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E99: Cheating scandals, Twitter updates, rapid AI advancements, Biden's pardon, Section 230 & more

October 07, 2022 / 01:25:30

This episode covers topics such as the recent cheating scandals in chess and poker, Elon Musk's Twitter acquisition, and marijuana legalization. Guests include David Sachs, Friedberg, and Chamath Palihapitiya.

The discussion begins with the cheating scandals in chess and poker, focusing on Hans Neiman's alleged cheating in chess tournaments. Sachs explains how statistical analysis has raised suspicions about Neiman's gameplay, while Friedberg shares insights on the implications of cheating in competitive environments.

The conversation shifts to Elon Musk's ongoing Twitter acquisition, with Sachs detailing the complexities surrounding the deal and the potential financial implications for Musk and Twitter shareholders.

Later, the hosts discuss President Biden's recent announcement to pardon federal offenses of simple marijuana possession. The implications of this decision on the legal cannabis industry and the need for regulatory changes are explored.

The episode concludes with a debate on Section 230 and the responsibilities of social media platforms regarding content moderation and free speech.

TL;DR

The episode discusses cheating scandals in chess and poker, Elon Musk's Twitter deal, and Biden's marijuana pardons.

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we're seven minutes in and we've

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produced absolutely nothing that will go

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in the show

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hey burgers

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ax I'm actually angry at sax for not

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publishing my AMA from the other day

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crashed we had such a crowded room we

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had some people in the room for like

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four hours it was crazy it was like the

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original days of Clubhouse everyone I

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know that was trying to get in was

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texting saying they couldn't get in so

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it definitely capped out right I know

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well we hit we hit some scalability you

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may want to buy an extra server sax

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cheap weren't you the same guy who was

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responsible for scaring PayPal no that

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was somebody else that was eBay

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they sold it before it's killed no no

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that's not true we had huge scalability

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challenges at PayPal too it seems like a

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theme yeah the theme is when you have an

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app that's breaking out you hit

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scalability challenges it's called a

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high class problem 2 000 people is not a

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high class problem it's a trickle it's

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2022. 2 000 people participate in the

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conversation is

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a child I haven't written code in 20

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years here's what you do when you get to

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a thousand people coming to the room

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that's a lot everybody else is in

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passive for you've never written code

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ever of course I of course I drive

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that's a lie come on be honest oh yeah

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it's actually been 25. the last time I

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wrote code was Lotus Notes it's true

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and let your winners ride

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[Music]

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we open source it to the fans and

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they've just gone crazy

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[Music]

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so there have been three cheating

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scandals across poker chess and even

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competitive uh fishing I don't know if

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you guys saw the fishing one but they

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found weights and fillets during a fish

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uh way and that everybody wants us to

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check in on the chess and the poker

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scandals

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chess.com just released their report

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that this Grand Master has been

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suspended they have evidence he cheated

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basically in a bunch of

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uh tournaments that were in fact for

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money he denied that he had done that

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but he had previously cheated as a kid

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they now have the statistical proof that

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he was playing essentially perfect chess

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and uh they've outlined this in like

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hundreds of pages in a report Saxy what

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are your thoughts on this uh scandal in

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chess Magnus Carlson finally came out

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and explained why he thought Hans Neiman

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was cheating basically he got the strong

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perception during the game that Hans

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wasn't really putting in a lot of effort

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that he wasn't under a lot of stress and

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he's he it's his experience that when

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he's playing you know the top players

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they're intensely concentrating and the

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Hans demon didn't seem to be exerting

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himself at all so his you know hackles

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were raised and got suspicious and then

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you know he has had this meteoric rise

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the fastest rise in classical chess

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rating ever and I guess there were he

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had gotten suspended from chess.com in

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the past for cheating so on this basis

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and maybe other things that Magnus isn't

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telling us Magnus basically said that

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this guy is cheating I think the maybe

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the interesting part of this is that

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there's been a lot of analysis now of

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Hans Neiman's games and I just think the

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methodology is kind of interesting so

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what they do is they run all of his

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games uh through a computer and they

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compare his moves to the best computer

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move and they basically assign a

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percentage that correlation matches the

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correlation matches the computer move

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and what they found is there were a

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handful of games where it was literally

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a hundred percent that's basically

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impossible without cheating I mean you

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look at the top players who through an

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entire career have never had 100 game

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that you know chess is so subtle that

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the computer can now see so many moves

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into the future that nailing the best

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move every single time for 40 50 100

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moves is just and and and in chess which

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a human really can't do that well is

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that there are positional sacrifices

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that you will make in short lines that

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pay off much much later in the future

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which is impossible for a human to

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calculate and so you know and you saw

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this by the way when uh I think it was

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the it it was the Google AI the deepmind

