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all right everybody welcome back to the
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number one podcast in the world I am
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your host Jason calanis and with me
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again couple of my besties David
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fredberg you know him as our Sultan of
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science lots to get into today Sultan
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huh how you
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doing I'm keeping busy thank you keeping
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busy jamath and I on Valentine's Day we
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had a little Trio we were on MK Ultra
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podcast and it hit number four Allin
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podcast of course number one uh trat
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Reflections on our Megan Kelly our
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triumphant Megan Kelly Valentine's
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spectacular I was fine it was good okay
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wow thanks you're such a great performer
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here giving me so much to work with
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chamath as always but it was a great
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great pod shout out to our friend and
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friend of the Pod Megan Kelly and also
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we've got an incredible Duo for the
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first time we've invited a Duo to join
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us in The Red Throne David Sax's seat
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busy saving the country but we're really
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excited Coulson brothers are with us
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thank you for having us you guys want to
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hear a great lost porn story John has
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one for you the last time we met jamaath
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was 18 years ago when we were working on
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our prior startup automatic with Harge
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and and cool tagar you were how old they
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were 17 18 19 was one of these San
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Francisco setups where it was like a
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two-bedroom apartment there was a few of
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us living there I think maybe six people
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working out of there and a normal number
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exactly normal number is to load up a
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two bed apartment with and then jamath
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you came and and visited this is what's
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so brutal about this okay I could have
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invested a
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dollar one single dollar and I would
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have made a billion dollars I remember
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meeting these guys and I was with Alan
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Morgan who was my boss at the time I was
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a junior principal at Mayfield shout out
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and I think we tried to guys I don't
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know if you remember Patrick and John I
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think we tried to invest in in the
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business or it didn't happen or then you
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ended up shutting it down but right away
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you spun back up and started stripe and
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I just watched from the sidelines the
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whole way it is such a first of all it's
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an amazing it's an well no it's an
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amazing place for silen valley where you
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can like see these people just keep
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pushing the boundaries up and up and up
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number one number two the thing that is
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such a learning for me is like why
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didn't I just pick up the phone and call
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them at any point in the last 17 years
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what am I thinking so
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brutal let your winners
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[Music]
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ride and instead we open source it to
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the fans and they've just gone crazy
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with
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[Music]
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it it is oh my God so brutal two things
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one um first you probably don't remember
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this but I remember that meeting that
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you know we offered you you you want
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something to drink we did not have a
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broad selection I think we had water or
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or milk in the fridge and and you asked
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for a glass of water um and so I went
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over to the sink and I realized that we
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hadn't really been on top of the the
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washing up so I had to sort of gingerly
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wash a glass for you to get your glass
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of water which um can't remember if you
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touched it over the course of that
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meeting but then secondly like when we
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started out with
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stripe like the fintech sector basically
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didn't exist I mean the the the word
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hardly existed and didn't exist yeah
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yeah people just didn't think that I
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mean you know teenagers weren't actually
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teenagers at the time but you know
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people in the early 20s college kids
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taking on you know PayPal or the
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incumbents or regulated Financial
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Services or whatever you know people
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just didn't think it was a good idea so
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I don't know uh you you you you
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certainly were like the vast majority of
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investors we spoke with in the first
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year or two of stri turned us down so H
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you were you were not anomalous John
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tell us what that meeting was like and
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to just take you back to the moment
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here's a picture stop stop here's a
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picture no striking here's a picture of
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pre
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pre nine figure chath oh my God and this
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is when he shopped at Macy's does that
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maybe that jogs some memories John when
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that guy walked in with his khakis and
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that light pink Brooks brother shirt
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what did you think I don't know I think
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you can uh you can go back and find
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historical photos of anyone and use them
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to like if that's the worst historical
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photo you have that's pretty that's
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pretty lightweight stuff exactly Jason
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do you want to tell everyone in the
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audience what stripe is and I mean do we
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have to okay stripe processes payments
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this is a 10 plus year old startup that
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basically if you're a startup company
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and you want to do transactions you use
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stripe for example the all-in startup
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uses stripe to pay for the tickets and
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then we give these guys for some reason
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a half million dollars every year no
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discount they don't sponsor the event
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and uh they're making a fortune they got
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10,000 employees and uh the company
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changed the world we've never been uh
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we've never been offered to sponsor the
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event I didn't know this was the this
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was an option but he hit us up for a
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half Millie last year I mean maybe this
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year you we can hit you up negotiate it
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live that's broadly accurate I would
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just fact check that it's nowadays not
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just startups even though they run on
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strip also the world's artist
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Enterprises Herz Amazon Ford all these
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kind of companies and so when we started
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out with stripe we thought it would only
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be for startups like we thought those
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were the people who needed a problem
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solved and we thought payments was
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broken for them and as time went on we
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just found out it was kind of broken for
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everyone and so sorry and is it public
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how much volume you guys do a year do
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you guys talk about that it's more than
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a trillion dollars a year a trillion
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dollars a year is process through your
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network yeah which works out to you
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Global GDP is around 100 trillion year
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so it works out to around 1% of global
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GDP and you could say well you know GDP
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is is final goods and and you know
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stripe processes more than only final
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goods so it's not if only you say that
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okay well look you could say it's not
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exactly the right or a fair comparison
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or something but but stripe mostly is
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used to sell final goods so I think it's
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I think it's reasonable and just the
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other thing I'd say is you know people I
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think reasonably think of stripe as a
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payments company because you know that
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is certainly what we started out doing
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and uh and it's uh certainly the largest
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line of our business but the thing we
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kind of realized a couple years in is
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that you know what business like the the
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the structural secular thing that's
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happening is that every kind of money
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movement is going from being manually
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orchestrated to being orchestrated by
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software
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and there's you know some program
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somewhere making the thing happen and so
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because of that like just because of
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what we hear from customers and the the
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pull there we're now you know helping
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with lending we're helping with card
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issuance we're helping with Treasury and
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money storage we're helping with
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crossborder money movement stable coins
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we got to talk about St coins got a
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stable yeah why' you do a stable coin
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stable coins are finally happening and
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they're really useful like we followed
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crypto for a long time the Bitcoin white
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paper dropped in 2008 the year before we
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started working on stripe and so it's
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been funny where stripe and crypto have
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grown up together and you know we tried
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to make Bitcoin happen as a payment
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method on stripe just wasn't that good
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as a payment method I mean it's good as
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a store of value as kind of a gold
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substitute but transactions are slow
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transactions are expensive you never
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know exactly how much you're going to
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get because it's not denominated in
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dollars the stable coins are now really
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good if you look at you know something
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on an ethereum L2 or salana or something
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like that and so we bought a company
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called bridge late last year who is
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building the stripe of stable coins and
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so if you're I mean I think you guys
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have talked about them a little bit but
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you know people like SpaceX using them
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for treasury management people using
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them to offer US dollar services to
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people all around the world just stable
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coins are I think the first really big
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payments use case and I think it's
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finally coming because the tech is good
