, right?
We hear this a lot in sports and like this is the ultimate thing where I think if any of you guys watch football, you know that there's been this tremendous, you know, move towards going for it more on fourth down.
That's very much supported by the data.
But you know, every time that it happens and it doesn't work, they think it was a bad decision and the decision the outcome should be completely separated there.
So real quickly, why is blackjack beatable?
Blackjack is the only game in the casino that's subject to something called conditional probability.
Meaning what you see impacts what you're gonna see.
If you contrast that to uh, roulette, walk up to a roulette wheel, see, you know, six reds in a row, you better bet black.
Correct? No, same thing, true.
I've always walk up to craps tables because that's the only thing I'm allowed to play in the casino. I can't play blackjack.
And I say, how's this table been?
Everyone's always like, oh, you know, great blah blah or bad, you know, but they're all the same.
There's a lot of sevens, there's not many elevens, but blackjack is different.
If I take all 4 aces out of deck of cards and hand you that deck of cards, what do you think the chance of you dealing yourself blackjack are zero, right?
There's, there's no more chance of blackjack.
So blackjack is a game with a memory like an elephant and the other games are like fish, hence the iconography.
Okay, so what is counting cards?
Counting cards is a very simple concept.
When there are a lot of, when you've seen a lot of high cards, that means there's a lot of low cards left.
Okay? That's bad for the player.
When you've seen a lot of low cards, that means there's a lot of high cards left that's good for the player.
And all you're doing is tracking these as they come by and adjusting your bet.
Obviously there's a little more math to this.
I could teach anyone in this room how to do this in an hour.
You would just actually have to like practice, practice, practice to get a good at it.
But I could teach you the concept in an hour.
So it's not like you need to be Rainman to do this.
You just need to practice and you need to learn this system.
So there I am Jeffrey, the dealer, in case she didn't believe me.
Uh, I always have this up as kind of a joke, but it's funny because I always have it up there to talk about one of the most difficult decisions I made, um, at the blackjack table.
So how many of you guys that have played uh, blackjack have ever split 10s?
Raise your hand if you split 10s or maybe mentally raise your hand.
'cause I don't want to be embarrassed about you raising your hand if you're not counting cards.
There's never a reason to split 10s, but I just told you that counting cards was the knowledge of how many 10s, face cards and aces remain versus low cards.
So let's say you have a pair of 10s and the dealer has a 6 showing and you know, almost every card that you have not seen is a 10 or a face card or an ace, then maybe is that a time you would split 10s?
'cause the expected value or the opportunity is higher.
It is. And there's math that will support this.
And so this is sort of an advanced thing you learn.
And I remember I walked into the MGM Grand, um, with this knowledge and I was excited and I sat down at a table where I, um, bet two hands of $8,000 and it was a really high number of high cards left in the deck.
And the dealer gives me a blackjack on one and a pair of 10s on the second one and the dealer has a 6 showing.
So the blackjack, she pays me my $12,000 and then she starts to go buy my 20 because who's gonna split 10s with $8,000 on the table?
And I said, excuse me ma'am, I want to split those.
And she said, you want to what those? And I said I want to.
And then all of a sudden I was like, eh, maybe I don't wanna split those.
And I started thinking about why I didn't wanna split those.
And I realized that the predominant reason that I didn't wanna split those is I am looking around this table and everyone at this table thinks I am a moron.
If I split these 10s, everyone will be angry with me.
If I split these 10s, they will disagree with that decision.
But if they had the technology, the data, the knowledge that I had, would they maybe agree with me?
And so what I'm doing here is falling for something called group think, which I'm sure you guys see in all your businesses.
And as you think about working with new technologies like MX and new ways of doing business, anytime you have advances in technology and data, you're gonna have to do unconventional things.
And anytime you do something unconventional, it's gonna p**s some people off.
So you can't make decisions based on group think or avoiding conflict, right?
That's the ultimate — making a decision to avoid conflict.
'cause good decisions, progressive decisions are always gonna create conflict.
Okay? I don't care about these people.
I decide like I don't know any of 'em.
I'm never gonna see any of them again.
I don't care about group think, but I still don't wanna split these 10s.
And why is that? And I realize that I am afraid of losing.
I have banked this $8,000 in my head because I have 20 and the dealer has a 6.
This is a great situation for me, but again, this is the wrong way of thinking about things.
I'm being loss averse right now where I'm fearing loss more than I am embracing gain, right?
I know the expected value is higher to do this.
So why should I be afraid of losing?
Losing is figured into that expected value.
And ultimately there are many, you know, companies that are great lessons of this, right?
When I was one of the first times I spoke at Facebook, I've spoken there twice, they had 30 million users.
Then I went back there, I think two years later they had 500 million users.
It was the day they're announcing that they had 500 million users.
And I was saying this whole spiel and I got to it and I go, you guys are a perfect example.
Now that you have 500 million users, are you gonna take the same kind of risks that you took?
And before the words were outta my mouth, an executive from the back row named Chamath Palihapitiya, who I'm sure some of you guys know now from his all in podcast, he screams hell yeah.
And what he meant is he knew that for them to continue to grow, get stronger in business, they were gonna have to continue to take risks.
And they went on to buy a company called Instagram for a billion dollars, which was risky at the time, but now looks like one of the biggest bargains in history.
They bought WhatsApp, they bought Oculus.
Like they've, they've taken risks and they've grown from that.
Um, okay, don't pay attention to this title.
It didn't get changed for this, but it, it's, it's applicable.
It should say something like what I've learned or learnings.
So just mentally say learnings 'cause it doesn't make sense.
If you don't see it now you're like, wait, what, what does that even mean?
Somehow I didn't get changed when I was updating my slides.
Okay, so let's go back to, wait a minute.