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AI that also play chess so the idea that

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this guy could pay could play absolutely

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perfectly according to those lines is

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only possible if you're cheating right

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exactly so so there were a handful of

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games at 100 and then there were

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tournaments where his percentages were

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in the 70s something plus and so just to

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give you some basic comparison Bobby

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Fischer during his legendary 20-game

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winning streak uh was at 72 percent so

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he only matched the computer so for best

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move 72 of the time Magnus Carlson

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playing at his best is 70 percent uh

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Gary Kasparov in his career was 69 and

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then the you know the the super GM's

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category are typically in the 64 to 68

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range so I think it's really interesting

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actually how you can now quantify by

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comparing the human move to the best

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computer move and it's multiple

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computers training the best they

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actually have it provides a way to

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assess who the greatest player ever is

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um I actually thought that it was Magnus

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but now maybe there's a basis for

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believing it was Bobby Fischer because

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he was at 72 and Max is only at 70.

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however look the idea that Hans Neiman

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is in the 70s 80s or 90s during

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tournaments would be you know just an

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off the charts level of play and if if

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he's not cheating then we should expect

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over the next couple of years that he

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should rapidly become the world's number

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one player over the board uh you know

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now that they have all this

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anti-cheating stuff right so it'll be

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interesting to see what happens in his

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career now that they've really cracked

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down on you know on with with anti-anti

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Gene technology I have a general

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observation which is these people are

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complete losers

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the people that cheat in any of these

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games don't understand

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this basic simple idea which is that

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trying is a huge part of The Human

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Experience the whole point is to be out

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there in the field of play trying and

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it's basically taking the wins and the

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losses and getting better that is the

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path that's what's fun once you actually

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win it's actually not that much fun

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because then you have this pressure of

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maintaining Excellence that's a lot less

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enjoyable than the path to getting there

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and so the fact that these people don't

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understand that makes them slightly

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broken in my opinion and then the other

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thing is like why is it that we have

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this strain of people now that are just

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so devoid of any personal responsibility

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that they'll just so brazenly take

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advantage of this stuff it's really

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ridiculous to be they don't it's really

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sad these people are pathetic it's

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really pathetic this but it is really

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interesting how they caught him and

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running this against the computer here's

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a chart of um his scores in these

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tournaments oh well here is this first

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chart is how quickly he Advanced which

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was off the charts and then the second

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chart that's really interesting is

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um his chest.com strength so if you

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don't know chess.com it has become like

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a juggernaut in the Chess World

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especially after that HBO series

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came out a lot of people subscribe to it

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I subscribed to it I like to play chess

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there

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and man you look at the chest strength

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score there

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he was just like perfect and then the

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number of games he likely cheated in you

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can see the last two columns he's

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basically cheating in every game

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you know Queen's Gambit yeah great show

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on Netflix

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and he he said he didn't cheat in any uh

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of the uh games

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where they were live streaming but

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they've proven that wrong sax how does

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he cheat in person then well that's the

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thing no one really knows and I don't

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want to overly judge it until they have

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hard proof that he was cheating I mean

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look here's the thing he was never

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caught in the act it's just that the

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computer evidence you know seems pretty

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damning

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and I mean here's the thing is I don't

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know how they prove I don't know how

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they prove that he was cheating over the

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board without actually catching him

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doing it and I don't I still don't think

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anyone really has a good theory in terms

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of how he was able to do that well it's

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not just him though like look the the

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fishing thing Jason which was crazy I

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think Friedberg shared the video this

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guy was in a fishing competition and

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they basically caught these fish and

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then they put these big weighted pellets

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inside the fish's body they even put

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like a you know chicken breast and

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chicken fillets inside of the things

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yeah

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you know uh then there's no crossover

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now in poker everybody's afraid that

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there are ways in which you can read the

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RFID and some of the cards and some of

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these you know televised situations and

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and front run what the what the playing

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situation is so that you know whether

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you're winning or losing and again I

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just asked the question like

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is it is it is this are things that bad

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that this is what it gets to like we all

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play poker the idea that we would play

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against somebody that would take that

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edge

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yeah it's gross yeah it's really makes

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me really it's sad so disappointing yeah

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it's horrible one one observation might

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be that across all three because I'm

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trying to find some common thread across

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these but it could be that there was a

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lot of cheating going on for a long time

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and maybe the fact that we do have

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so much digital imagery that's live on

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these things now and so much coverage

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and everyone's got a cell phone that

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suddenly

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our perception of the cheating in

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competitive events is becoming

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more tuned whereas maybe there's been a

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lot of cheating for a long time and it's

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just kind of coming to light I mean we

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didn't have a lot of live streaming in

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poker who knows I mean we could probably

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ask Phil this we're kidding but like for