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enough is there a moment guys where is
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it a regulatory event where you'll say
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the Visa Mastercard dapoli can get
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challenged is there a set of boundary
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conditions that you have written down
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where when you can check a few of these
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boxes you know that it's time for those
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companies to get dismantled the behavior
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we're seeing right now is that stable
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coins are most interesting and seeing
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most adoption where there is some crossb
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component and so uh you need to manage
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corporate treasury around the world you
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want to send remittances to people in
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other countries often it's people in
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other countries want to whole dollar
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balances or things like that what we've
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always seen is that I don't know in the
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US things work pretty well in Europe
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things work pretty well and so we even
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see this pre- crypto where the way
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people pay for stuff has been radically
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changing you know UPI in India picks in
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Brazil you have all these designed by
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central banks actually really good kind
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of government run venmo Solutions those
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have all happened in Emerging Markets
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broadly and not in the US and Europe we
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certainly keep our eyes peeled for that
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changing at some point but I think right
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now I don't know P would you characteriz
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it that way that like a lot of the
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interesting stuff we see is happening
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internationally yes so you know with
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respect to visa and Mass Master Card I
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think an important thing to keep in mind
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is that most of the interchange fees
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that are charged to Merchants and you
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know you mentioned what we charge the
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all-in podcast you know the vast
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majority of that flows right back to the
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uh to the issuing Banks uh in the form
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of interchange and almost all of that
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flows right back to the consumers in the
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form of you know the lending that the
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that the you know the cards themselves
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represent but then also in card rewards
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like card programs are not actually big
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profit pools uh for most of the major
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Banks and so I think any you know any
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substitute for for visa and MasterCard
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in that sense you know the sort of a
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question of well are the consumer
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rewards going to go down are the
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consumer protections going to go down
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will we be extending less consumer
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credit and maybe other points in that
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space are viable but you know it it is a
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set of trade-offs and it's not as simple
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as this this enormous rent extraction
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happening John's totally right I think
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the interesting use of stable coins is
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cross border is outside the US I mean
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the big use case that's taking off right
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now is consumers in other countries
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seeking to hold dollars you know we in
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the US here today you know we obviously
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benefit from being able to do that the
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vast majority of people in the world
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have kind of a are subject to a worse
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currency worse in the sense that it's
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less stable H it's more inflationary you
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know storing savings is is is much less
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favorable uh you know if you look at the
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nirra for example there are a lot of
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people in Nigeria and the the currency
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there has devalued by a factor of you
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know three or four over the last couple
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years and so that use case of consumers
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being able to store dollars is really
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exploding and we think about this really
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as kind of an analogy to the to the euro
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dollar system where you know the euro
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dollar system in the 70s and 80s this
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was a way for companies to store dollars
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and to you know have something more
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stable and and and reliable and so forth
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but it was only except I mean I think
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the minimum transaction size was like a
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million dollars so there's kind of a
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very high barrier to entry whereas with
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stable coins now you can be a consumer
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in Ecuador and you can have like A1 us
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balance and that was just not a product
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that was accessible to you before and so
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I think it's I think it's a really big
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deal you know certainly for people in
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those countries and in some sense also
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for the us because the dollar status as
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the world's Reserve currency I think is
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is is know process of becoming much more
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deeply established yeah that is the huge
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win for allowing stable coins and you
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know making them legal giving them rails
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putting aside tether and all the bans
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and fugazy stuff they've been doing or
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have done and all the lawsuits that
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they've lost and the bands in different
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countries having usdc having yours and
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other ones in the United States means we
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can regulate them and they have to buy
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treasuries and so okay dollar Supremacy
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continues and that's fantastic but right
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now Allin just using the example could
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accept
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payment in stable coin correct with
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stripe we just check a button we get
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stable coins yes okay so then the next
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piece I have we follow with you
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afterwards to make sure we I'm actually
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really excited that you guys are going
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to be sponsoring the all in Summit this
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year that's actually exciting super
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exciting no freeberg is great at
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securing the bag yeah the thing that's
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interesting though is if let's say we
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had a Millie sitting in our stripe
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account and then we had to pay a venue
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or pay other vendors and we're sitting
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there in uh yourk coins called bridge is
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that what it's going to be called or is
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called bridge is the is the company is
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the platform and you know that's like
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there there okay so they're not
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stra correct correct but you all have a
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stripe stable coin at some point yeah
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like one Bri actually has one already
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yeah Bridge has a a small stable coin
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for but we don't need to get into
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details but but bridge is primarily set
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of software apis got it but you'll
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obviously have a strip stable coin the
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point is if you turn on stable coin
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acceptance with um you know for for all
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in today that'll use usdc perfect now
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could we then go pay people from our
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stripe account and then you could lower
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our fees if they were also doing stable
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coins is that exist today or is that
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something coming next year look you
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could pay people in stable coins but
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again to the point of where you'll see
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adoption first paying people via bank
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transfer in the US like yeah it's not
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great it's kind of slow everything like
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that but it's fine it's not the biggest
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problem today yeah yeah exactly whereas
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the people who are using Bridge it's
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like scale AI is you know they have to
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pay the contractors all around the world
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and when you want to get money to people
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in the Philippines that starts to get
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really annoying and expensive and so
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just from our point of view the like
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real hair on fire problem is the
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international stuff and domestic I
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assume you're paying domestic suppliers
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it'll come later I think you're I think
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I think you're answering narrowly to you
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know stable coins I think everything you
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just said is is right but I will say I
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think Jason your intuition that man it's
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really inefficient and annoying to you
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know engage in B2B transactions and to
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get these invoices paid and like the
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whole system and if you look at most
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companies they're losing 1 two 3% of
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Revenue to AP and AR now some of that
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might be because of the transaction
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rails themselves a lot of just because
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of you know baroke inefficient processes
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uh where you have humans sending
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invoices humans reconciling them you're
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trying to line up transfers in your bank
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account statement and figure out you
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know what corresponds to what and so on
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and that's super inefficient and so
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we're separately I mean Cil con would be
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part of the solution here but but but
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there's more to it separately we're
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trying to solve that with a product
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called stripe billing which we actually
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just announced last week has passed you
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half a billion in uh in ARR and so uh we
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we could send an invoice to somebody
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which right ex so it's like fresh books
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or whatever those other products in the
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market are all amazing all the back
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office is there a version of a network
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effect inside of stripe for their
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customers where if I just allowed you
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guys to just be integrated into my GL
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somehow and you gave me some kind of
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phantom bank account why isn't it just a
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ledger entry if I'm just making a
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payment from me to somebody else that's
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also on strip the thing we really want
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to solve is all the calculation the ID
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verification the risk like those are the
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things that are actually expensive um uh
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if you if you look at this flow uh it's
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where companies lose their money today
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having said that you're right um you
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know we're the fraction of money
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movement on stripe where you know the
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two counterparties are both part of the
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stripe network is obviously growing and