Hmm. These are outta order. Okay, there we go.
We can just ignore that one then. Perfect.
Okay, so that was just a superfluous slide.
All right. You guys are all wondering like, oh my god, that moment in time, right?
Oh, I didn't actually finish telling that story.
So anyways, I split, I was so confused 'cause I was looking at the previous slide.
So of course I split the 10s, right?
I put down another $8,000, the dealer flips 'em, gives me an ace on one and a 9.
On the second one, the dealer flips the 10 to make, uh, 16 and then another 10 to make 26.
I win my $16,000, grab my other 12,000, the show's over and everyone at the table does not want to kill me.
So I basically just kinda like run away from the table with my money.
But that ability to overcome those biases to make these difficult decisions is, is uh, is a real thing.
Okay? So now back to that one story.
You guys are all like, oh my God, what happened with him and God, I'm not gonna be able to sleep tonight.
And if I know what so well of course I believe in numbers, right?
And of course I kept betting, right?
And I, you know, had that test the table, got the woman behind me screaming about her mortgage and I got these, all these people looking at me like, this kid just lost $50,000.
What's he gonna do? So I put three hands of $10,000 down, which is what the math tells me to do. On the first one I get a 9.
On the second one I get a 19 on the first one, third one I get a soft 15 and the dealer has a 6.
Showing the 9 against a 6 is a hand that I want to do what?
Double. So I put another $10,000 on that and I get a queen to make 19.
And then the ace against a 6 is the nother hand that I want to double and I do and I get a 4 on that to make 19.
So very circular now 19, 19, 19 against the dealer's.
16, right? So dealer flips the king to make 16.
And I'm in this situation to basically win back everything I just lost.
The only reason I'm in this situation is 'cause I believe in numbers and I have this like stick to it in my gut and the dealer flips a 5 to make 21.
So I lose another $50,000, the show's over and I have no money left.
So I grab no money and walk up to my room at Caesar's Palace, collapse on the floor, stare up at the ceiling, wondering myself, why is there a mirror up there?
But once I get over that, I mean I'm 21 years old, graduate from MIT I'm like, do people lie in bed and get ready?
It seems weird. Okay.
So I, I think a little bit about what do I do next in this moment in time I evaluate what do I do next?
And you know, first thing I think about is this idea of of, well maybe I'll just quit for a little while.
I'll go back to MIT and evaluate the decision.
And well that's bias to inaction.
That's not making a decision, which is the same thing as making a decision.
And then I think a lot, a little bit about this and you talked about this, this kind of concept of a long-term perspective and having MX as a partner for the long term.
I think that's so important in business.
'cause I had done quite well at blackjack up until then.
And also so much of what we were based on was a, a lot playing a lot of hands, right?
We have a small edge with variance and I need to have that same long-term perspective as I'm thinking about myself and my own career.
And it's one of the hardest things we do like at, at Twitter, I always used to say like one of our challenges, one of the smartest things that Elon did with Twitter was making it private.
Because when you're a publicly traded company and you've gotta make quarterly decisions for shareholder meetings, you're making bad decisions often.
So having a long-term perspective is incredibly important.
And then I think about this idea of losing, right?
If we have like a 51% chance to win, that means we have a 49% chance to lose, which means we are going to lose sometimes. That's okay and I can't be afraid of losing.
And then I think about trusting the process.
Had I had a bad outcome, uh, had I had a bad process or I just gotten unlucky and I'm pretty sure I had had a strong process, I feel very comfortable about that, right?
And so I think a lot about this in the moment in time that I thought about this.
And when I've told this story before, I was speaking at an event that a guy made him put on sort of legendary VC in Silicon Valley.
And the speaker before me that day was a guy by the name of Bill Gates.
So it was very intimidating to be on that stage.
And as I was speaking, you know, I got to this part of the speech and um, OD looks at me and stands up and he says, Jeff, I don't believe you.
I said, what do you mean? He says, how could you, how could you have doubted the math?
How could you have questioned what you're doing?
And I sort of like looked at him at the time and I'm like, please just sit down.
But when I got by that idea of he was right, I mean I think I always will believe in that math and I always have that stubbornness to continue going.
And my personal mentor is a guy by the name of Kevin Compton.
Kevin was the operating and managing partner at Kleiner Perkins during their heyday.
Legendary VC has been the first money in about 13 different companies that have had multi-billion dollar market caps.
And I've heard him do, he is very modest.
He's not one of those guys that will beat his chest about anything he has ever done.
But I found a small interview he did online and they ask him about VC as an asset class.
And he says, well, I, I don't know what this asset class is, but I know we do really well.
And I know the reason we do really well is we stick with our entrepreneurs.
We know the reason that they, or we believe the reason they fail is not 'cause they're not good or they don't work hard or they don't have good ideas, so they run outta capital.
And so we like to stay with them so they have a chance to succeed.
And so I think a lot about my own life where I've started four companies that have all I'm lucky to have like somewhat successful exits from, and I don't think I'm the smartest or I don't think I'm like the hardest working, but I do think I might be one of the most stubborn.
So it was that moment in time I galvanized the stubbornness and I went back down and I kept playing and over the next day I won back the hundred thousand and the last day there I won $70,000.
So I ended up leaving up $70,000.
And I do think that was a very seminal moment for me to understand the value of one being data-driven, but two being determined.
And if you think about in all the things we do in business and like MX I'm sure there's been moments in time where that determination to get to being here, having an event like this at like, it's funny because I do, you know, I've never started a company that had a, a beautiful event like this.
I can only, I look at this, I'm like, how much does this cost?
These guys can't even imagine.
But, um, anyways, if I had given up, which I probably wanted to at some times, I never would've got written a book or had a movie made about me or been able to come have a wonderful time in Park City with all of you guys.
So thank you guys.
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