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how many years well there was Visions

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yeah well there were tons of cheating

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and online poker yeah remember like

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people are using these like software

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programs that would uh track the hand

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history yeah of your opposition yeah

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exactly so

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so it helped you assess whether the

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person might be bluffing in that

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particular situation yeah like he has

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superhuman memory so I don't know if you

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guys I don't know if you guys watch

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Twitch like video games like fortnite or

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whatever but there are like players that

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have been accused of using the screen

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overlay systems that basically more

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accurately show you and drive the mouse

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to where an individual is on the screen

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so you can more accurately shoot them

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and so there's software overlays that

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make you a better

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you know competitive video I'll tell you

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what the through line is and then this

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the stuff basically became like so now

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what's interesting is now there's eye

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tracking software that people are using

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on Twitch streams to see if the

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individual is actually spotting the

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target when they shoot or if the

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software is spotting the target yeah

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they're called reverse team Bots they're

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aimbots yeah yeah and like reverse cheap

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the whole thing and I think what's

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interesting is just that there's so much

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you know Insight now so much more video

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streams so much more I mean think about

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all those guys

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yeah and there's cell phones and they

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all videoed this thing happening yeah I

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think 10 years ago that wouldn't have

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been the case and there wouldn't have

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been a big story about it and so you

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said there was a theme you wanted to uh

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there was a threat I I think the theme

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is is pretty obvious which is that

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there's been an absolute decay

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of personal responsibility people don't

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feel like there's any

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downside to cheating anymore and they're

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not willing to take it upon themselves

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to take a journey of wins and losses to

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get better at something they want the

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easy solution

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the easy solve the quick answer you know

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that gets them to some sort of finish

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line that they've imagined for

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themselves will solve all their problems

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the problem is it doesn't solve any

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problems and it just makes them a wholly

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corrupt individual yeah okay so let's

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talk about this Hustler Casino Live uh

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cash game play there's this woman Robbie

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who is a new player apparently she's

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being staked in a very high stakes game

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she's playing as a guy Garrett who is a

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very very

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um known winning cash game player

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and it was a very strange hand on the

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turn all the money gets in she says she

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has a bluff catcher then she claims that

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she had a thought she misread her hand

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now people are saying that

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the poker world seems to be 70 30 that

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she cheated but people keep vacillating

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back and forth

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there was a lot of weird word salad that

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she said that she had a bluff catcher

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which would normally be an ace then she

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said she thought she had a pair of

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Threes And then she immediately said

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afterwards that he was giving her too

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much credit

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they confronted her in the hallway she

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gave the money back because she

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supposedly loves production so all this

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stuff sounds very weird one side says

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okay while this is happening because

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she's a new player the other side is

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saying somebody was signaling her that

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she was good and giving her just a

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binary you're good because if you were

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gonna cheat cheating with Jack high in a

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situation where you just put all in for

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a 200 quarter million dollar pot seems

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very suspect

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uh I don't know if you guys watched the

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hand breakdown where does everybody

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stand on a percentage basis I guess if

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they think she was cheating or not

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because we this is not definitive

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obviously it's not like they cut it open

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and found the ball bearings it's not

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it's not so obvious in that situation

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but I think the way that that line

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played made no sense

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and I guess in her previous hand she had

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a jack three and there was a three on

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the board so if she misread her hand was

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ten ten nine three no but you would have

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but you would have you would have had to

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call the Flop so I'm thinking what

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yeah no I get it the hand makes no sense

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but I'm just trying to find a logical

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explanation and that Jack three

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explanation somebody kind of fed that to

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her and then she changed her story to

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that so this changing of the story is

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the thing I was sort of keyed on

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Friedberg is why does she keep changing

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her story is it because she's

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embarrassed maybe she's had a couple of

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beverages or whatever

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or she's just a new player and she's

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embarrassed by her play and can't

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explain it she can't explain the hand

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history all of the things you're saying

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are probable

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I don't think that yeah I don't think

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there's any data for us to have a

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strongly held point of view on this I'm

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just looking forward to us all playing

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live yeah HCL Poker Live October 21st