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so I think that'll be another way we can
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reduce fees over time although again I
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actually think the biggest part of that
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is is going to be because we reduce
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fraud like both counterparties are known
00:15:01
and like I talked to a company a payroll
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company recently and they were
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describing you know how big a deal it is
00:15:07
for them that you know people sign up
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you know frauding companies whatever and
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you know they can lose millions of
00:15:10
dollars in a single attack and so having
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some kind of trusted node rather than
00:15:15
just like routing an account number that
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would be a really big deal for them look
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you have a very good pulse and what I
00:15:21
would say is that as a subset of the
00:15:23
economy you probably reflect a large
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part of the global economy have you ever
00:15:28
been approached or have you ever
00:15:30
considered on a regular basis publishing
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some sort of economic sentiment one of
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the big things that we've talked about
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is how many backward revisions there are
00:15:39
to everything from non-farm payrolls to
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GDP that they've become so unreliable
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and so it's very difficult for people
00:15:46
that are transacting in Market to know
00:15:49
what to
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do have you guys ever thought about that
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because I'm sure that you have a much
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more accurate sense of where the economy
00:15:55
is than many other people we have and I
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feel a bit ruthful you know with you're
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asking that question because I feel like
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on some level we should have done it um
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the thing that makes it kind of tricky
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is because two two things one stripe is
00:16:06
not like a full CR section of the
00:16:07
economy you know we're more biased
00:16:08
towards online we're more biased towards
00:16:10
Innovative companies you know whatever
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that that you know it's kind of net that
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out somehow and you know there can be
00:16:14
these stories where I mean during Co
00:16:16
like the online economy was doing great
00:16:18
H the offline economy was sort of a
00:16:19
different story so the interpretation
00:16:20
can be a bit tricky but then just the
00:16:21
second thing is the stripe business is
00:16:22
growing so quickly and changing so fast
00:16:24
that again you know it's not necessarily
00:16:26
representative of of the EC economy and
00:16:29
even if stripe is way up year overy year
00:16:30
you know you you have to be a bit
00:16:31
hesitant in drawing conclusions from
00:16:32
that having said that I think in
00:16:34
principle you could draw you know some
00:16:35
conclusions and you know one thing we we
00:16:37
we did look at uh was just inflationary
00:16:39
data over the last couple years and I
00:16:42
think you can construct and the team did
00:16:44
construct a pretty reliable kind of
00:16:46
leading indicator huh for inflation and
00:16:49
so we would like to share that openly
00:16:52
because you know I think it's I think
00:16:53
it's a public good forther to be better
00:16:54
and more reliable economic data all
00:16:56
right freeberg before we get into the
00:16:57
doc you got any question for the boy
00:16:59
here if you were to kind of build the
00:17:01
financial system from scratch today
00:17:05
we've got Swift we've got banks that
00:17:08
store assets we have credit cards and
00:17:12
these credit card networks then we've
00:17:14
got transaction service providers that
00:17:16
sit on top of this what's the right
00:17:18
solution if we were to build a financial
00:17:20
system for the world from scratch today
00:17:23
and can you guys see a world where we
00:17:24
Bridge away from the credit card
00:17:26
networks where we move out of some of
00:17:28
these Legacy systems or they so deeply
00:17:31
ingrained and everything that it's it's
00:17:33
going to continue to be this thing where
00:17:34
we've got to build these complicated
00:17:36
Solutions into an around the legacy of
00:17:39
financial infrastructure I'll give my
00:17:41
view and then I'm curious about um
00:17:44
Patrick has I would say firstly there is
00:17:48
just general Tech scalability you know
00:17:49
there's the um you know the finance
00:17:51
industry has its version of the M shafts
00:17:53
for sure where uh everything should be
00:17:55
uh you know highly scalable in real time
00:17:57
and I think in a way stable coins are
00:17:59
solving something that you would you
00:18:01
don't technically need full
00:18:03
decentralization to do but the ability
00:18:05
to make kind of realtime payments any
00:18:06
hour of the day or night is a useful
00:18:08
property and again some private systems
00:18:10
have uh also built that I think a big
00:18:12
one for us is trust and the fact that
00:18:16
the fraud problem hasn't really been
00:18:18
solved in online payments a big reason
00:18:19
people come to stripe is basically we
00:18:22
are a reputation Network across the
00:18:24
internet economy and so when someone
00:18:26
comes and buys something from a stripe
00:18:28
user
00:18:29
93% of the time we have seen that card
00:18:31
before and so the merchant can know
00:18:34
something and know that they can trust
00:18:36
this end user and it's gotten to the
00:18:38
stage now where if someone comes along
00:18:40
and buys with a credit card if they're
00:18:42
you know signing up with an email
00:18:43
address or a phone number or something
00:18:45
that we haven't seen before that is just
00:18:47
ipsofacto
00:18:48
suspicious because you know they are
00:18:51
coming along and maybe trying to a
00:18:52
stolen credit card or or or or something
00:18:54
like that and so a big part of what
00:18:56
stripe ends up doing is act as a
00:18:59
reputation Network to keep fraud out of
00:19:01
the system that maybe you would have
00:19:03
wanted to design in from from day one
00:19:06
well In fairness jth told me I could use
00:19:08
that credit card anytime I wanted I
00:19:10
don't think he remembered but I think
00:19:12
you need to turn my account back on and
00:19:13
freeberg I just got news from our CEO
00:19:17
John MasterCard just canceled their
00:19:18
sponsorship of all in Summit so this is
00:19:21
costing us a fortune this podcast so far
00:19:23
two things one to your point about just
00:19:25
all these different networks and so
00:19:26
forth I think stable coins are going to
00:19:27
be a big part of
00:19:29
a big part of the solution actually
00:19:30
don't think that's going to supplant all
00:19:31
the consumer facing networks I think
00:19:32
we're going to see consumer facing
00:19:33
networks built upon and that you know
00:19:35
substantially leverage these things but
00:19:36
I think stable coins will probably be
00:19:37
the common Rail and then just secondly I
00:19:39
think part of what you're hearing is
00:19:40
most businesses lose more money to fraud
00:19:43
than they do to the kind of pure
00:19:44
transaction cost themselves and you know
00:19:46
you're hearing us talk a lot about fraud
00:19:47
here uh and that's because one it's just
00:19:49
it's it's a huge economic cost for these
00:19:51
businesses today and there's even
00:19:53
indirect costs where you make the
00:19:54
consumer experience more hostile because
00:19:57
you have to protect against uh you know
00:19:58
possible fraud like you know why why do
00:20:00
you have to type in all lock out my bank
00:20:02
account yeah all this stuff exactly but
00:20:04
then secondly I think these we can just
00:20:05
see in the data these problems are
00:20:07
actually getting worse and harder
00:20:08
because you know ml AI
00:20:12
globalization yeah exactly and so like
00:20:15
you know various fraud metrics across
00:20:17
the industry and the ecosystem are way
00:20:18
up over the last couple years now and
00:20:19
striped actually down by 80% but it's
00:20:21
it's really becoming a cute issue all
00:20:23
right and we'll get into uh staying
00:20:24
private longer and when you guys are
00:20:26
going to pull the IPO trigger later in
00:20:27
the show but we got to get through this
00:20:29
docket we got so many great topics to
00:20:30
talk about let's get to our first story
00:20:32
here it's a kind of a fun one Jamie
00:20:34
Diamond went on a rant about remote work
00:20:37
and and zoom uh in a town hall and uh
00:20:41
here's a snippet a lot of you were on
00:20:43
the zoom and you were doing the
00:20:45
following okay you know looking at your
00:20:47
mail sending text to each other when ask
00:20:49
the other person is okay not paying
00:20:52
attention not reading your stuff you
00:20:54
know and if you don't think that slows
00:20:56
down efficiency creativity creates
00:20:58
rudeness and stuff it does okay and when
00:21:01
I found out that people are doing that
00:21:03
you don't do at my goddamn meetings you
00:21:05
go to meeting with me you got my
00:21:06
attention you got my focus I don't bring
00:21:08
my goddamn phone I'm not sending text to
00:21:10
people okay it simply doesn't work the
00:21:13
Young Generation is being damaged by
00:21:15
this that may they may or may not be on
00:21:17
your particular staff but they are being
00:21:19
left behind they're being left behind
00:21:21
socially ideas meeting people in fact my
00:21:24
guess is most you live in communities a
00:21:26
hell of a lot less diverse than this
00:21:28
that's not how you run a great company
00:21:30
we didn't build this great company by
00:21:32
doing that by doing the same semi
00:21:34
disease that everybody else does colon
00:21:37
Brothers tell us about how you run
00:21:38
stripe are you remote does this resonate
00:21:41
with you four years after uh we've come
00:21:43
out of the
00:21:44
pandemic I love listening to Jamie
00:21:46
Diamond rants like I feel like that's
00:21:48
business ASMR um business ASMR that
00:21:53
itself s to be a great podcast I was
00:21:55
about to say I'm subscribing that's an
00:21:56
instant $10 a month subscription
00:21:59
what do you think yeah I don't know
00:22:01
people just said a lot of sh during the
00:22:03
pandemic like do you remember it's like
00:22:05
oh handshakes are going to be over
00:22:06
business travel is going to be over
00:22:08
every company is going to be fully
00:22:09
remote I would say stripe
00:22:11
broadly is in a pretty similar spot to
00:22:13
where it was beforehand which is most
00:22:16
people go into an office like most
00:22:17
people are you know uh part of our San
00:22:19
Francisco office or New York or Dublin
00:22:21
or or Singapore wherever and then we
00:22:23
have a bunch of people also who work
00:22:24
remotely I think kind of obviously you
00:22:28
know Jimmy is right on some points I
00:22:30
think also working remotely has had a
00:22:32
bunch of benefits where there's a way
00:22:34
larger talent pool available to
00:22:36
companies like stripe and there's a lot
00:22:38
of people you know you see uh kind of
00:22:40
the two body problem where it allows a
00:22:42
lot of couples where you know maybe one
00:22:44
partner is assigned to some Hospital in
00:22:47
Idaho and like they don't get to choose
00:22:49
what hospital necessarily they got
00:22:50
assigned to and the other person gets to
00:22:51
work a a high paying Tech job and so I
00:22:54
don't know I think when like like one of
00:22:56
the theories for declining dynamic in
00:22:58
the US in declining tfp is that
00:23:00
allocative efficiency uh of of you know
00:23:02
people declined as women enter the
00:23:04
workforce because now you have you know
00:23:07
what John describes this two body
00:23:08
problem where you know both people have
00:23:09
to make coordinated
00:23:11
switches and
00:23:12
uh remote work Sol it actually yeah
00:23:16
freeberg you're running a company now
00:23:18
you're the CEO of ohalo tell us uh does
00:23:21
this resonate with you what do you think
00:23:23
especially about younger people his
00:23:24
point and like being rude or being
00:23:26
focused being in the media and then like
00:23:29
maybe there's too many meetings where
00:23:30
people are partially paying attention
00:23:32
maybe there should be half as many
00:23:33
meetings and people should be paying
00:23:34
attention what do you think well there's
00:23:36
always room for optimization there we we
00:23:38
deal with this too too many meetings too
00:23:40
many people I think what was most
00:23:41
striking for me about the Jamie Diamond
00:23:43
rant and the resonance it seems to be
00:23:45
having particularly in Silicon Valley
00:23:47
and particularly with folks that are in
00:23:49
leadership positions or on boards is
00:23:52
that this is another example of what I
00:23:54
think is kind of a different tenor for
00:23:57
leaders in business right right now
00:23:59
relative to where we were a few years
00:24:00
ago leaders are starting to step up and
00:24:03
speak their mind and speak more directly
00:24:06
and lead from the front rather than lead
00:24:08
from the back I think the last couple of
00:24:10
years and I would say that the whole
00:24:12
kind of transition a away from wokeism
00:24:15
and coddled employee workforces which is
00:24:17
something that a lot of folks talk about
00:24:19
I'm I'm not trying to just characterize
00:24:21
it I'm just saying that's the
00:24:21
characterization that's been placed on
00:24:23
it is that the employees made the
00:24:25
decisions and then the leaders kind of
00:24:27
said okay I'm Ed to the employees whims
00:24:29
and needs and look at what's gone on
00:24:31
with Zuck he said you're with me you're
00:24:33
against me here's a buyout option Elon
00:24:35
obviously was an Exemplar of this at
00:24:37
Twitter uh We've now seen this become
00:24:41
coinbase Brian and his letter and we've
00:24:43
now seen this become I think a bit more
00:24:45
of a standard in the kind of emergence
00:24:47
in the postco era that leaders can lead
00:24:50
from the front speak directly and say
00:24:52
this is the way things are going to be
00:24:53
my job is not to coddle my employees my
00:24:56
job is to lead my employees so that our
00:24:57
organiz
00:24:58
our team wins and we achieve our mission
00:25:01
that's the objective it's not to create
00:25:03
a family workplace for everyone to be
00:25:05
happy all the time it's to help the
00:25:07
organization succeed and so I think I
00:25:09
have heard from people individually I've
00:25:11
seen this tenor shift underway right now
00:25:14
um and I think that Jamie Diamond is
00:25:15
another kind of Exemplar of this that
00:25:17
that seems to have some resonance all
00:25:18
right shth I want you to respond
00:25:20
specifically to this next clip let's
00:25:22
play the second clip about
00:25:24
organizational bloat every area should
00:25:26
be looking to be % more efficient if I
00:25:29
was ready to depart with 100 people I
00:25:31
guarantee you if I wanted to I could run
00:25:33
it with 90 and be more efficient I
00:25:35
guarantee you I could do it just I could
00:25:37
do it in my sleep and the notion these
00:25:40
bureaucracies I need more people I can't
00:25:42
get it done no because you're you're
00:25:44
feeling that request that don't need to
00:25:46
be done your people going to meetings
00:25:47
they don't need to go to someone told me
00:25:49
to approve some his wealth management
00:25:51
that they had to go to 14 committees I
00:25:54
am dying to get the name of the 14
00:25:56
committees and I feel like firing 14
00:25:58
chairman of committees I can't stand it
00:26:01
anymore all right shth the bloated
00:26:03
bureaucracy at big companies your
00:26:05
thoughts well you know there's that
00:26:07
adage that says something akin to 50% of
00:26:10
advertising is useless we just don't
00:26:12
know which 50% yeah I think it's
00:26:14
probably true for most corporate
00:26:17
structures in general which is that a
00:26:20
lot of the organizational bloat has
00:26:22
evolved because of the way that people
00:26:26
have responded to how you use technology
00:26:30
so meaning if you went looked back 50
00:26:33
years ago if you look at that famous
00:26:34
picture of the Microsoft early team they
00:26:37
didn't rely on software necessarily
00:26:39
there wasn't Salesforce there wasn't
00:26:41
workday there wasn't all of this
00:26:44
infrastructure and so instead they
00:26:45
probably organized by what they were
00:26:47
good at and they just tried to do things
00:26:49
efficiently and I suspect that many
00:26:51
companies in the absence of Technology
00:26:53
found a way to just be very efficient
00:26:55
that started to change when you had
00:26:57
these rigid demarcations of where one
00:26:59
job ended and another job started and
00:27:02
part of why that happened is because you
00:27:03
had all this software that went in and
00:27:05
convinc people this will create
00:27:07
efficiency but in return the chief
00:27:09
marketing officer's job is X Y and Z
00:27:11
this is how the roles are defined this
00:27:14
is how people do it and so I think that
00:27:16
the reason why things have become so
00:27:18
bureaucratic and Bloated is that there
00:27:20
is just this propensity to run towards
00:27:23
software because you think it's a
00:27:26
solution at best it's a
00:27:29
symptomatic Aid it doesn't address the
00:27:31
root cause and in fact it promotes
00:27:33
bureaucracy and it promotes the bloat
00:27:35
that Jam's talking about and if you look
00:27:37
at Jim's p&l he spend $6 billion dollar
00:27:40
a year on it and I suspect that if you
00:27:43
screamline that you'd actually have half
00:27:45
as many people because they'd be doing
00:27:47
the job in a wholly different way and by
00:27:50
the way the the counterfactual to it is
00:27:52
if you look at companies like Facebook
00:27:54
or Google or Tesla or SpaceX who design
00:27:58
and I'm sure stripe is the same who
00:27:59
designs a lot of stuff internally that's
00:28:02
custom built for their or I think the
00:28:05
way that you see this in the revenue per
00:28:06
employee and a bunch of these other
00:28:08
metrics in terms of the efficiency of
00:28:09
those companies so I think what he is
00:28:11
talking about is that he is a
00:28:14
victim of this push to productivity
00:28:16
because he would look like a lite if he
00:28:18
didn't adopt technology but by adopting
00:28:20
the off-the-shelf stuff he introduces
00:28:23
organizational blo because these things
00:28:25
are demarked very very rly you got the
00:28:27
marketing team as you mentioned using
00:28:29
HubSpot and then you got like the sales
00:28:31
team using I don't
00:28:32
know organizational bloat the other
00:28:35
thing I just want to say on the first
00:28:36
topic is I've mentioned this
00:28:39
before other than Engineers who are who
00:28:43
are naive but can be extremely
00:28:45
productive from day one there are very
00:28:47
few other job types where naivity is an
00:28:51
asset most people early in their career
00:28:54
are in a jcurve where they are
00:28:56
negatively contributing and the
00:28:58
go everybody down and the whole goal is
00:29:01
that you invest in these people so that
00:29:02
they come out of the J curve there are
00:29:04
probably other jobs that are like
00:29:05
engineering but many many are not and so
00:29:09
I think it's important to get the kind
00:29:10
of mentoring you get by being in an
00:29:12
office and in the absence of that I
00:29:14
think these young people like Jamie said
00:29:16
are totally lost that's that's on them
00:29:19
but then for the company they're
00:29:20
completely unproductive and useless
00:29:22
which is on us hey John uh Toby I I
00:29:25
don't know if you know Toby from Shopify
00:29:26
but he did this like zero based
00:29:28
budgeting kind of concept for meetings
00:29:30
he just purged all meetings at the
00:29:31
beginning of the year he just like
00:29:32
deleted everybody's meetings from the
00:29:35
top down I'm curious how you think about
00:29:38
bloat and just all of these meetings and
00:29:41
committees do you worry about that at
00:29:42
strip we know Toby very well and I don't
00:29:45
know I always feel like yeah we should
00:29:48
I'm tempted to uh take some of the ideas
00:29:50
like we haven't done the meeting
00:29:51
deletion one and you just say oh the
00:29:53
meetings get recreated but they measured
00:29:55
it and they didn't it sounds like uh and
00:29:58
I do always enjoy Toby's perspective
00:30:00
which I think that you know many
00:30:02
organizational problems are in fact
00:30:04
software problems and you know you just
00:30:05
need to write a script to literally like
00:30:07
I think he wrote the script to all the
00:30:09
meetings uh you know from the Google
00:30:11
Calendar instance but uh there's kind of
00:30:13
this Purity that uh uh you're you're
00:30:15
over intellectualizing your problems and
00:30:17
I do agree with jamat on the remote
00:30:18
thing where like it's it's very
00:30:21
dangerous I one thing that can be
00:30:23
dangerous with as CEOs think about this
00:30:25
stuff is I think there is these unfair
00:30:29
anecdotes that feel unfair that get
00:30:30
people really riled up the quiet
00:30:32
quitters the anti-work subreddit you
00:30:34
know all these talk of people working
00:30:35
two jobs and that generates a lot of
00:30:38
energy with corporate leaders but you
00:30:40
don't want to design your policies
00:30:41
around like the bottom 5% of the company
00:30:44
that would be a horrible mistake yeah
00:30:45
you want to design your policies against
00:30:47
the top town and we have some like
00:30:48
outrageously productive remote people
00:30:50
and they're off and again the cabin
00:30:51
Idaho somewhere just you know Co coding
00:30:53
up a storm the thing that we have seen
00:30:55
and interestingly we measured this
00:30:58
before covid cuz we were doing a lot of
00:31:00
remote hiring and we wanted to see we
00:31:02
wanted to see how much we should lean
00:31:04
into it is that it is not good for early
00:31:06
career people we could actually measure
00:31:07
it in our productivity Data before the
00:31:09
whole discussion about remote work
00:31:10
happened during covid and it's bad from
00:31:12
a work point of view it's also just bad
00:31:14
from a personal point of view where they
00:31:16
go mad because they're 23 years old and
00:31:18
they're not Sol conf exactly literally
00:31:22
solitary confinement it's ridiculous and
00:31:25
by the way breaking news here Jamie
00:31:27
Diamond now now uh knows which 2,000 or
00:31:30
I'm sorry
00:31:30
1,739 employees to lay off first there
00:31:33
is a coworker.org petition to get Jaimie
00:31:37
to retract his statement so the optin
00:31:40
has been created if I know Jamie I know
00:31:42
he'll be uh retracting that statement
00:31:44
right away absolutely he will bend to
00:31:46
the pressure of those 1700 mids Patrick
00:31:49
how do you deal with mids at stripe how
00:31:51
do you deal with the mids the people who
00:31:53
I'm not saying you have any but maybe
00:31:55
you've run into because you got over
00:31:56
10,000 employees when somebody's average
00:31:59
that must make you crazy how do you deal
00:32:01
with it no the median employee at stripe
00:32:03
is awesome the median employee Atri
00:32:05
employee at stripe is is not the median
00:32:08
person in the population at large
00:32:10
although I think the median person in
00:32:12
the country is we um you know we
00:32:14
employ well no I was using the term mids
00:32:17
mids are people who are just average
00:32:18
people not the above average strip
00:32:20
people who opt into that but how do you
00:32:21
deal with low performance is kind of
00:32:22
what I'm getting at well look you need
00:32:24
to have an aggressive Performance
00:32:25
Management culture and to stay on top of
00:32:27
that and look at it's not it's it's not
00:32:29
good for anyone to keep those people
00:32:30
around because nobody likes feeling that
00:32:32
they aren't succeeding and so if those
00:32:34
people are you know their careers aren't
00:32:36
advancing they're not getting you know
00:32:37
positive feedback from their manager
00:32:39
from their peers they aren't shipping
00:32:40
things like whatever this is just like
00:32:41
not a good equilibrium for anyone so we
00:32:43
really try to you know stay on top of
00:32:44
that we track it closely the thing just
00:32:46
on this discussion broadly to say is I
00:32:48
think people very readily fall into a
00:32:50
kind of
00:32:51
normative moralizing perspective on this
00:32:54
stuff of people should be in the office
00:32:56
they shouldn't be in the office but like
00:32:57
there's a lot of should here I think
00:33:00
it's helpful to just one kind of as John
00:33:02
referenced with you know some of the
00:33:03
analysis just you know be quite
00:33:04
empirical and objective and just like
00:33:06
look at what the data says and and then
00:33:07
second just recognize there's a lot of
00:33:09
heterogeneity as in people have
00:33:11
different preferences people have
00:33:12
different abilities to work effectively
00:33:15
you know when they're by themselves and
00:33:16
you know some don't organizations are
00:33:18
doing different kinds of work Nvidia you
00:33:21
know last I checked is doing pretty damn
00:33:22
well and you know Jensen is on the
00:33:24
record of saying he know doesn't give a
00:33:26
about where you work coinbase
00:33:28
Shopify you know they're all these you
00:33:29
know remote first companies and then you
00:33:31
know I was recently ched the folks at
00:33:32
Jane Street and they really believe that
00:33:35
you know being collocated and be able to
00:33:37
share ideas on the trading floor and so
00:33:39
forth is is really important but I don't
00:33:41
think these pictures are NE or these
00:33:43
worldviews are necessarily contradictory
00:33:44
they probably hire different kinds of
00:33:45
people or in different kinds of
00:33:46
businesses and so on and so I don't know
00:33:48
I guess I'm just skeptical of flat
00:33:50
shoulds in this space and many to yeah
00:33:54
many paths to Heaven uh all right so
00:33:56
let's move on to our next story
00:33:59
last we just keep in mind and labor
00:34:01
productivity in the US is up like 20% in
00:34:04
the last 10 years and so just like again
00:34:05
you just you just look at the data just
00:34:07
the median person in the economy or the
00:34:08
average person is H is producing 20% on
00:34:11
an inflation adjusted basis more than
00:34:12
they were 10 years ago yeah that's going
00:34:14
to keep wrapping up with AI and all
00:34:16
these amazing tools that are coming out
00:34:18
we'll leave that on the side for now
00:34:19
because that would be an hourlong rabbit
00:34:20
hole we could jump down but we got to
00:34:22
get back into Doge the number well I've
00:34:24
heard a couple criticisms of Doge one of
00:34:26
them is it's one-sided we're only
00:34:27
hearing about you know people on the
00:34:29
left doing griffs and US Aid the other
00:34:32
one is hey you're you're pointing at
00:34:35
little tiny things like USA when are you
00:34:36
going to get to defense spending and
00:34:39
Social Security well here we are
00:34:41
Washington Post is reporting that in
00:34:43
between doing sets of 47 push-ups
00:34:46
defense secretary Pete hegf asked senior
00:34:49
leadership at the Pentagon to develop a
00:34:51
plan to cut 8% from the defense budget
00:34:55
each of the next five years that's
00:34:56
compounding 8% here's a chart we're
00:34:59
talking about close to 300 billion in
00:35:01
savings over 5 years if uh they hit
00:35:04
which isn't a crazy Target 8% a year
00:35:06
it's just crazy in our country where we
00:35:09
haven't even been able to have our
00:35:11
defense department pass a basic audit if
00:35:14
you've seen those type of reports let's
00:35:18
pause there and just talk about military
00:35:21
spending chth I think that military
00:35:24
spending needs to sit Downstream from
00:35:29
technology because if you if it doesn't
00:35:31
you're sort of misappropriating the
00:35:33
money and what I mean is that we're
00:35:36
inventing incredible capabilities in Ai
00:35:39
and autonomy I think that you need to
00:35:42
take those things first and figure out
00:35:43
how to productize them because I think
00:35:45
that builds the kind of modern war
00:35:46
machine we need otherwise what happens I
00:35:50
tweeted about this Nick maybe you can
00:35:51
find it but like the CBO red flagged a
00:35:54
project where the Navy was about to
00:35:57
appropriate $1.2
00:35:59
trillion to build frigs now there's a
00:36:02
body I think of of military planning
00:36:04
that says this is a projection of power
00:36:06
and so you need to spend this kind of
00:36:07
money because people want to see the big
00:36:09
boats and the Big Iron in the water okay
00:36:11
and and maybe there's something about
00:36:13
that but the reality is you can't be
00:36:15
spending three or four billion dollars a
00:36:17
boat and taking you know eight nine 10
00:36:20
years to build these things it's so this
00:36:22
is not sustainable and part of why they
00:36:25
do that is it's not coupled to what's
00:36:28
actually happening with respect to
00:36:29
Innovation where there are core pockets
00:36:32
of companies Sanic just announced a $600
00:36:36
million raise today sa drone announced
00:36:40
hundreds of millions of dollars of
00:36:41
contracts with the Navy andril is doing
00:36:43
that with the army so I think that
00:36:45
military spending needs to happen
00:36:46
Downstream from what's actually
00:36:48
happening in technology broadly speaking
00:36:51
we don't have that what you have instead
00:36:53
are system integrators with extremely
00:36:56
deep connectivity that are able to
00:36:58
contract well not necessarily to invent
00:37:01
well freeberg any thoughts there on
00:37:05
cutting defense spending obviously we
00:37:07
have uh to chat's point amazing Founders
00:37:11
like my guy pommer lucky cutting the
00:37:14
cost of very important uh AR he hates
00:37:17
that's my guy my bestie oh no we it's
00:37:19
all a joke everybody calm down we just
00:37:22
have a little hates you Jason heally
00:37:25
listen I know all the board m
00:37:29
Rel to your Ranch he loves J he loves it
00:37:33
everybody needs a foil uh it's all sorts
00:37:35
of problems for the rest of us when you
00:37:37
go out and talk about people for no
00:37:38
reason it's great what are you talking
00:37:39
about I never talk about stripe
00:37:41
guys you don't have any beef with
00:37:43
employees mids for no reason for no
00:37:45
reason you're just like oh what about
00:37:46
your mid was a hypothetical yeah okay I
00:37:49
did say that you you guys pocketed 500
00:37:51
large look we we can come to the summit
00:37:54
and you know Palmer Style just like
00:37:57
long list of things I've said
00:38:01
about yes absolutely shout out to my guy
00:38:04
Palmer lucky but what do you think
00:38:05
freeberg for serious let's get back on
00:38:06
track here okay so here's what I here's
00:38:08
what I think if you take defense down to
00:38:10
First principles there was an excellent
00:38:12
tweet that we were all texting about
00:38:14
yesterday it made the
00:38:16
observation that Trump's negotiations
00:38:18
with Russia and China where there's all
00:38:21
of this Heming and hawing about those
00:38:23
negotiations being complying with the
00:38:26
wants and needs of dictators
00:38:28
may actually be a shift in strategy on
00:38:31
the global relationship the United
00:38:33
States has with other Global powers in
00:38:37
particular a shift from the objective
00:38:39
being about us Primacy and the us being
00:38:43
kind of the sole great power on Earth to
00:38:45
recognizing that that's no longer the
00:38:47
case and that in a multi-polar world we
00:38:50
no longer need to invest in Wars need to
00:38:53
invest in conflicts need to invest in
00:38:56
defense with supposed allies to try and
00:38:59
build up our strength across the globe
00:39:02
and I'm not saying that this is
00:39:03
necessarily the right strategy but it
00:39:04
was an observation that maybe the
00:39:06
Strategic imperative is now to have kind
00:39:08
of a a multi-polar stance in the world
00:39:10
rather than a stance of Primacy and in
00:39:12
that framing you then ask the question
00:39:15
okay at make that the case now if we do
00:39:18
agree that we are all going to settle
00:39:19
into a new world where China Russia the
00:39:21
United States are not necessarily equal
00:39:24
Powers but shared Powers across the
00:39:26
globe in that
00:39:28
context do we need to have as much of an
00:39:31
investment in global defense do we need
00:39:33
to continue to pour dollars into
00:39:35
building up arsenals and military bases
00:39:38
and troops and stations and positions
00:39:40
All Around the World perhaps not perhaps
00:39:41
the world gets divided peacefully and we
00:39:44
open up global trade relationships and
00:39:46
everyone benefits economically from the
00:39:48
advances in technology and improvements
00:39:49
in productivity and the world order is
00:39:51
peaceful but multi-polar maybe that's
00:39:54
the new era that we're entering and in
00:39:56
that context you need as much of a
00:39:58
defense and separately to chamat point
00:40:00
there's different technology that's now
00:40:02
in play we've seen it in the Ukraine
00:40:03
Russia context that a $10,000 drone can
00:40:06
destroy A10 million piece of equipment
00:40:08
and China now has drone factories that
00:40:10
can output millions of drones each month
00:40:12
so if China develops this new type of
00:40:14
Arsenal with millions of autonomous
00:40:16
flying systems that can go and attack
00:40:19
troops and attack expensive pieces of
00:40:21
equipment do we really need aircraft
00:40:23
carriers do we really need tanks and I
00:40:25
think that's the whole hegf Le um Trump
00:40:28
Le conversation that's underway in
00:40:30
defense right now number one multi-polar
00:40:32
number two therefore we don't need as
00:40:34
much defense spending number three maybe
00:40:36
the defense spending that we do do
00:40:38
should account for the new technology on
00:40:40
in play in the battlefield and that
00:40:42
really changes the character of how the
00:40:44
defense department is structured and how
00:40:46
funding is structured so that's really I
00:40:47
think the way to look at it versus hey
00:40:49
let's just cut defense spending for
00:40:50
cutting sake um and that might be what's
00:40:52
going on right now a holistic view of it
00:40:54
Patrick any thoughts on uh what we're
00:40:56
seeing in fense Tech and uh saving money
00:41:00
through Doge well obviously what um what
00:41:03
you know Andel and others are doing is
00:41:05
is pretty amazing um but you know we're
00:41:07
we're obviously not defense experts uh
00:41:09
but sort of just bring the credit card
00:41:10
merchant uh perspective uh to Bear here
00:41:13
uh you know we naturally just go and
00:41:14
look at the the time series um and the
00:41:17
sort of the data around it and I guess
00:41:18
I'm struck by again maybe I'm getting
00:41:20
some of the details wrong here I'm this
00:41:22
is outside of our Zone but as far as I
00:41:25
can tell the cuts proposed over the next
00:41:28
couple years of the for the defense
00:41:29
department are of approximately the same
00:41:32
magnitude as the reduction in the
00:41:34
defense budget that occurred between
00:41:36
2010 and today and so it's not like this
00:41:39
is some unprecedented transformation in
00:41:42
DOD budget uh we we we've done this and
00:41:45
then secondly you know as far as I can
00:41:48
tell one of the most ecumenical
00:41:51
uniformly shared bipartisan issues in
00:41:54
Washington is the in efficiency and the
00:41:58
pricacy of Defense procurement you jimes
00:42:00
Fallows writing a book about this in the
00:42:02
late 80s you had you know Augustine's
00:42:04
laws and their whole book about this
00:42:06
just everyone seems to you know uh
00:42:08
fervently believe um that defense
00:42:10
procurement is monstrously inefficient
00:42:12
now you know it's possible to make
00:42:15
budgetary changes without fixing that
00:42:17
but obviously the prospect of meaningful
00:42:19
Improvement there uh seems uh seems like
00:42:22
it would be you know really
00:42:23
beneficial and if I can just give a
00:42:25
quick book recommendation this book Boyd
00:42:28
by Robert korm about John Boyd the Air
00:42:29
Force Colonel who you know was part of
00:42:31
the reformist uh movement I feel like
00:42:33
everyone in Silicon Valley has that book
00:42:34
on their shelf and no one's actually
00:42:36
read it but it is a exactly it it is
00:42:40
kind of referencing sprinkling some UDA
00:42:41
Loops into your remarks uh always helps
00:42:44
exactly yeah yeah yeah um sounds smart
00:42:46
but uh that is a great book and it's a
00:42:48
book about Air Force procurement
00:42:50
essentially where he had his you know
00:42:53
basically the story is that the Air
00:42:54
Force generals of the time wanted planes
00:42:56
that were bad and he had a theory about
00:42:58
better fighter jets uh and he had his
00:42:59
fingerprints all over the F16 and the
00:43:01
A10 and the F-15 and uh various aircraft
00:43:05
and it was a real battle to get the Air
00:43:09
Force to produce better aircraft and
00:43:11
they really you know the generals really
00:43:12
wanted these bad aircraft that they had
00:43:14
planned and so that's a fun read at this
00:43:16
moment in time when it feels like we
00:43:18
have this similar transition from man to
00:43:21
name of the book again I know there's
00:43:22
many books about it's called Boyd by
00:43:24
Robert corm and it's a it's a really
00:43:26
engaging read it's also just very well
00:43:28
written it's this kind of narrative
00:43:29