00:13:57

minus David Sachs unfortunately to mop J

00:14:00

Cal gerthner

00:14:02

Stanley Tang Phil Hellmuth so we're

00:14:04

going to be playing on the same stream

00:14:05

we're gonna be playing on the same

00:14:07

screen same table I figured out how to

00:14:09

hack into the video stream for the

00:14:10

camera I just got my RFID sunglasses as

00:14:13

well I'm gonna read all your shitty

00:14:14

hands jaycal I'm gonna take your money

00:14:16

and I'm gonna buy your kids

00:14:18

for my 40th birthday Sky organized poker

00:14:22

in Tahoe okay and and we we brought in

00:14:25

the team from CBS that was the present

00:14:27

and they they taped it as if it was

00:14:29

being broadcast with whole cards and

00:14:31

commentators and we edited it into a

00:14:33

two-day show it was an incredible

00:14:35

birthday present I I it was it's one of

00:14:37

the greatest things that that anybody's

00:14:39

ever given me I appreciate

00:14:41

there was a one hour block where

00:14:44

somebody at the table said okay guys how

00:14:46

about we do a cheating free-for-all yes

00:14:48

where you could look at each other's

00:14:50

cards and you know you could sort of

00:14:52

help somebody else

00:14:53

switch cards whatever in that one hour

00:14:56

our beautiful home game of friendship

00:14:59

became Lord of the Flies I have never

00:15:02

seen so much hatred Angling

00:15:06

Behavior oh my God it was incredible

00:15:10

all that humans are capable of so I I

00:15:12

hope that we never uh we never we never

00:15:14

see cheating in our game yeah well we'll

00:15:16

see how it goes on October 21st at HCL

00:15:18

Poker Live

00:15:20

I'm excited I can't wait it should be a

00:15:22

lot of fun it should be a lot of fun oh

00:15:23

and uh we're not having any official 100

00:15:26

stuff but the fans uh some of the fans

00:15:28

who were at the um all in Summit

00:15:32

2022 are doing

00:15:34

uh their own 100 episode 100 meetups on

00:15:38

October 15th I think all in meetups.io

00:15:42

so there are fan meetups happening in

00:15:43

Zurich in a bunch of other places I'm

00:15:45

going to FaceTime into some of them and

00:15:46

just say hi to the fans you know it

00:15:47

might be like 10 people in a bar

00:15:49

somewhere

00:15:50

um I think the largest one is like Miami

00:15:52

or San Francisco are going to be like 50

00:15:53

people or something we should all

00:15:55

FaceTime it that'd actually be kind of

00:15:56

fun I I'm basically I told them to send

00:15:59

me an invite and I'll FaceTime in any

00:16:00

time this is next week when is this the

00:16:03

15th I think is this occurring

00:16:06

the October 15th it's a Saturday the

00:16:08

Saturday after the 100th episode people

00:16:09

are doing these all in meetups.io what's

00:16:12

next earlier this week it was reported

00:16:15

that Elon contacted Twitter's board and

00:16:18

suggested that they move forward with

00:16:20

closing the transaction at the original

00:16:21

terms and the original purchase price of

00:16:24

54.20 cents a share in the couple of

00:16:27

days since then and even as of right now

00:16:29

with some news reports coming out here

00:16:31

on Thursday morning

00:16:32

um it's it appears that there are still

00:16:34

some question marks around whether or

00:16:36

not the deal is actually going to move

00:16:38

forward at 5420 a share because Elon as

00:16:40

of right now the report said is still

00:16:43

asking for a financing contingency in

00:16:45

order to close and there's a lot of back

00:16:47

and forth on what the terms are

00:16:48

meanwhile the court case in Delaware is

00:16:50

continuing forward on whether or not

00:16:52

Elon breached his terms of the original

00:16:55

agreement to close and buy Twitter at

00:16:57

54.20 as we know leading up to the

00:17:01

signed deal or a post signing the deal

00:17:04

Elon put together a financing Syndicate

00:17:06

a combination of debt investors as well

00:17:09

as Equity co-investors with him to do

00:17:11

the purchase of Twitter at 54.20 a share

00:17:15

so the 40 some odd billion dollars of

00:17:17

capital that's needed was committed by a

00:17:20

set of investors that were going to

00:17:21

invest debt and equity and there's a big

00:17:23

question mark now on whether or not

00:17:25

those investors want to or would still

00:17:27

consummate the transaction with Elon

00:17:29

given how the markets have turned and

00:17:31

given how debt markets are trading and

00:17:33

Equity markets are trading so chimath

00:17:35

I'd love to hear your point of view on

00:17:37

what um hurdles Does Elon still have in

00:17:39

front of him does he still want to get

00:17:41

this done and is there still a financing

00:17:43

Syndicate that's standing behind him at

00:17:45

the original purchase price to get it

00:17:46

done

00:17:47

that's a great question

00:17:49

um maybe the best way to start is Nick

00:17:50

do you want to queue up what I said in

00:17:53

August 25th the lawsuit really boils