non-fiction style yeah this there it is
00:43:31
okay everybody another book selection
00:43:33
from the all-in book club brought to you
00:43:36
by stripe use the code Allin to get a
00:43:40
year free of got the stripe press books
00:43:43
absolutely oh you do actually have a
00:43:44
series of cool books yeah we'll uh we'll
00:43:46
plug those towards the end uh all right
00:43:49
shath you added a crypto update crypto
00:43:51
corner is back we had an exciting week
00:43:55
of innovation in the crypto space last
00:43:57
week Argentine president mle who is a
00:44:01
hero to a lot of people in uh on the
00:44:04
right or for government efficiency
00:44:07
promoted a meme coin it was called Libra
00:44:09
dollar sign Libra and uh he originally
00:44:12
tweeted this private project will be
00:44:15
dedicated to encouraging the growth of
00:44:18
the
00:44:19
Argentine economy uh with a link to
00:44:22
Libra for his citizens to go buy it and
00:44:24
buy it they did but he deleted that
00:44:27
tweet when this whole thing came apart
00:44:28
and said I was not aware of the details
00:44:30
of the project and after having become
00:44:32
aware of it I decided to not continue
00:44:35
spreading it the market cap ripped 4
00:44:37
billion it crashed 95% as these meme
00:44:40
coins always
00:44:41
do 74,000 Traders
00:44:45
lost almost 300 million 24 wallets had
00:44:49
losses over a million and mle has been
00:44:51
sued 100 plus times already and this
00:44:55
just happened last week he's being
00:44:57
investigated by his own government now
00:44:59
and uh there is an impeachment uh
00:45:02
attempt underway by the opposition mle's
00:45:05
team told CNN that his endorsement of
00:45:07
the coin was a mistake really oh wow
00:45:10
going on a limb there according to
00:45:12
insiders Malay never actually owned any
00:45:13
Libra and was not associated with the
00:45:15
coin I think family members maybe put
00:45:17
him up to it the details of why he
00:45:21
promoted it remain a little bit unclear
00:45:23
there's a lot of speculation jamat your
00:45:25
thoughts it's kind of crazy I mean he
00:45:28
was on such a positive upswing of
00:45:30
momentum it doesn't make much sense why
00:45:32
he got embroiled in all of this the the
00:45:35
problem with this though is I think that
00:45:36
the cover up is always worse than the
00:45:38
crime itself so the first message was
00:45:41
you know very Clinton esque like I did
00:45:43
not have sexual relations with that
00:45:45
woman he was like I did not endorse it I
00:45:49
just shared it was his justification for
00:45:52
how he how he um could rationalize what
00:45:57
he did the kid that's behind this thing
00:46:01
Hayden Davis I think is his name he was
00:46:03
on coffeezilla was an incredible one
00:46:06
hour did you see that the coffee Zilla
00:46:08
intervie well I saw I saw some of the
00:46:09
clips on X and it was pretty Brazen
00:46:11
because he he essentially said that he
00:46:13
had Javier Malay in his pocket and then
00:46:16
there were text messages that use some
00:46:19
pretty colorful language to basically
00:46:21
say the same thing then on top of that
00:46:23
there were some text messages that
00:46:24
seemed to implicate malle's sister as
00:46:27
having got some of the money from all of
00:46:29
this I don't know the whole thing just
00:46:30
makes absolutely no sense that he was
00:46:32
doing so much good and now he's goingon
00:46:35
to go through this whole cycle of trying
00:46:36
to wash his hands of this whole thing
00:46:38
it's a complete waste of time and effort
00:46:41
I don't know why he did this and there
00:46:42
was another like interesting little
00:46:44
tidbit uh fredberg uh friend of the Pod
00:46:48
David pornoy supposedly he's been
00:46:51
getting in on this and he's a gambler
00:46:52
and he loves gambling and he looks at as
00:46:54
gambling obviously he had put reportedly
00:46:56
millions of dollars into this and this
00:46:58
guy we're talking about gave him his
00:47:00
money back this guy also has something
00:47:03
like a hundred million sitting in a bank
00:47:05
account anywhere what's your take on all
00:47:06
these meme coins
00:47:07
Freer I don't like them I don't think
00:47:11
that they're okay like good I don't
00:47:13
think they're productive all right I
00:47:15
think that a bunch of people are going
00:47:16
to put money in and lose money and a few
00:47:19
people are going to make a lot of money
00:47:21
and you know but at the end of the day
00:47:22
it's no different than the people that
00:47:24
sell trading cards or the people that
00:47:26
create and sell Collectibles and get
00:47:28
paid for them and this is just
00:47:30
effectively a digital Collectibles
00:47:31
business unfortunately I think it's like
00:47:33
Amplified by like a thousand X because
00:47:36
Collectibles businesses have friction
00:47:38
and they're manual and you got to ship
00:47:39
them and this creates um a bit more of a
00:47:42
digital frenzy where you see the social
00:47:43
feedback loop happen really quickly in
00:47:45
real time and that drives these things
00:47:47
to a high value which means people have
00:47:49
the ability to lose a lot more than the
00:47:50
otherwise qu but look I mean these are
00:47:52
not helping the financial system get
00:47:54
rebuilt as we talked about earlier
00:47:55
they're not uh creating productive value
00:47:58
they entertainment mechanisms just like
00:47:59
any other kind of gambling system might
00:48:02
be and you know people can choose to do
00:48:04
that if they want but personally I'm not
00:48:06
into it I just think it's stupid but
00:48:07
whatever Patrick their own yeah do you
00:48:10
think these are like Collectibles or do
00:48:13
you think they are perceived by the
00:48:17
people buying them more like Securities
00:48:19
and more like Bitcoin they do uh to
00:48:21
steal me on the other side of the
00:48:22
argument uh they do trade with a ticker
00:48:24
symbol they are traded uh on major
00:48:28
platforms like coinbase and Robin Hood
00:48:32
and people share charts about them and
00:48:35
so where do you stand on it you're in
00:48:37
the finance business mem coin's good
00:48:39
mcoins
00:48:40
bad I'm basically with Dave I mean I
00:48:46
well they seem to me to be maybe
00:48:49
analogous to to gambling um which you
00:48:53
know I don't know that we want to ban
00:48:55
gambling uh like if you're
00:48:57
able to do it responsibly and you
00:48:59
understand what you're getting into and
00:49:01
so forth like I guess that's fine but as
00:49:04
you
00:49:06
say judging by the tweets that I see
00:49:09
there are a lot of ticker symbols and
00:49:12
charts and prognostications about future
00:49:16
price trajectories and so forth that
00:49:18
lead me to think that people are placing
00:49:19
somewhat more weight on the asset and
00:49:22
security value of these uh as compared
00:49:24
to the I don't know some numinous
00:49:26
intrinsic
00:49:27
aesthetic value
00:49:30
so John maybe two things could be true
00:49:33
here people are gambling and they are
00:49:35
being presented as financial instruments
00:49:38
and they're trying to trick the suckers
00:49:39
at the table the suckers in this case
00:49:41
being the people who voted for Malay to
00:49:43
chat's point this is the unbelievable
00:49:45
self home of the of the decade yeah look
00:49:49
I don't like meme coins I think they're
00:49:51
bad and I think they're part of like
00:49:54
Patrick said a broader swaye of things
00:49:56
that we need to figure out Society where
00:49:59
the legalization of sports betting and
00:50:02
combined with highly targeted
00:50:04
advertising I don't know if you guys
00:50:05
have seen the stats on you know whales
00:50:07
in sports betting losing very large
00:50:09
amounts of money and it's just these
00:50:11
heartbreaking tales and there's a very
00:50:13
large number of them of people kind of
00:50:16
losing much more than they expected and
00:50:19
I don't know we have to to reckon with
00:50:22
these societal questions I don't think
00:50:24
the super easy answers they come along
00:50:25
from time to time learned recently that
00:50:28
um state lotteries are a relatively
00:50:29
recent phenomenon like I think it was
00:50:31
one state started doing it in the 1970s
00:50:33
and then a bunch of the other states
00:50:34
followed suit but it's kind of odd when
00:50:36
you step back that like I pass a
00:50:38
billboard on 101 for you know the state
00:50:41
of California trying to you know get me
00:50:43
to buy Lottery a negative e EV bet yeah
00:50:47
just like but but that's become very
00:50:48
normalized and so I think it's a bucket
00:50:50
of hard questions here around you know
00:50:52
beam coins Sports gambling whatever I
00:50:55
don't know what you do but there's a lot
00:50:57
of meme coins are not the only place you
00:51:00
find these very heartbreaking stories
00:51:02
this is the this is the first time where
00:51:03
they've actually talked about at least
00:51:05
where I saw the details of how this
00:51:07
stuff happens because he laid it out and
00:51:09
there's these people called snipers that
00:51:11
go and like pump up the bids right as
00:51:14
soon as the coin gets launched and then
00:51:16
they're able to Fe so there's like this
00:51:19
entire mechanism Soo shady I was gonna
00:51:22
say some there where I I feel like the
00:51:24
specific thing within beam coins
00:51:26
probably most pernicious is like the
00:51:28
rugging
00:51:29
dynamic and if you could have meme coin
00:51:32
girl but without the without the pump
00:51:36
and rug if it was like I don't know just
00:51:38
some mimetic tracker of some sentiment
00:51:40
or something like maybe that' be okay
00:51:42
but the the the like the particular way
00:51:44
in which they seem to be you know
00:51:46
employed is like yeah some some sort of
00:51:48
discontinuous run up and then well the
00:51:49
rug what do you think J I agree with you
00:51:52
chath uh Malle had the greatest PR run
00:51:55
of all time I think
00:51:57
I mean he became an inspiration to all
00:51:59
of us here in America who were concerned
00:52:02
about the deficit and outof control
00:52:04
spending and ridiculous departments we
00:52:07
heard Jamie Diamond talking about
00:52:08
ridiculous committees and all this
00:52:10
nonsense I don't know if you guys
00:52:11
remember but remember he was like
00:52:12
minister of culture AA and minister of
00:52:15
genda AA this was the precursor to of
00:52:19
course Doge where now we're like USA
00:52:22
deleted Department of Education deleted
00:52:25
you know defense department Min - 8% and
00:52:28
you know what I really find terrible
00:52:31
about this is that what it means for
00:52:33
leadership what mle did was he rug
00:52:37
pulled the people who put him in office
00:52:39
the people who voted for Malay are the
00:52:41
ones who got hurt here and when you
00:52:44
think about leadership at its core it
00:52:46
really is about putting the needs of
00:52:48
your constituents ahead of your own
00:52:50
interest the needs of your investors in
00:52:52
the case of you know if you were running
00:52:54
Stripe Right you got to think about all
00:52:56
these shareholders leadership you know
00:52:58
at its core is I think setting the
00:53:00
example right you set the St the
00:53:02
standard the moral the ethical The Vibes
00:53:05
the culture you set that standard he had
00:53:07
set such a great standard that we all
00:53:09
loved and you know the appearance of
00:53:13
impropriety is impropriety in my mind
00:53:16
that's the leadership standard that
00:53:17
should be here so even being near this
00:53:19
your sister launching it your brother
00:53:21
launching whatever it is he then went on
00:53:23
to taunt this is where I really you know
00:53:25
like people make mistakes but and this
00:53:27
is a stupid one to make but the taunting
00:53:30
of his own followers you know I'm out on
00:53:32
Malay right now this is what he said the
00:53:34
reality is if you go to the casino and
00:53:36
lose money I mean what is the claim if
00:53:38
you knew that it had these
00:53:41
characteristics this is another failure
00:53:43
of leadership leaders own their mistakes
00:53:45
they don't attack the victims you take
00:53:46
ownership of it and the way you should
00:53:49
judge people I think is what they do
00:53:51
when they're given a lot of power and
00:53:53
what they do when they make mistakes mle
00:53:55
is a failure on all of those those
00:53:56
fronts it's absolutely
00:53:59
abhorent that's it thanks for coming to
00:54:01
my TED
00:54:03
Talk No I'm just I'm on fire about it I
00:54:05
just think it's like really terrible do
00:54:07
you need help getting off your moral
00:54:08
grandstand now I do
00:54:11
actually yeah I'm over I'm sorry I
00:54:13
actually care about morals ethics and
00:54:15
Leadership I think that there's a
00:54:17
standard set by these people that's what
00:54:18
I that's what I think about when I think
00:54:19
about you yes of course thank you uh all
00:54:23
right with friends like these cson
00:54:24
brothers can you imagine imag please say
00:54:27
okay I'm so annoyed can you please say
00:54:28
their
00:54:29
name pronounce the goddamn
00:54:32
eye I'm pronouncing the Irish okay we we
00:54:35
speed things up a little bit we we put
00:54:36
them together it's a little bit
00:54:38
different you wouldn't know this from
00:54:39
being from Sri Lanka a great
00:54:41
country you guys wouldn't know why
00:54:43
anyone watches this show would you yeah
00:54:46
I don't
00:54:47
knowbody says no context for this why
00:54:50
you make every show a train wreck and we
00:54:52
have to get it out of the the banter is
00:54:54
why why people come people listen you
00:54:56
know so many TV shows are about it's
00:54:58
nice to have friends I mean you look at
00:55:00
friends or How I Met Your Mother my wife
00:55:01
and I are rewatching The West Wing right
00:55:03
now and it's basically a show about you
00:55:05
know yeah but it's just like all buddies
00:55:07
and loyal to each other and everything
00:55:09
and I think the underlying idea behind
00:55:11
lots of TV shows is it's nice to have
00:55:13
friends and I think that's the the
00:55:15
success the all in sng by the way is an
00:55:17
Inc is an incred which season are you on
00:55:19
it's an incredible show we're up to
00:55:21
season four now God I gotta get five or
00:55:24
seven never got in on the west of course
00:55:26
sorin left after season 4 and so many
00:55:29
people said of the whole thing about the
00:55:32
great debate that America needs to have
00:55:33
I think is still like the missing aspect
00:55:36
of modern politics is the great debate
00:55:39
yeah well the great debate is like let's
00:55:40
talk about the topic that's at hand and
00:55:42
talk about it on the merits of what's
00:55:44
right for the country as opposed to
00:55:46
everything being about attacking because
00:55:47
the other side brought the idea forward
00:55:50
and now we have to attack the other side
00:55:52
and frame the idea as being beneficial
00:55:54
to them and hurtful to us nothing
00:55:56
actually gets resolved because we don't
00:55:58
end up having objectivity around these
00:56:00
conversations around some of the major
00:56:02
issues that the country faces many of
00:56:03
which by the way both sides have valid
00:56:05
points of view and if we can kind of
00:56:07
have the great debate if we can have
00:56:08
these conversations like Doge right like
00:56:11
abortion like you know the rights of
00:56:13
States like spending like there are all
00:56:16
these things that we should be talking
00:56:17
about rather than use that moment as a
00:56:19
way to attack the other side politically
00:56:21
so I can make sure I've got points and
00:56:23
Kudos leading into the next election
00:56:25
cycle it's just awful anyway I missed
00:56:27
that about the West wi it feels like a
00:56:28
purest like just a beautiful like way of
00:56:30
thinking about I wonder what it would be
00:56:32
like to watch the westwing and then
00:56:34
House of Cards back to back that's
00:56:36
something I should no but it's like
00:56:38
really a ju to position those two
00:56:39
different shows yeah but they've isn't
00:56:41
The West Wing kind of the opposite of
00:56:43
what you just said you want the all in
00:56:44
to represent because I see I see the
00:56:47
westwing as being sort of fully immersed
00:56:50
in and representing you know one sort of
00:56:52
particular worldview there was you know
00:56:55
there was inms since we look back on the
00:56:57
990s at the Clinton years or something
00:56:58
as you know this period of great Harmony
00:57:00
in the country and you know that Harmony
00:57:01
might have been great and the economy
00:57:02
was doing well and you know all the
00:57:03
things um but it wasn't exactly a period
00:57:06
i whatever I wasn't here in the 90s but
00:57:08
you know from afar it did not feel to me
00:57:10
when I was eight or whatever as a period
00:57:12
of tremendous ideological uh debate and
00:57:15
fervor and schisms and all the rest
00:57:18
during the 90s during the Clinton era
00:57:20
you're think yeah yeah and I think I
00:57:22
mean maybe I'm wrong but I think of the
00:57:23
west wing as you know a kind of
00:57:25
recapitulation
00:57:27
maybe they were I mean maybe they were
00:57:28
the compromising party because I mean
00:57:31
tell me another modern Democrat
00:57:34
president that's had any point of view
00:57:35
on balancing the budget and creating a
00:57:37
surplus which was aligned with the
00:57:39
Reagan point of view at the time and he
00:57:41
kind of you know again as Jal says he
00:57:43
was a Centrist and he brought brought
00:57:45
the the parties closer together rather
00:57:46
than further apart with how they I agree
00:57:49
with Patrick the thing that makes the
00:57:51
westwing a great show is that it's about
00:57:53
The Insider nature of the White House
00:57:55
and the West Wing where you see these
00:57:57
characters like Toby who would never be
00:58:00
a star in any other show under any other
00:58:03
circumstance on any network ever and
00:58:07
instead he's one of these Central quasi
00:58:10
good quasi nefarious bully kind of you
00:58:13
know he was like a the precursor to the
00:58:15
Rah Emanuel archetype in the Obama White
00:58:17
House I think I also find it funny where
00:58:20
you know the way uh Dominic Cummings has
00:58:22
talked about just his experience of life
00:58:24
in government was that it's so
00:58:26
distracting trying to get anything done
00:58:28
because you know you have some plan you
00:58:29
get up in the morning and you're going
00:58:30
to go do something that matters for the
00:58:32
country and then you're just instantly
00:58:34
by 8 a.m. you know sideswiped by some
00:58:36
kind of silly controversy of the day
00:58:38
that's basically many of the episodes of
00:58:40
the westwing where they like have some
00:58:42
actual important thing that they want to
00:58:44
get done and then they just get whed by
00:58:46
a silly controversy yeah seems to me
00:58:48
like you're also the product of the
00:58:52
technological innovation that occurred
00:58:54
during your presidency and during your
00:58:56
term and if you think about Clinton he
00:58:58
got to ride the internet and this
00:59:00
massive economic boom and you look at
00:59:03
you know Reagan the pce boom I mean
00:59:06
sometimes the timing really matters I
00:59:08
think um though I think you know and
00:59:11
again I'm not any Grand expert on the on
00:59:13
the Clinton years but I think you know
00:59:14
it is interesting where you know one of
00:59:16
the first acts of the Clinton presidency
00:59:18
was the was the deficit reduction act um
00:59:21
you know Dave to your point you know
00:59:22
when's the last time that a you know a
00:59:23
Democratic president you really really
00:59:25
cared about the deficit and I think
00:59:26
federal spending fell by Five Points of
00:59:30
GDP over the course of the of the
00:59:32
Clinton presidency which is really not a
00:59:33
small amount you know so obviously there
00:59:35
were some kind of structural Tailwinds
00:59:37
from you know technology and the
00:59:39
internet and all the yeah a bunch of
00:59:40
that was defense but but like
00:59:42
nonetheless so he did the in the last
00:59:45
two administrations and you look at
00:59:47
California there were massive Windows of
00:59:50
surplus and there were massive Windows
00:59:52
of a surging stock market over the last
00:59:54
eight years and we plundered and we
00:59:57
wasted them by adding 16 trillion to the
01:00:00
debt during a good time like what's
01:00:03
going to happen during a bad time just
01:00:05
absolutely brutal let's move on where do
01:00:08
we want to go here we got grock 3 we got
01:00:11
the China private sector we got a
01:00:12
victory lab for freeberg I want to ask
01:00:14
you guys questions about Arc Institute
01:00:16
and the Evo model we should do that
01:00:18
let's do the arc Institute freedberg why
01:00:21
don't you ask the question Patrick runs
01:00:23
the arc Institute right okay yes I'm one
01:00:25
of the co-founder and then there were
01:00:27
scien and you guys are fund of it or
01:00:29
yeah maybe you guys give us the a lot of
01:00:31
money into this yeah yeah so the arute
01:00:34
is a nonprofit it does basic biology
01:00:36
research it's in paloalto Nexus Stanford
01:00:38
it's about 230 people today and uh yeah
01:00:42
John and I are among the funders of us
01:00:43
but there's a there's a bunch of other
01:00:44
very generous donors can you explain
01:00:47
idea of curiosity driven research that's
01:00:49
on the website yeah there's kind of two
01:00:50
things behind this so the first is
01:00:52
scienti the vast majority of biology
01:00:54
scientists today receive NIH grants
01:00:57
doing basic research and the NIH grants
01:00:59
are one just hard to get and annoy to
01:01:01
get you know assigned TOS spend 40% of
01:01:03
their time working on Grant overhead and
01:01:04
so forth but worse like even more
01:01:06
perniciously the grants are very
01:01:08
restrictive in terms of the kind of
01:01:09
science they can do and so we ran a
01:01:11
survey of scientists back a couple years
01:01:13
ago of top scientists and four out of
01:01:16
five like 79% of them told us that if
01:01:19
they could just spend money however they
01:01:21
wanted if they weren't kind of limited
01:01:22
by you know what they're prescribed by
01:01:24
these nhh grants for told us they would
01:01:26
change the research agenda a lot um and
01:01:29
so I think the analogy here is imagine
01:01:30
if there was only one VC firm and it was
01:01:33
run by the government how would that VC
01:01:35
firm had strong opinions on what kind of
01:01:37
companies people should build exactly
01:01:39
and you know literally the the grand
01:01:41
panels at the NIH are um they're
01:01:43
consensus based like explicitly they've
01:01:46
consensus based scoring mechanisms and
01:01:48
they you know penalize you if you're
01:01:49
doing work outside of your field and so
01:01:50
forth so I we we kind of we go to all
01:01:53
this work to train these amazing
01:01:55
scientists and then we sort of don't let
01:01:56
them pursue their best ideas that's kind
01:01:57
of problem one and Arc The Arc
01:02:00
investigators you know they're fun to do
01:02:02
whatever they want curiosity driven
01:02:03
research and then the second thing
01:02:05
behind Arc is is this idea that you can
01:02:07
kind of divide diseases into three
01:02:08
categories you know you have infectious
01:02:10
diseases and we we you know broadly
01:02:12
speaking know how to you know generate
01:02:14
cures for and treatments for infectious
01:02:16
diseases we've monogenic diseases like
01:02:18
one genetic mutation or something and we
01:02:20
don't know how to cure those in most
01:02:22
cases but we can we can you screen for
01:02:24
them and so on um and then we you know
01:02:26
what the biologists call complex
01:02:27
diseases where there's some kind of Gene
01:02:29
environment interaction that's most
01:02:30
cancers most autoimmune diseases most
01:02:32
neurodegenerative diseases and so forth
01:02:34
Alzheimer's things like that exactly and
01:02:37
we've never cured a complex disease and
01:02:39
you know many of these diseases are very
01:02:41
tragic precisely because you know we not
01:02:43
only have we not cured them we don't
01:02:44
even have treatments as you know as John
01:02:46
says uh in in the case of Alzheimer's
01:02:48
for example and so you know the question
01:02:51
is can we do something about this and
01:02:52
you know what would a research agenda
01:02:54
and program that you know can that can
01:02:56
help you know shine some light on these
01:02:58
complex diseases look like and our
01:03:00
hypothesis you know we'll see we'll see
01:03:02
uh how much it's born out but our
01:03:03
hypothesis is that we've gotten a couple
01:03:05
of new technologies over the last couple
01:03:08
of years single cell sequencing we can
01:03:10
sequence the the DNA or the RNA just
01:03:12
like in one cell uh We've you know fancy
01:03:15
new functional genomics and crisper
01:03:16
Technologies uh so you can make these
01:03:18
you know fine edits and perturbations
01:03:20
again even just in a single cell and
01:03:21
then obviously you have Transformers and
01:03:23
Ai and ML and all this stuff and this is
01:03:25
kind of a new
01:03:26
read think write Loop in biology that
01:03:30
just didn't exist a decade ago and again
01:03:32
the question is is this powerful enough
01:03:34
now to you know solve some of these
01:03:36
previously intractable uh diseases and
01:03:38
so yesterday Arc released this new uh
01:03:42
Foundation model for biology it's the
01:03:44
largest biology ml model ever it's it's
01:03:48
it's actually I think the largest open
01:03:50
source AI model ever this is evo2 you're
01:03:52
talking about EO the number two Evo two
01:03:56
and so it's not just open weights like
01:03:58
uh like you know the Deep seek model or
01:04:00
or llama or something it's actually it's
01:04:02
open source and the training code is uh
01:04:04
is public and you know you can people
01:04:07
can go read the blog post of the paper
01:04:08
whatever the thing I find amazing about
01:04:10
Evo and that just really surprised me is
01:04:12
so it's trained on nine trillion base
01:04:15
pair Gene tokens so you know uh chat gbt
01:04:18
llms are normally trained on on you know
01:04:21
the on on human language this is a a
01:04:23
language model but it's trained on on
01:04:25
DNA the language of life and there's
01:04:28
only one human genome in the training
01:04:30
set it's mostly other
01:04:33
species and even though it's only seen
01:04:35
one human genome it's state-of-the-art
01:04:38
at predicting the pathogenicity of human
01:04:42
genome mutations and so you know a
01:04:44
famous mutation is the brocha mutation
01:04:46
for breast cancer like it's
01:04:48
state-of-the-art at predicting the the
01:04:50
pathogenicity the harmfulness of uh of
01:04:52
brocka mutations again it only desite
01:04:54
never having seen one humans it's it's
01:04:57
only seen one human genome and that
01:04:58
human you know did not have these
01:04:59
pathogenic mutations and so it's it's
01:05:02
kind of learning something deep across
01:05:03
the tree of life and I know I find that
01:05:05
pretty cool and sorry is there a
01:05:07
phenotypic data set that's used in
01:05:09
training so I think like you know
01:05:12
typically right and so when you're
01:05:14
building
01:05:15
models in typical like genotype by
01:05:19
phenotype models you're trying to look
01:05:20
at the phenotype the physical
01:05:21
characteristics of the organism what can
01:05:24
it do what is look like what are the
01:05:26
features and then you look at the genome
01:05:29
and so that tells you hey these are the
01:05:30
specific genes or alterations or
01:05:32
mutations that drove this particular
01:05:35
phenotype is kind of what the model
01:05:36
tries to learn over time with the
01:05:37
objective being hey can I ask it to
01:05:39
define a genotype or a genome based on a
01:05:42
phenotype based on a physical set of
01:05:44
characteristics I'm looking for vice
01:05:45
versa maybe you can just help us
01:05:47
understand what what is it trained on
01:05:49
and how you know how did that kind of
01:05:51
you know prediction in braa you know how
01:05:53
how is that possible great question so
01:05:56
it's totally unsupervised that is to say
01:05:58
You Know You're just showing us lots of
01:06:00
genomes uh and any kind of latent
01:06:02
structure that it learns is just based
01:06:03
on trying to figure out how to kind of
01:06:05
organize uh that knowledge but we're not
01:06:07
showing it any labeled data or
01:06:08
phenotypic you know kind of outcome data
01:06:11
or you know what have you and so then
01:06:12
you're able to you can give it a genetic
01:06:15
sequence and ask relative to its
01:06:18
understanding of genetic Universe how
01:06:20
lightly is this particular sequence and
01:06:22
so then you can do things like uh like
01:06:24
you know predict anomalousness or
01:06:26
pathogenicity or whatever right you can
01:06:28
also then kind of using the embeddings
01:06:32
of the upper layers we need to get two
01:06:33
technically here but like you you can
01:06:35
train another model on top of the model
01:06:38
um and uh and even if you show it maybe
01:06:40
only a couple of examples it learns very
01:06:42
quickly okay kind of here's you know
01:06:44
here's how the weights of evo2
01:06:47
correspond to this particular task and
01:06:49
those uh those sort of models trained on
01:06:51
top uh turn out to be you know really
01:06:54
accurate you guys open source the base
01:06:56
model or you open source the fine-tuned
01:06:58
or both we open source the base model
01:07:01
but there's no kind of proprietary
01:07:03
reason that we didn't open source the
01:07:04
fine tunes like it's really easy to
01:07:05
produce them and yeah if anyone wanted
01:07:08
one of them we we we'd happily share it
01:07:09
where does it stand in the spectrum of
01:07:13
different tools that folks would would
01:07:15
use to solve these Life Sciences
01:07:16
problems there's cell models that are
01:07:18
being developed by some then there's
01:07:20
these protein models where does this fit
01:07:23
this kind of landscape of of um of
01:07:26
foundation models in biology it's
01:07:28
obviously very new so it's a um it's a
01:07:30
bit of an open question sort of how
01:07:31
exactly people are going to find you
01:07:33
know ways to to to use it and and
01:07:35
applications for it part of I think is
01:07:36
cool is
01:07:38
that proteins and RNA and I mean
01:07:42
phenotypic expression and everything you
01:07:44
know all these things sit on top of the
01:07:45
DNA like in some sense the DNA encodes
01:07:47
everything because you know the the
01:07:49
whole organism comes from the DNA and so
01:07:51
I guess the question would be and you
01:07:54
know we don't really know yet is DNA all
01:07:56
you need uh and with EVO One we saw some
01:08:00
you know encouraging uh suggestions that
01:08:03
for example you can build really good
01:08:05
protein structure prediction models out
01:08:07
of a DNA Foundation model even if you
01:08:09
don't train on a lot of you know protein
01:08:10
structure uh data so but I I'd say just
01:08:13
it's a really exciting time and it's
01:08:15
kind of an open question and I don't
01:08:16
know if you analogize evo2 to I don't
01:08:19
know whether it's gpd2 or three or
01:08:21
something but you know I think we're
01:08:23
going to see a similar Cambrian
01:08:24
explosion of of applications over the
01:08:27
next couple years the thing we really
01:08:28
excited about at ARC is is training yeah
01:08:32
cell State models and trying to better
01:08:35
understand you know how cells you know
01:08:36
what what causes them to change States
01:08:39
and so we're thinking a lot about that
01:08:40
but but you know the reason the the
01:08:41
weights are in hugging face and
01:08:42
hopefully we'll be surprised in in what
01:08:44
Patrick do you just expect that over
01:08:46
time as stripe continues to grow you can
01:08:48
just take the ex some of your own excess
01:08:51
capital and other people will do the
01:08:52
same and keep funding Arc and then if
01:08:54
there's something that Arc creates or
01:08:57
innovates on if it can generate some
01:09:00
amount of money it would just kind of
01:09:01
flow back is it meant to be
01:09:02
self-sustaining or is it always just
01:09:04
going to be via patronage from
01:09:06
successful folks that just want to keep
01:09:07
it going John and I are you know we are
01:09:10
ourselves very committed to it and um
01:09:13
and you know we're we're kind of
01:09:14
underwriting it in that regard but well
01:09:18
one we're just lucky where there's a a
01:09:20
growing donor pool of other people
01:09:21
supporting it I think it's just better
01:09:22
for an institution if it's not kind of
01:09:25
be P into the whims of you know one
01:09:27
donor one group of donors or something
01:09:28
so I think that's just a much healthier
01:09:30
uh structure for it I think there's also
01:09:32
a larg group of people who are just
01:09:33
becoming interested in science and
01:09:35
realizing I mean you know Jason was on
01:09:36
his uh his moral Pulpit my Pulpit is
01:09:41
that you know all is not well in basic
01:09:43
research uh in the US today and again
01:09:46
the way to see this is to just talk to
01:09:48
the scientists themselves and they tell
01:09:51
you um how kind of
01:09:52
inhibited they are and you know the the
01:09:55
the kind of problems caused by the
01:09:56
strictures and structures around them
01:09:59
and we don't see Arc as you know the
01:10:01
answer hopefully it can be sort of one
01:10:04
point in the space but then you know
01:10:05
there's other people doing cool stuff
01:10:06
you know Brian Armstrong of course
01:10:07
started ACC companying the longevity
01:10:09
space and Yuri mner and other started
01:10:11
alos and you know this is people this
01:10:14
the Chan
01:10:15
Zuckerberg Institute and so you know
01:10:17
people are trying different things but
01:10:20
no Arc is um you know we're we're very
01:10:22
happy to support it and then if if you
01:10:23
know it's possible that Arc over the
01:10:25
long-term become self- sustaining but
01:10:26
you know that's well that was my next
01:10:28
question is yeah it takes a while to get
01:10:29
things into the clinic so you know we're
01:10:31
not holding out for that tomorrow well I
01:10:33
you know when they uh they have this
01:10:34
technology transfer department at every
01:10:36
major university where when scientists
01:10:39
get grants and they work on some
01:10:41
Innovation it gets monetized and so what
01:10:44
happens here who owns the Innovations
01:10:46
how do you license them because it would
01:10:48
be amazing if it just wasn't based on I
01:10:51
believe you guys have put over a billion
01:10:53
dollars into this that was my
01:10:54
understanding is that true just like you
01:10:56
guys are over a billion dollars into
01:10:57
this effort not quite the numbers yeah
01:10:59
not quite the numbers are public so Arc
01:11:02
spends around 100 million a year oh okay
01:11:05
and it started about uh three years ago
01:11:09
so so hundreds of millions of dollars
01:11:11
this is a really significant thing yeah
01:11:13
and and again I want to emphasize there
01:11:14
there are other donors um so it's not
01:11:17
just us but I mean it's a nonprofit
01:11:21
there there have been spin outs and
01:11:23
there will continue to be and so if one
01:11:24
of those know really if one of those
01:11:26
becomes madna or you know the next OIC
01:11:29
or something then you know that could be
01:11:31
really good for Arc and Arc might have
01:11:32
an endowment and be able to kind of
01:11:34
self- sustain and so forth uh we're
01:11:36
we're there's no Prospect for us to make
01:11:38
money on it in the sense that you know
01:11:40
it's aprit yeah well actually John yeah
01:11:43
just one thing there I was talking to a
01:11:45
friend of mine you could if this thing
01:11:47
actually hits you could flip this
01:11:48
nonprofit for profit I got a guy you
01:11:51
could talk to John go ahead oh strays
01:11:55
on the whole like modeling world we talk
01:11:57
a lot about the idea that you can kind
01:11:59
of use a computer State the phenotype or
01:12:02
the physical characteristics you want in
01:12:04
a biological organism and have the
01:12:06
software resolve the whole genome all
01:12:09
the DNA needed to make that physical
01:12:11
organism real and it can do it from its
01:12:15
prediction ability on what genes what
01:12:18
combinations but we're a couple orders
01:12:21
away from that right I mean I think like
01:12:22
ultimately we we always talk about hey
01:12:24
we want to be to define or have the
01:12:26
software Define the plant that can grow
01:12:28
on the surface of Mars it knows the soil
01:12:31
type of Mars it knows the air you know
01:12:33
it knows that it's carbon dioxide based
01:12:35
it's 10% of the Earth's atmosphere it
01:12:38
this is what the day the daylight
01:12:40
structure looks like it needs to be wind
01:12:41
tolerant and then the software predicts
01:12:44
an organism that might be able to do
01:12:45
that you know and obviously there's a
01:12:47
lot of this predictive work going on in
01:12:48
proteins then the higher order is cells
01:12:51
so single cell organisms microbial
01:12:53
organisms and then ultimately multi
01:12:55
cellular organisms so plants and then
01:12:56
finally animals where you could
01:12:58
basically create organisms from scratch
01:13:00
using software because we have all the
01:13:02
other tools to biologically put these
01:13:03
pieces together today but this is a
01:13:06
great kind of I I view it as a pyramid
01:13:08
there's a ton of phenotypic data that
01:13:09
still needs to be fed in ultimately to
01:13:11
kind of have us all understand protein
01:13:13
protein models and and a lot more to it
01:13:15
but it's a great I think I think that's
01:13:17
right like you can uh this there's a
01:13:19
certain amount you can probably derive
01:13:20
sort of uh you know from first
01:13:22
principles just by looking at the
01:13:23
genomes but I think the really powerful
01:13:24
model model are going to need to do
01:13:26
exactly what you say and to feed in a
01:13:28
lot of ancillary phenotypic and and just
01:13:30
kind of other data how they fa in
01:13:32
different environments and the
01:13:34
sequencing data got ahead of the
01:13:35
phenotyping data because there's so much
01:13:37
sequencing data that's com in so you can
01:13:39
do a beautiful job predicting like
01:13:41
correctness in a genome but and this and
01:13:44
the sequencing data is really nicely
01:13:45
digital whereas you know the phenotypic
01:13:47