00:17:56

down to one very specific clause which

00:17:58

is the Pinnacle

00:18:00

question at hand which is there is a

00:18:02

specific performance

00:18:05

Clause that Elon signed up to

00:18:08

right which you know his lawyers could

00:18:11

have struck out and either chose not to

00:18:13

or you know couldn't get the deal done

00:18:15

without and that specific performance

00:18:18

Clause says that Twitter can't force him

00:18:21

to close at 5420 a share

00:18:24

and I think the the issue at hand at the

00:18:26

Delaware business court is going to be

00:18:28

that because Twitter is going to point

00:18:30

to all of these you know gotchas and

00:18:33

disclaimers that they have around this

00:18:35

bot issue

00:18:36

as their cover story

00:18:40

and I think that really you know this

00:18:43

kind of again builds more and more

00:18:44

momentum in my mind that the most likely

00:18:48

outcome here is a settlement where

00:18:51

you have to pay

00:18:53

the economic difference between where

00:18:56

the stock is now and 5420 which is more

00:18:58

than a billion dollars

00:19:00

or you close at some number below 54.20

00:19:05

cents a share

00:19:06

and I think that that is like you know

00:19:08

if you had to be a betting person that's

00:19:09

probably and if you look at the

00:19:11

the way the stock is traded and if you

00:19:14

also look at the way the options Market

00:19:15

trades that's what people are assuming

00:19:18

that there's a seven to ten billion

00:19:19

dollar swing

00:19:21

and if you impute that into the stock

00:19:22

price you kind of get into the fifty one

00:19:25

dollars a share kind of a an acquisition

00:19:27

price again I'm not saying that that is

00:19:29

right or should be right that's just

00:19:30

sort of what the market says yeah so so

00:19:33

I it turns out that you know sort of

00:19:35

like that

00:19:36

kind of guessed him it turned out to be

00:19:38

pretty accurate because the stock today

00:19:39

is at 51 this year so I think that the

00:19:42

specific performance thing is exactly

00:19:44

what this thing has always hinged on and

00:19:47

I think that there was a realization

00:19:48

that there were very few outs around how

00:19:51

that contractual term was written and

00:19:53

agreed to so there is an out in the

00:19:56

contract and that out says that I think

00:19:58

it's by April if um if the deal doesn't

00:20:02

get done by April then the banks can

00:20:04

walk away from their commitment to fund

00:20:06

the debt and if the banks walk away then

00:20:09

Elon does have a financing contingency

00:20:11

that allows him to walk away so the

00:20:14

actual set of events that have to happen

00:20:16

is those two things specifically get to

00:20:18

April so the banks can pass and say

00:20:20

we've changed our mind market conditions

00:20:22

are different and then Elon is able to

00:20:24

say well you know the banks just walked

00:20:26

away right now the banks if you look at

00:20:29

all of the debt that they've committed

00:20:30

to

00:20:31

while they committed at a point in time

00:20:34

when the debt markets were much better

00:20:36

than they are today in the last you know

00:20:39

six or seven months since they agreed to

00:20:41

do this the debt markets have been

00:20:43

clobbered and specifically junk bonds

00:20:45

and a bunch of junk bond debt the yields

00:20:48

that you have to pay so the price to get

00:20:49

that kind of debt has skyrocketed so

00:20:52

roughly back of the envelope math would

00:20:55

tell me that right now the banks are

00:20:56

offside between one and two billion

00:20:58

dollars because they're not going to be

00:21:00

able to sell this debt to anybody else

00:21:01

so I think the banks obviously want to

00:21:03

weigh out the problem is their only way

00:21:06

out is to run the shot clock off until

00:21:08

April so I think that's the dance that

00:21:10

they're in right now elon's trying to

00:21:13

find a way to solve you know for the

00:21:15

merger

00:21:16

I think Twitter is going to say we're

00:21:17

not going to give you a financing

00:21:18

contingency you have to bring the banks

00:21:20

in and close right now and then we will

00:21:22

not go to court otherwise we're going to

00:21:25

court

00:21:26

and so I think it's a very delicate

00:21:28

predicament that they're all in but my

00:21:30

estimate is that the equity is probably

00:21:32

20 percent offside so it's not a huge

00:21:35

thing he can make that up because he can

00:21:37

create Equity value like nobody's

00:21:38

business

00:21:39

the debt is way offside by a couple

00:21:41

billion dollars

00:21:43

which is hard to make back but I think

00:21:44

in the end you know given enough time

00:21:47

they can probably make that back

00:21:49

the best off in all of this are the

00:21:50

Twitter shareholders they're getting an

00:21:53

enormous premium to what that company is

00:21:55

worth today in the open market