stuff it's like well even is the data
01:13:50
yeah totally Dave sorry while we're in
01:13:52
the science corner I have a question for
01:13:53
you Dave which your strawberries you
01:13:54
might know answer to this a bunch of
01:13:57
tree species around the world are under
01:13:59
attack so in Ireland we have this
01:14:01
problem of the Ash dieback Ash is kind
01:14:03
of Ireland's national tree they use it
01:14:04
to make Hurley which is you know the for
01:14:06
the national sport and uh since the
01:14:08
mid-2010s you know especially as the
01:14:10
live plant trade has ramped up we need
01:14:11
to get a a hurl for uh for for for Jason
01:14:14
Jason absolutely I put right here on the
01:14:17
Shelf the American chestnut here yeah no
01:14:20
exactly I was going to reference the
01:14:21
American chestnut as well in the US but
01:14:23
it feels like we have this real problem
01:14:24
and it's so
01:14:25
where so many beautiful trees are under
01:14:27
attack the bar the bark beetle in in
01:14:30
California and you know the the various
01:14:31
conifers that we're losing so we got to
01:14:33
Sol the blackp disee the blackp fungus
01:14:35
and cacao and coffee is being destroyed
01:14:37
TR4 is destroying banana right now Doom
01:14:40
let's go no no like it's a real like is
01:14:43
a real this is a real issue down to the
01:14:45
science corner here so this is um yeah I
01:14:47
mean this is exactly what we aim to
01:14:49
address at ohal so in some cases you can
01:14:52
actually silence a gene that's a
01:14:53
suppressor of immune function of the
01:14:55
organism which can actually improve
01:14:57
disease resistance but how do you do
01:14:59
delivery of that do you like this
01:15:01
Airborne sprays or what's the yeah how
01:15:03
do how do how do you treat the tree yep
01:15:05
so ultimately if you're going to use a a
01:15:08
genomic method you would transform the
01:15:11
genome so you would edit the genome and
01:15:13
you would regenerate a plant or
01:15:15
regenerate a tree and then propagate
01:15:16
that tree okay but then like we we have
01:15:17
to replant all the trees we to replant
01:15:19
the trees we'd have to replant the trees
01:15:21
and ultimately do custom projects can we
01:15:24
do a little thing on Ash in Ireland
01:15:25
absolutely that is some of the work we
01:15:27
do so we announced a few weeks ago a
01:15:29
partnership with University Florida to
01:15:32
use our methods to basically introduce
01:15:34
disease resistance for major fungal
01:15:36
pathogen that's destroying the Florida
01:15:38
strawberry crop and so that's what we
01:15:40
call a trait program at ohol where we
01:15:41
can identify specific genomic trait that
01:15:44
we can go and introduce into that plant
01:15:46
but then you're right you do have to
01:15:47
grow all the plants back and then put
01:15:48
them back in the ground that's the
01:15:50
second best to to Pure Extinction but um
01:15:52
I have in in Ireland I ended up owning
01:15:56
this kind of country house and uh virgin
01:15:59
woodlands where you know Woodlands that
01:16:02
Ireland was used to be fully forested
01:16:04
and then was denuded with the arrival of
01:16:06
Agriculture and there's uh some kind of
01:16:08
ancient Woodlands on it that are from
01:16:09
the original when Ireland was fully kind
01:16:11
of covered in trees and I find the die
01:16:15
off of species very sad and so we got to
01:16:17
get yeah but no it's I'm not like I I'm
01:16:19
I'm very optimistic like we know how to
01:16:21
address these Solutions we know how to
01:16:23
regenerate the trees we can we we can do
01:16:25
this quickly we can resolve these
01:16:26
problems but you are right I think you
01:16:28
should be selling a skew a skew to the
01:16:30
people in Tahoe like you know the Tahoe
01:16:32
Basin has been
01:16:33
so worse than decimated as in decimation
01:16:36
is only one in 10 which is like you know
01:16:37
half the half the trees in in Tahoe have
01:16:39
been hit by by bark Beetle so those are
01:16:42
very interesting ones because insects
01:16:44
you can actually build very specific
01:16:46
defense mechanisms against uh insects
01:16:49
but we generally have to improve genetic
01:16:52
diversity and in doing so you know there
01:16:55
there's a natural resistance because the
01:16:57
evolutionary like like the reason we
01:16:58
have a TR4 problem in banana all the
01:17:01
world's banana that we grow commercially
01:17:03
comes from one original banana clone
01:17:04
called dwarf Cavendish and they took
01:17:07
that one plant they cut clippings of it
01:17:09
put it in the ground grow another plant
01:17:10
cut clippings of that and they kept
01:17:11
multiplying it so all the bananas we eat
01:17:12
and all the bananas that are planted
01:17:14
across tens of millions of Acres
01:17:15
worldwide come from one original clone
01:17:17
and because of that this fungus has been
01:17:19
exceptionally capable of evolving itself
01:17:22
to better eat that banana plant and so
01:17:25
60 cents of every dollar we spend on
01:17:26
bananas today goes towards fungicide
01:17:28
we're spraying these banana trees once
01:17:30
or multiple times a week to kill this
01:17:32
fungus we're consuming that it's super
01:17:34
expensive and if we had genetic
01:17:36
diversity if we had better genetics in
01:17:38
the banana programs around the world
01:17:40
we'd be able to radically matter what
01:17:42
the administration says you think we
01:17:43
need more diversity are you in favor of
01:17:46
Dei freedberg they cornered you
01:17:48
freedberg I got you got to make one
01:17:49
promise to me here it comes you're not
01:17:51
going to start working on Raptors I
01:17:53
don't want to see any of these Raptors
01:17:54
running around uh San Francisco okay
01:17:57
jamaath your thoughts here on um science
01:18:00
corner here it's been a really
01:18:01
enthralling one the Raptors are coming
01:18:03
for you I find it
01:18:07
incredibly inspiring that there's just
01:18:10
so much movement in these foundational
01:18:12
models it's incredible like every day
01:18:14
just seems like there's something new
01:18:16
the biggest problem that I think that
01:18:19
the commercial Community is going to
01:18:21
deal with is how to actually take
01:18:22
advantage of it because you're kind of
01:18:24
head spins because you don't exactly
01:18:25
know where to start the biological
01:18:26
models are are different in that I think
01:18:28
it's a much smaller population of people
01:18:30
that will use it and I think they do
01:18:33
have to figure out how to take these
01:18:34
models and and complement the existing
01:18:37
pipeline they have the pipeline they
01:18:38
have right now I think is pretty brittle
01:18:40
I think we all know that in life
01:18:42
sciences my wife struggles with
01:18:44
this a lot is how to complement a very
01:18:48
traditional Pipeline with this kind of
01:18:50
stuff so I see it firsthand in how she
01:18:53
tries to allocate Capital towards these
01:18:55
problems on the other side I just think
01:18:57
these foundational models are really
01:18:58
incredible and I think that I was
01:19:00
completely wrong
01:19:01
on a couple of my earlier thoughts one
01:19:05
thought that I had for a long time was
01:19:09
it just seemed like all these base
01:19:10
models were ASM toting and so I was not
01:19:13
convinced where all this
01:19:15
capex would go in a productive way like
01:19:18
why are you buying all these Nvidia gpus
01:19:20
and then I think if you looked at
01:19:24
Colossus the elon's Colossus xai built
01:19:29
the largest data center over 100,000
01:19:32
gpus going to 200,000 in 122 days I mean
01:19:36
basically what he
01:19:38
proved was that there are still valuable
01:19:42
gains in
01:19:44
pre-training and so the larger the
01:19:46
cluster the more value that there is now
01:19:48
he also benefits I guess from the
01:19:52
X feed but was really interesting so now
01:19:55
I'm like a little bullish on Nvidia I'm
01:19:57
like oh my God if this is true then all
01:19:58
this capex may be justified you could be
01:20:00
buying a lot of stuff then you look I I
01:20:03
actually also just to maybe Riff on this
01:20:05
grock 3 thing for one second I had three
01:20:08
takeaways my first takeaway was I was
01:20:11
sneakily surprised on the pre-training
01:20:14
upside on having a larger cluster so I
01:20:18
think that that's very Pro Nvidia
01:20:20
actually and and it's actually also just
01:20:22
really good in general for foundational
01:20:24
model so I think like that's like a
01:20:26
really positive thing the second thing
01:20:29
is I don't know if you watched the live
01:20:31
stream but did you guys hear some of the
01:20:34
stuff that these guys had to pull to
01:20:36
pull this thing off one of the most
01:20:38
incredible so the way that Elon narrated
01:20:41
it
01:20:42
was we first had a physical problem so
01:20:45
we just had to search all around the
01:20:46
country for one single location where we
01:20:49
could actually put 100,000 gpus and they
01:20:52
found it which was an old Electrolux
01:20:54
Factory in
01:20:55
Memphis that's kind of
01:20:57
interesting he only had like 15 megawatt
01:21:00
and he had to get a quarter gwatt and so
01:21:02
he had to basically buy every useful
01:21:04
generator that was available but then
01:21:06
they had to liquid cool it and so they
01:21:08
bought onethird of all the portable
01:21:10
liquid cooling capacity in America and
01:21:13
located it on Prem but then they figured
01:21:16
out that there was a power problem so
01:21:17
then they took all these Tesla power
01:21:19
packs and then had to do power smoothing
01:21:21
which had them had to rewrite all of the
01:21:23
Power Pack firm
01:21:25
in all of this you know how we talked
01:21:28
about deep seek being this moment where
01:21:30
we had lost sight in America of uh
01:21:33
Capital being the source of innovation
01:21:36
he proves actually a more generalized
01:21:38
rule that I took away from this which is
01:21:40
you always have to have a constraint so
01:21:42
meaning let's say that there's like
01:21:44
infinite capital in his case and
01:21:46
infinite talent because he can basically
01:21:48
recruit anybody he wants what did he do
01:21:51
instead he created this artificial
01:21:52
constraint of time and so he was just
01:21:55
able to sayou going to get this done in
01:21:57
a moment and Nick I show the the third
01:22:00
graph that the guys at artificial
01:22:01
analysis sent to me I just want to put
01:22:04
it up here because it shows you guys the
01:22:06
quality of grock 3 relative to the
01:22:09
amount of time that they've spent on
01:22:11
this problem is to me what's staggering
01:22:13
so if you just sort of project the rate
01:22:15
of change of this and this is without
01:22:18
judging open AI or anthropic or anything
01:22:21
else those guys have been doing it for
01:22:23
years these guys have been doing it for
01:22:25
a year and they did all of this mcgyver
01:22:30
engineering and were able to pull this
01:22:32
off so that's my second takeaway is that
01:22:36
Innovation needs a constraint sometimes
01:22:38
it's Capital sometimes it's talent and
01:22:42
sometimes it's time and so if you can
01:22:45
basically
01:22:47
be just
01:22:49
completely rigid on one of those
01:22:51
Dimensions you can get a great team to
01:22:53
create something so that was an
01:22:55
interesting takeaway and then the third
01:22:56
is I think what this also speaks to is
01:22:58
the notion of like a cetu right which is
01:23:01
like the Japanese word for like
01:23:03
companies that work together while still
01:23:05
remaining independent conglomerates yeah
01:23:08
lose part it's more interl companies
01:23:10
inter you know Koreans have chals right
01:23:13
Japanese Japanese have cetus but this is
01:23:16
the manifestation of an American ketu
01:23:19
which is Elon is able to get Engineers
01:23:22
from Tesla he's not just buying the
01:23:24
power packs he had them re-engineer the
01:23:26
actual firmware in real time on site and
01:23:29
so there's this this positive ability to
01:23:33
just like organize effort and human
01:23:35
capital like look could we all stand up
01:23:37
at Data Center and go and buy $500
01:23:39
million a power packs from Panasonic
01:23:42
absolutely it would take a few months 18
01:23:45
and then when it looked like we need to
01:23:46
rewrite the firmware it would take
01:23:47
another 18 months to your point Jason so
01:23:49
it's really incredible what what these
01:23:51
guys are able to do together those are
01:23:53
my it was really really inspiring chath
01:23:55
a book I think you might find really fun
01:23:57
is uh it's called Henry Kaiser builder
01:23:59
in the American West but Kaiser is kind
01:24:01
of underappreciated these days he was
01:24:03
the Elon of his time he started as a
01:24:05
road builder of all things he won the
01:24:07
contract to build the Hoover Dam he
01:24:08
built the Hoover Dam he started a
01:24:09
shipyard during World War II uh yeah
01:24:12
exactly this made cars he he he decided
01:24:14
to make cars he decided to make
01:24:15
airplanes stations TVs the the famous
01:24:19
4day Liberty ship uh remember the
01:24:21
propaganda win during World War II of
01:24:23
you know they were able to lay down that
01:24:24
was at the Kaiser shipyards Kaiser
01:24:26
Permanente spun out of them as part of
01:24:29
their
01:24:30
um John I was literally TR was saying
01:24:33
that pulling up my notes from the book
01:24:35
um and uh just he was just a complete
01:24:37
phenam and he just kept finding new
01:24:39
Industries it's like oh building cars
01:24:41
how hard can it be oh building airplanes
01:24:43
how hard can it be yeah I mean that is
01:24:46
the nature entrepreneurship the nature
01:24:49
of Entrepreneurship is doing something
01:24:51
delusional and then just letting you
01:24:53
know most R preneurs just do one
01:24:55
delusional Thing Once and stay that like
01:24:57
again Elon and Henry Kaiser back in the
01:24:59
day it's in the world of atoms very hard
01:25:01
things short timelines and S San
01:25:04
Francisco now kind of at least in the
01:25:06
physical domain stands for a kind of
01:25:08
stasis you know it takes you 10 years to
01:25:10
you know build anything um but when he
01:25:12
had the ship the toilet the ship
01:25:14
building yards here he went from zero to
01:25:17
100,000 people in Richmond in one year
01:25:20
he basically built the city of Richmond
01:25:22
California how do you how do you but
01:25:24
guys okay let's just double how how do
01:25:27
you think these guys pull this off
01:25:30
I personal sacrifice massive personal
01:25:33
sacrifice I understand that Jason but
01:25:35
I'm I'm talking about like tactically
01:25:37
pull this off where you have to be on
01:25:40
site at some point organizing this team
01:25:42
directing this team being able to help
01:25:45
isolate these problems fix them it just
01:25:47
seems impossible to do it once let alone
01:25:49
six I don't understand how they do I
01:25:51
actually have some insight to this just
01:25:52
from knowing Elon this lot of these
01:25:54
things compound a lot of what he learned
01:25:56
in Material Science doing SpaceX and
01:25:59
about making uh the engines and then
01:26:02
working with metal you see in his
01:26:05
production at Tesla and specifically in
01:26:09
the Cyber truck he has learned so much
01:26:12
about factories I don't think there's a
01:26:14
person on the planet who knows more
01:26:15
about factories now having built a
01:26:17
battery Factory a space Factory an
01:26:20
engine Factory and a car factory and now
01:26:22
building Optimus on of that so these
01:26:24
things compound and then a lot of the
01:26:27
engineers will float between the
01:26:28
companies so there are folks who have
01:26:30
worked at SpaceX who then go do a tour
01:26:32
over at Tesla Etc and a number of those
01:26:37
wound up coming into
01:26:39
um you I'm going to read you a few
01:26:41
quotes in this book I'm just going to
01:26:42
see if they remind you of of anyone
01:26:46
Kaiser's managers challenged convention
01:26:48
from the start as Builders they were
01:26:50
expert at coordinating workers and
01:26:52
materials Kaiser was almost contemptuous
01:26:54
of traditional methods his Partners had
01:26:57
long since despaired of getting him to
01:26:59
follow customary
01:27:00
procedures in preparing his bids for
01:27:02
each new job Kaiser would try to
01:27:04
conceive every possible technique that
01:27:06
might justify uh making a bid low enough
01:27:08
to win the chob once the construction
01:27:11
was underway he was forever trying to
01:27:12
come up with ideas that would expedite
01:27:14
the work perhaps more than any other
01:27:16
Builder he believed that the faster a
01:27:18
job gets done the lower the costs can be
01:27:21
that's incredible incredible well and
01:27:23
what happened with
01:27:25
is they had told Elon that it would when
01:27:29
he wanted to use other network operation
01:27:33
centers to host Colossus you know and he
01:27:36
looked they were not available and when
01:27:38
he did find quotes from them they told
01:27:40
him 18 to 24 months he just determined
01:27:43
hey if this there's no reason to even do
01:27:45
this if I can't get this done in you
01:27:47
know a 100 days or something why even
01:27:49
join the race I'm going to be so far
01:27:51
behind and if you look just to wrap this
01:27:53
segment up and get on to our final two
01:27:56
segments if you look at these two charts
01:27:59
about grock it's now uh and you know
01:28:02
listen these benchmarks and these Arenas
01:28:04
and testing there's a lot of controversy
01:28:06
around them and people keep leapfrogging
01:28:08
each other but they they do give us I
01:28:10
think our best shot at looking at
01:28:12
progress this is The Benchmark here for
01:28:15
grock on a bunch of different tests Math
01:28:18
Science and coding and as you can see
01:28:20
grock 3 has now eclipsed Gemini which is
01:28:25
uh
01:28:26
Google's llm and deep seek from China
01:28:30
Claude and chat GPT 40 and so to your
01:28:34
point it's pretty impressive yeah top of
01:28:38
the lmis
01:28:39
leaderboard the the thing here I think
01:28:41
freeberg I'd like to get your um comment
01:28:44
on is if Hardware is the
01:28:48
constraint does that mean that the
01:28:51
person who understands hardware and
01:28:53
buildout as chth was pointing to does
01:28:56
that mean that they by default win Jason
01:28:59
hold on this is what's counterintuitive
01:29:00
it wasn't clear because no it was not
01:29:03
yes I would guess that the last couple
01:29:05
of iterations it seemed like open AI has
01:29:09
moved to what comes after the base model
01:29:12
meaning in the allocation of resources
01:29:14
in terms of what they were creating and
01:29:16
so this is what's so counterintuitive he
01:29:18
was like No And so I I don't understand
01:29:21
what he knew that everybody else didn't
01:29:22
know but that the size of that cluster
01:29:25
made no sense and it could only be a
01:29:27
result like this where he basically
01:29:29
proved that there was still value in
01:29:30
pre-training where size actually led to
01:29:32
better outcomes that's that's not that I
01:29:35
think that was counter it's super
01:29:36
consequential is my is I'm in complete
01:29:39
agreement with the chth and just
01:29:40
freeberg to wrap the segment up and put
01:29:42
a bow on it we see these llms they've
01:29:45