00:21:57

and so I think this deal is going to

00:21:58

close it's probably going to close in

00:22:00

the next few weeks and had you bought

00:22:02

Twitter when we were talking about it in

00:22:04

August you would have made 25 in six

00:22:07

weeks and you know if the deal closes at

00:22:08

54 you would have made it you know a

00:22:10

third of your money in eight weeks which

00:22:12

is you know very hard to do in a market

00:22:14

if you're a GP at one of the funds like

00:22:17

Andreessen or Sequoia

00:22:19

and you had made this commitment to Elon

00:22:21

or even Larry Ellison a couple months

00:22:24

ago

00:22:25

do you fight against closing at 5420 do

00:22:28

you stick with the deal and support him

00:22:31

I mean what do you do given that the

00:22:32

premium is so much higher than where the

00:22:34

market would trade it at today some

00:22:35

people are saying the stock should be at

00:22:37

like 20 bucks a share or something the

00:22:38

average premium in an m a transaction in

00:22:40

the public markets is about 30 percent

00:22:43

so um and I think the fair value of

00:22:46

Twitter is around 32 to 35 bucks this

00:22:49

year

00:22:49

so you know it's not like he is

00:22:52

massively massively overpaying

00:22:55

and so you know I would just sort of

00:22:56

keep that in the realm of the possible

00:22:59

so like if you take 35 as the midpoint

00:23:02

fair value is really 45.50 so yeah he

00:23:06

paid 20 more than he should have but he

00:23:07

didn't pay a hundred percent more

00:23:09

so it's not as if you can't make that

00:23:11

Equity back as a private company

00:23:13

particularly because there's probably

00:23:15

ten dollars of fat in the stock if you

00:23:17

think about just Opex right in terms of

00:23:19

all the buildings they have maybe they

00:23:21

don't need as many employees maybe they

00:23:23

revisit salaries you know one thing is

00:23:25

when I looked at doing an activist play

00:23:27

at Twitter I think I mentioned this five

00:23:30

or six years ago one of the things that

00:23:31

I found was at that time Twitter was

00:23:33

running their own data centers and you

00:23:36

know the most obvious thing for me at

00:23:37

that time was like we're going to move

00:23:38

everything to AWS now I don't know if

00:23:40

that happened but I'm sure that if it

00:23:42

hasn't just bidding that out to Azure

00:23:45

gcp and AWS can raise you know three or

00:23:48

four billion dollars because I'm sure

00:23:49

those companies would want this kind of

00:23:51

an app on their cloud

00:23:53

so there's all kinds of things that I

00:23:55

think Elon can do as a private company

00:23:56

to make back maybe the small bit that he

00:23:59

overpaid and then he can get to the core

00:24:01

job of rebuilding this company to be

00:24:03

usable uh this product to be usable

00:24:05

because look I'll just speak as a user

00:24:06

right now

00:24:08

it has been decaying at a very very

00:24:11

rapid clip

00:24:12

and I think that his trepidation in

00:24:14

closing the merger

00:24:16

in part also even though he hasn't said

00:24:18

it has to do with the quality of the

00:24:20

experience it's just degraded it's not

00:24:22

as fun to use as it was during the

00:24:25

pandemic

00:24:26

um or even before the pandemic so

00:24:28

something is happening inside that app

00:24:30

that needs to get fixed and if he does

00:24:32

it he'll make a ton of money sort of

00:24:34

like what happened with Friendster and

00:24:35

Myspace and any social networking app

00:24:37

over time the quality degrades if it's

00:24:40

not growing it's shrinking and it gets

00:24:41

if it if it's if it's not growing and

00:24:43

also if the product hygiene isn't

00:24:46

enforced in code and product hygiene in

00:24:48

this case are this you know the spam

00:24:51

Bots you know the trolling it can really

00:24:55

take away from the experience yeah I

00:24:57

mean interestingly like if you think

00:24:59

back to the original the the starting

00:25:01

Days the original days of Twitter I

00:25:02

don't know if you guys remember you

00:25:04

would send in an SMS to do your Tweet

00:25:06

and then it would post up and other

00:25:08

people would get the SMS notification

00:25:10

and um it would crash all the time and

00:25:13

the apps were the app was notoriously

00:25:15

crashing it was poorly architected at

00:25:18

the beginning and some people have

00:25:19

argued that Twitter has had

00:25:22

a cultural technical incompetence from

00:25:25

the earliest days I think that's a

00:25:26

little harsh so I do think look Twitter

00:25:28

was known for what's called a fail whale

00:25:30

you know they used to have these fail

00:25:31

whales constantly

00:25:33

and they did hire people that attempted

00:25:36

to try to fix it I remember the the

00:25:38

funniest part of when I went in there

00:25:40

and said hey here's my plan and here's

00:25:42

what I want to do is literally a day or

00:25:44