made incredible progress as we just
01:29:46
heard from ev2 or evo2 I'm sorry a Gro
01:29:50
and we're making these giant gains in
01:29:52
space uh you know in work and
01:29:56
specifically in space Dave do you think
01:29:58
this will get us any closer to
01:30:02
Uranus so sad so sad it didn't even land
01:30:05
okay let's do our final don't even don't
01:30:07
even acknowledge don't even acknowledge
01:30:08
it do not acknowledge it because we'll
01:30:09
just do more of it I tried to get your
01:30:11
mouth to do one he wouldn't do it okay
01:30:14
last two segments we're going to talk
01:30:16
about staying private longer and when
01:30:17
you guys are going to go public and then
01:30:19
there's an asteroid coming what do we
01:30:20
want to do first boys you want to talk
01:30:22
about this asteroid coming is it the end
01:30:24
of the world if it hits us what's going
01:30:26
on NASA dropped the probability of it
01:30:29
hitting Earth to one and a half% so
01:30:31
every day when the sky gets dark they
01:30:33
can do a better job seeing this asteroid
01:30:36
that everyone's freaking out about so we
01:30:38
finally got a good night sky two nights
01:30:40
ago the telescopes were able to get a
01:30:43
better trajectory reading on it and that
01:30:45
allows the models to make estimates on
01:30:47
the probability of this asteroid hitting
01:30:49
Earth in 2032 when it's projected uh to
01:30:54
our orbit and so right now the
01:30:56
probability is estimated at 1.5% that it
01:30:59
will hit the earth and based on the size
01:31:01
of this asteroid there's this range it
01:31:03
goes up to 320 feet in diameter as small
01:31:06
as 80 feet in diameter which actually
01:31:08
can have a pretty big effect on how big
01:31:11
of an energy release there would be if
01:31:14
it actually uh you know hit the earth so
01:31:17
even on the high end if it was call it
01:31:19
300 feet it would be the equivalent of
01:31:21
call it a 20 Megaton bomb wow which is
01:31:24
not insignificant if it were that big it
01:31:26
would hit the earth if it was smaller
01:31:28
than that it would probably just
01:31:29
detonate me air and create a massive
01:31:31
shock wave and and Firestorm but the
01:31:34
region that it would decimate would be
01:31:36
limited uh to probably a couple dozen
01:31:39
miles up to a thousand miles of effect
01:31:41
and if you look at the total surface
01:31:42
area of the Earth you know we're talking
01:31:44
about 10 to 15% of the earth having
01:31:46
people that habitate you know enough
01:31:48
people to habitate probably going to
01:31:49
land in an ocean right I mean all right
01:31:50
yeah so it's one and a half% chance of
01:31:52
hitting the Earth and then call it a 15%
01:31:55
chance of it hits the Earth causing loss
01:31:56
of life 10 basis points it hits a city
01:31:59
one basis point City and right and then
01:32:00
it's a function of how big it is if it's
01:32:02
actually as small as 80 feet then it's
01:32:04
not going to be that significant even if
01:32:05
it does get close to habited area so
01:32:08
yeah I'm not losing sleep over over
01:32:10
there did you come across in your
01:32:11
research I feel like this is a real boys
01:32:13
are monitoring the situation moment did
01:32:15
you come across the tunguska event
01:32:18
research so that one Inc yeah so uh I
01:32:22
don't you want to talk about it go ahead
01:32:23
yeah Ju Just um no one knows this in
01:32:25
1908 an asteroid hit the earth it hit an
01:32:28
relatively uninhabited part of Russia it
01:32:31
was a first off the asteroid did not hit
01:32:33
the Earth because it got so hot on
01:32:35
re-entry there was an air burst and it
01:32:38
was a thousand harashima in size the
01:32:41
explosion yeah they have here the 60
01:32:42
meter asteroid and they have the megat
01:32:44
tonage somewhere wow it's the yeah
01:32:47
largest impact event in recorded history
01:32:49
obviously there was you know stuff
01:32:50
before recorded history it flattened 80
01:32:53
million trees
01:32:55
weirdly basically no one was killed
01:32:58
because he was so uninhabited but this
01:32:59
is quite comparable to the one that NASA
01:33:02
is talking about that's right it's about
01:33:03
the same size y exactly and I think you
01:33:06
could take a little bit of reassurance
01:33:07
maybe that we have had similar size
01:33:09
asteroids hit before and there is some
01:33:11
existence proof that despite the giant
01:33:14
explosion you know it doesn't show up in
01:33:16
the climactic data for 198 Tusa asteroid
01:33:18
was at like 160 200t so if if this
01:33:22
asteroid is in that range and it the
01:33:24
Earth you have this kind of explosion in
01:33:25
the
01:33:26
air if it gets above I think 250 roughly
01:33:30
is where they think that it doesn't burn
01:33:31
up fully in the air and it actually will
01:33:33
strike the Earth but yeah that's um
01:33:36
there you go this is roughly what we saw
01:33:38
happen what we think the size will be
01:33:39
right if it hits is there a counter
01:33:42
measure I don't mean to get all sci-fi
01:33:44
here great question yeah but is there a
01:33:46
countermeasure possible and like if this
01:33:48
thing was coming let's say in five
01:33:51
years size yeah relative to the Earth
01:33:54
this is like tens of thousands of
01:33:57
kilometers an hour right it's it's a
01:33:59
it's a very fast moving object it's
01:34:01
pretty small right 160 ft so you've now
01:34:04
got to figure out the exact trajectory
01:34:06
get it perfectly right get a launch off
01:34:09
of the earth and intercept this thing at
01:34:12
the exact moment that you need to to
01:34:14
push it off course or detonate something
01:34:16
near buy it to to redirect it so
01:34:18
technically very complicated very hard
01:34:20
to pull off but this is exactly why we
01:34:22
have this planetary defense
01:34:25
funding at Nasa which is to track these
01:34:27
objects and this is another example by
01:34:29
the way where I would say AI can play an
01:34:31
important role and I'd love Patrick and
01:34:33
John to aine on this but I have a thesis
01:34:35
that like AI more than anything unlocks
01:34:38
deeply complicated project for humans
01:34:40
that would otherwise be kind of
01:34:41
infeasible in the pre AI era I think in
01:34:43
the post a era we're going to be like oh
01:34:45
here's all these projects that we do
01:34:46
that are like oh you know we we on a
01:34:48
daily basis we mine to the Center of the
01:34:50
Earth and we get cool like Rare Earth
01:34:52
minerals from like 500 miles down and we
01:34:54
go to space and colonize the moon and
01:34:56
all these crazy things because AI
01:34:58
unlocks these large scale projects that
01:35:00
would require millions of people to do
01:35:02
things in a coordinated way and AI can
01:35:04
be very smart in this way but I think AI
01:35:05
could play a role also in these
01:35:07
planetary Defense Initiative Concepts
01:35:09
jcal in the future where you can
01:35:10
actually build an a complete project
01:35:12
model in software on how you would
01:35:15
actually address this problem and then
01:35:17
you know go execute it with Automation
01:35:19
and but yeah there's a planetary defense
01:35:21
function at Nasa they track these
01:35:22
objects and they're funded to do it so
01:35:24
we hope that NASA continues to get
01:35:26
funding to do this work very important
01:35:27
and guys it just came through that NASA
01:35:29
just dropped the probability of a impact
01:35:32
event to about a one-third of 1% so it's
01:35:35
gotten even smaller which is we can all
01:35:37
go to sleep comfortably tonight all
01:35:38
right all right now everybody's been
01:35:40
waiting for Patrick John you founded the
01:35:44
company in 2010 it's uh 15 years later
01:35:47
the entire LP industrial complex and
01:35:50
venture capitalist everywhere I'm sure
01:35:52
some employees are wondering when will
01:35:55
stripe go public and under what
01:35:56
circumstances and what's the hold up
01:35:59
here why aren't you public
01:36:02
already yeah look um I think people
01:36:05
sometimes hold us out to be dogmatic or
01:36:09
something on this topic whereas we feel
01:36:12
like so many other people out there in
01:36:15
the world are dogmatic and we just Tred
01:36:17
to be pragmatic H us you know Keith was
01:36:19
on the show and he was saying you know
01:36:20
he believes companies should go public
01:36:22
as quickly as possible I don't know
01:36:23
maybe that's the right thing for some
01:36:25
companies but uh in at least Stripes
01:36:28
case that that hasn't been the case I
01:36:30
also think the environment has changed
01:36:32
quite a bit where it used to be the case
01:36:35
to that to do any return of capital to
01:36:37
shareholders you know or if you needed
01:36:39
any kind of large sums of money you
01:36:41
needed the public markets that's
01:36:42
obviously not true today where uh the
01:36:45
you know stable private markets exist
01:36:47
but we look and we say is strip better
01:36:49
off at the moment as a private or a
01:36:51
public company and you know up to this
01:36:53
point we have determined private that
01:36:55
could change at some point but it's kind
01:36:58
of no Dogma from our point the last
01:37:00
thing I'll just say is you know I think
01:37:01
Keith made the argument people generally
01:37:03
make the argument that it is critical
01:37:05
for discipline to be public and public
01:37:08
companies run in a more disciplined
01:37:10
fashion and I think that's hogwash like
01:37:13
if you need a 25-year-old Fidelity
01:37:15
analyst asking you to double click on
01:37:16
your capex blah blah blah blah to run
01:37:18
the company with discipline something is
01:37:21
horribly wrong at the company and you
01:37:22
need new management and so that argument
01:37:24
has never
01:37:25
really resonated with me basically what
01:37:28
you guys are saying is for your
01:37:31
intellectual perspective you get a lot
01:37:33
more return on the time you spend
01:37:35
talking with the private investors you
01:37:37
have and your team and then and
01:37:40
customers and customers and it would
01:37:42
just be delive and you would have your
01:37:44
outcomes quite honestly if you had to
01:37:46
talk to these other folks who are
01:37:48
talking to you and 50 other companies
01:37:50
don't really know much of anything maybe
01:37:52
very surface level and then may actually
01:37:54
distract you and force you to make
01:37:56
decisions you don't want to make we're
01:37:57
not even that negative not that negative
01:38:00
I was going to say but but it's um
01:38:02
there's no spiritual status associated
01:38:04
with being public like why be public it
01:38:06
is a cheaper source of deeper and more
01:38:08
liquid capital and so if you want
01:38:10
cheaper and uh and more liquid Capital
01:38:12
then you know by all means go with it
01:38:14
but you know it's it's not it's not more
01:38:16
moral and and I think you know again
01:38:19
it's it's just helpful to sort of get
01:38:20
away from uh from that kind of framing I
01:38:22
also think it's noteworthy if you look
01:38:23
at Financial Services in particular and
01:38:25
we're kind of a company at the
01:38:25
intersection of financial services and
01:38:27
Technology being private for a long time
01:38:29
is is the norm so you know Bloomberg is
01:38:31
a private company Fidel is a private
01:38:33
company vanguard's a private company
01:38:34
Jane Street's private company um gold
01:38:37
citel secur Citadel Citadel yeah Goldman
01:38:39
waited 130 years to go public JB Morgan
01:38:42
waited 70 years to go public Visa waited
01:38:44
Visa waited 50 years to go public and
01:38:47
you know again those are all kind of
01:38:49
different times in history so that's
01:38:51
saying you can draw def them but I but
01:38:54
well I I think the thing in financial
01:38:55
services where there's always a tendency
01:38:58
uniquely here to be kind of procyclical
01:39:00
and I think you need to be kind of
01:39:02
particularly careful as a public
01:39:04
financial services company to avoid some
01:39:06
of those Temptations and some of those
01:39:07
Tendencies and so you know I think that
01:39:09
that that's a unique Dynamic that
01:39:11
applies uh in our space and uh and then
01:39:14
you know Financial Services generally if
01:39:17
you look at companies like SpaceX
01:39:18
they're able to provide this yearly
01:39:20
liquidity which actually is probably
01:39:21
better because it Smooths out a lot of
01:39:23
all and then people can get back to work
01:39:25
and just kind of are you guys profit by
01:39:27
the way we are profitable yeah I'm
01:39:30
profitable like a fully loaded Gap net
01:39:32
income basis not like a community
01:39:34
adjusted e but a stuff but shout out
01:39:37
Adam Newman come on the prod
01:39:39
anytime you gotta wear
01:39:41
shoes yeah I do think we
01:39:44
think as it comes you know pertains to
01:39:48
people joining the business and being
01:39:50
compensated you know everyone loves the
01:39:51
idea of an IPO pop but if you look at a
01:39:54
bunch of the other fintech companies you
01:39:57
know Square really great company 70% off
01:40:00
its 2021 Peak PayPal 80% off their 2021
01:40:03
Peak if you're an employee and you join
01:40:05
those companies in 2021 it's not a great
01:40:08
feeling and so again I think the um the
01:40:10
the lack of Val you know the the good
01:40:13
and the bad is you are Nas priced every
01:40:15
single day by the markers but it's not
01:40:17
only a bad thing the framework you know
01:40:20
if I'm trying to predict our actions
01:40:21
like the framework we use is is kind of
01:40:22
two things one I I think you know what
01:40:24
matters is less kind of the returns in a
01:40:26
given year and more duration and so the
01:40:29
question is you know what enables the
01:40:30
best compounding on sort of a 10-e Time
01:40:31
Horizon and you know what's best for
01:40:32
shareholders uh as you really take kind
01:40:34
of the the longer term perspective and
01:40:35
then just what's best for customers and
01:40:37
you know what you know helps you build
01:40:38
the best products and you chat you kind
01:40:39
of said it where you know at least at
01:40:40
this juncture with the business growing
01:40:42
at this rate we want to spend the
01:40:44
marginal hour with h with some customer
01:40:46
and and I think you guys have gotten
01:40:47
this sense like this is our life's work
01:40:49
you know we're not going anywhere we'll
01:40:50
be very happily running stripe in 10
01:40:52
years time in years time and there's so
01:40:54
much going on in this space where we
01:40:56
spent a bunch of time talking about
01:40:57
stable coins talking about AI everything
01:40:59
like that and it's hard enough to stay
01:41:02
ahead in the world of business you know
01:41:04
without all these distractions like you
01:41:05
said and so it's just a question of how
01:41:07
do you set yourself up to win and do
01:41:09
right by a new one in a the world's
01:41:11
pretty competitive I think if you had to
01:41:13
Steelman the bill Gurley point of
01:41:15
view there are very few Founders that
01:41:17
are probably as Steely eyed as you guys
01:41:21
and so what I think a lot of Bo members
01:41:23
in most other situations that are not
01:41:25
stripe deal with is what is a good
01:41:29
forcing function to keep these folks on
01:41:31
track focused and focused and thinking
01:41:34
in a multi-decade kind of way and they
01:41:37
found that the public markets I think do
01:41:39
that more than anything else that's
01:41:40
probably the most compelling for the
01:41:42
folks that would otherwise maybe get
01:41:44
distracted but then for guys like you
01:41:45
that can frankly just do it it's it's
01:41:48
great all right impressive it's really
01:41:50
impressive congratulations well
01:41:51
appreciate you guys coming on the
01:41:52
program come back anytime you were
01:41:54
awesome today and listen let's recap
01:41:57
what have we
01:41:58
learned people got to put some pants on
01:42:00
and get back to work constraint makes
01:42:02
for great art Stripes going public in
01:42:04
2050 chamath lost five billion not
01:42:08
investing uh the coulson's read a lot of
01:42:10
books but I'm still kicking live and
01:42:12
kicking bro he's still in the arena got
01:42:14
a lot of chips still to fire so see what
01:42:16
happen to fire fire fire South American
01:42:19
president shouldn't have their own meme
01:42:21
coins and life finds a way we are and
01:42:26
and you pronounce a kison obviously as
01:42:28
aison because you know we're down the
01:42:30
road and carry and we go and get some
01:42:32
eggs and bakey sometimes okay coming to
01:42:35
South by Southwest brought to you by the
01:42:38
co cison brothers and stripe a Allin is
01:42:42
headed to the South by Southwest they're
01:42:44
not sponsoring it I'm joking Allin is
01:42:46
headed to South by Southwest on March
01:42:47
13th me and freeberg are going to sit
01:42:49
down and do our interviews two besties
01:42:52
on the future of Med media and building
01:42:55
businesses in this new media ecosystem
01:42:57
we're going to have a casual party food
01:42:58
drinks the whole thing event is going to
01:43:00
be uh pretty intimate couple hundred
01:43:03
seats when are you guys do this March 13
01:43:06
you opt it out me and freeberg want to
01:43:08
do it oh Thursday no K doker and uh it's
01:43:13
by application only with a small $30
01:43:16
registration fee of which stripe will
01:43:18
take $19 go to allin.com events to apply
01:43:22
I'm not B about it and programming note
01:43:26
the besties are on a tear we were on
01:43:28
Megan Kelly last week and next week our
01:43:31
bestie fredberg is representing us on
01:43:34
Celebrity Jeopardy we can't say what
01:43:37
happened get the clips ready get the
01:43:38
clips get the clips ready we are going
01:43:41
to do a recap of every single question
01:43:44
when when do you when do you when ises
01:43:45
it air on Monday next week I think I
01:43:47
don't know Wednesday at 900 p.m.
01:43:49
Wednesday Wednesday at 9M perfect before
01:43:51
the taping yum yum H yeah perfect
01:43:55
perfect there he
01:43:56
is between Anna
01:43:59
Navaro she's from The View right well
01:44:01
she's pretty angry I've seen clips of
01:44:03
her she's I should have gotten some
01:44:05
counsel ahead of signing up for
01:44:06
Celebrity Jeopardy on the lack of upside
01:44:09
in doing this and you will see why we'll
01:44:12
talk next week oh no bye oh no you lost
01:44:14
not good you
01:44:16
lost view you didn't lose to the view
01:44:20
did you look guys I'm just telling you
01:44:23
got 160 IQ The View put together doesn't
01:44:26
have 160 IQ let me just tell you well
01:44:29
we'll talk about it
01:44:30
afterwards don't tell me they got you on
01:44:32
pop culture you're pretty good on pop
01:44:35
culture oh no no comment okay love you
01:44:37
guys I got to go love you bye bye see
01:44:39
you next time bye
01:44:41
boys let your winners
01:44:48
ride and instead we open source it to
01:44:50
the fans and they've just gone crazy
01:44:52
with it Love You Queen
01:44:55
[Music]
01:45:01
of
01:45:03
Besties that's my dog taking your
01:45:09
driveway oh man
01:45:11
myit we should all just get a room and
01:45:13
just have one big huge orgy cuz they're
01:45:15
all just useless it's like this like
01:45:17
sexual tension that they just need to
01:45:18
release somehow
01:45:25
P we need to get merch
01:45:30
[Music]
01:45:34
our I'm going in