two later the head of engineering quit I

00:25:46

can't remember who his name was but he

00:25:48

was just out the door uh but it is a

00:25:54

I think it is a team that has tried its

00:25:56

best

00:25:57

that probably at the edges definitely

00:26:00

made some technical miscalculations like

00:26:02

I said at that time the idea that any

00:26:04

app of that scale would use their own

00:26:06

data centers made note technical sense

00:26:09

whatsoever it made the app laggy it made

00:26:11

it hard to use it made it more prone to

00:26:13

downtime to your point

00:26:15

but that being said I would be shocked

00:26:17

if they haven't made meaningful

00:26:18

improvements because the stack of the

00:26:21

internet has gotten so much better over

00:26:22

the last seven years and so to your

00:26:24

point David if they didn't take

00:26:25

advantage of all these new abstractions

00:26:28

and mechanisms mechanisms to rebuild the

00:26:30

app or to rebuild search or to rebuild

00:26:32

you know how you know all these

00:26:35

infrastructure elements of the app work

00:26:36

I would be really surprised because then

00:26:38

what are they doing over there yeah well

00:26:40

look I mean to the point earlier besides

00:26:42

the product points there was a

00:26:44

a really good

00:26:46

a tweet I liked

00:26:49

that said for what it's worth I think

00:26:51

Elon will show us just how lean the

00:26:53

Silicon Valley Advertising companies can

00:26:54

be run at the very least it'll be an

00:26:56

interesting thought experiment for

00:26:58

spectators

00:27:00

um because if he does go in and actually

00:27:01

does significantly reduce Opex and head

00:27:03

count and the company does turn

00:27:05

profitable and he can grow it well look

00:27:07

it'll really by the way it'll really be

00:27:09

a beacon from the financial big

00:27:11

companies yeah from a financial

00:27:13

perspective there is ten dollars a share

00:27:15

in Opex cuts that he should make right

00:27:17

away just so that he is economically

00:27:19

break even and he looks like every other

00:27:21

m a transaction you know you paid a 30

00:27:23

premium and you bought a company there

00:27:26

is a lot of margin of safety there if

00:27:27

Elon does that so to your point there

00:27:29

probably is and there probably needs to

00:27:31

be a meaningful riff at Twitter I'm not

00:27:33

saying it's right I'm not saying it's

00:27:34

you know and I feel for the people that

00:27:36

may go through it but from a financial

00:27:37

perspective the math makes sense for him

00:27:40

to do that because then he is a break

00:27:43

even proposition on a go in m a

00:27:45

transaction and I think that there's

00:27:46

there's a lot of intelligent Financial

00:27:49

sense so that all the debt holders feel

00:27:51

like he's doing the right thing and all

00:27:53

the equity holders particularly see a

00:27:56

chance for them to make a decent return

00:27:57

here

00:27:58

all right well let's move on

00:28:01

conversation a great conversation

00:28:03

between

00:28:04

Dave Friedberg uh about

00:28:07

the Twitter transaction and now we're

00:28:09

being rejoined by our besties

00:28:13

yeah how was your cappuccino Jayco that

00:28:16

was great I have a I have a nice cold

00:28:18

brew here a nice iced Cobra and a nice

00:28:20

drip coffee I'm working but I'd love to

00:28:23

talk about topics that I'm not uh being

00:28:24

subpoenaed or depositioned about we will

00:28:27

have a lot to say in the coming weeks

00:28:28

I'd love to talk about topics that my

00:28:30

lawyers have advised me not to talk

00:28:31

about how Eerie was our prediction 51

00:28:34

bucks a sharing it is exactly where the

00:28:36

stock is right now that's Yuri

00:28:38

yeah uh all right lots of advances let's

00:28:41

keep going yeah speaking of Elon uh

00:28:43

Tesla AI day

00:28:45

was last week I actually went it was

00:28:47

great uh this is a recruiting event

00:28:49

where what did you do after Fel helmuth

00:28:52

and I went and uh I drove Phil home

00:28:54

youth home uh the end uh no it's a great

00:28:57

event and

00:28:59

it uh is essentially a giant recruiting

00:29:01

event hundreds of AI sorry sorry I'm

00:29:04

sorry I'm sorry can we just talk about

00:29:06

Phil hamley's non-sequitur in the group

00:29:08

chat about Ken Griffin

00:29:10

I mean oh yeah where he's just like I

00:29:14

made a joke about his net worth and what

00:29:16

he's going on what is going on we were

00:29:18

talking about the most serious of topics

00:29:20

and he just comes seven seconds to fill

00:29:22

it's what's going on seven seconds to

00:29:25

fill by the way I uh I I was uh texting

00:29:27

with uh Daniel negranu he did an

00:29:30

incredible podcast if you guys with Lex

00:29:32

Friedman if you haven't listened to it

00:29:34

the Daniel negronu uh pod with Lex is

00:29:37

incredible but I I was joking with

00:29:40

Daniel that there's a section where he's

00:29:41

talking about the greatest poker players

00:29:43

of all time and if you look in the bar

00:29:45

of YouTube it shows where the most

00:29:47

viewership was and it was exactly the 30

00:29:50

seconds he talks about helmuth and I

00:29:52

said to Daniel this must have been Phil

00:29:54

re-watching it over

00:30:05

so anyway the event was um uh super

00:30:08

impressive

00:30:10

Elon only spoke when he showed The

00:30:12

Optimist the new robot he's building a a

00:30:15

general purpose robot that will work in

00:30:17

the factories it's very early days but

00:30:20

they showed two versions of it and um he

00:30:22

said he thinks they could get it down to

00:30:24

twenty thousand dollars it's going to

00:30:25

work in the factory so it's actually got

00:30:26

a purpose

00:30:27

and obviously the factors already have a

00:30:29

ton of robots but this is more of a

00:30:31

robot that uh will benefit from the

00:30:34

general or the the computer vision

00:30:38

and the AI the narrow AI being pursued

00:30:40

by the self-driving team this is like

00:30:42

two and a half hours of really intense

00:30:43

presentations

00:30:45

um the most interesting part for me was

00:30:46

uh they're building their own super

00:30:48

computer

00:30:48

and their chips and the dojo

00:30:52

supercomputer was really impressive

00:30:55

um at how much they can get through uh

00:30:58

scenarios so they're building every

00:31:00

scenario of every self-driving I

00:31:01

actually have the full self-driving beta

00:31:04

on my car I've been using it it's pretty

00:31:06

impressive I have to say

00:31:08

if you haven't used it yet I feel like

00:31:12

AI is moving at a pretty Advanced clip

00:31:15

the past year if you haven't also seen

00:31:17

meta announced a text to video generator

00:31:20

so this is even more impressive than

00:31:22

dolly dolly you put in a couple of words

00:31:24

Friedberg and you get a painting or

00:31:26

whatever

00:31:27

this is put in a couple of words and you

00:31:29

get a short video so they had one of a

00:31:31

teddy bear painting a teddy bear

00:31:33

so it looks like you're going to be able

00:31:35

to

00:31:37

essentially create a whole movie by just

00:31:39

talking to a computer

00:31:41

really impressive where do you think we

00:31:43

are Freeburg in terms of

00:31:46

the compounding nature of these narrow

00:31:48

AI efforts you know obviously we saw

00:31:50

poker chess go Dolly gpt3 self-driving

00:31:55

it feels like this is all compounding at

00:31:57

a faster rate

00:31:59

or am I just you imagining that yeah

00:32:02

look I mean it's interesting when when

00:32:03

people saw the first computer playing

00:32:05

chess they said the same thing I think

00:32:07

any time that you see progress with a

00:32:09

computer that starts to mimic

00:32:11

the predictive capabilities of a human

00:32:14

it it it's uh it's impressive but I will

00:32:17

argue and I just I'll say a few words on

00:32:20

this it's I think this is part of a

00:32:22

60-year cycle that we've been going

00:32:24

through

00:32:25

um fundamentally what humans and human

00:32:28

brains do is we can sense our external

00:32:32

environment then we generate Knowledge

00:32:33

from that sensing and then our brains

00:32:36

build a model that predicts an outcome

00:32:38

and then that that predicted outcome is

00:32:40

what drives our actions and our Behavior

00:32:42

we observe the sunrise every morning

00:32:44

then we observe that it sets and you see

00:32:46

that enough times and you build a

00:32:47

predictive model from that data that's

00:32:49

been generated in your brain

00:32:51

that I predict that the sun has risen it

00:32:53

will therefore set it has said it will

00:32:55

therefore rise and I think that the

00:32:57

Computing approach is very similar it's

00:32:59

all about

00:33:00

sensing or generating data and then

00:33:02

creating a predictive model and then you

00:33:03

can drive action and initially the first

00:33:07

approach was just basic algorithms and

00:33:09

these are deterministic models that are

00:33:11

built it's a piece of code that says

00:33:13

here's an input here's an output and

00:33:15

that that model is really built by a

00:33:17

human and a human designed to design

00:33:18

that algorithmic model and said this is

00:33:20

what the uh the predictive potential of

00:33:24

the software is then there was this term

00:33:26

called data science so as data

00:33:28

generation began to proliferate meaning

00:33:30

there was far more sensors in the world

00:33:32

it was really cheap to to create Digital

00:33:34

Data from the physical world really

00:33:36

cheap to transmit it really cheap to

00:33:37

store it and really cheap to compute

00:33:39

with it data science became the hot term

00:33:41

in Silicon Valley for a while and these

00:33:43

models were not just a basic algorithm

00:33:45

written by a human but it became an

00:33:48

algorithm that was a similar

00:33:49

deterministic model

00:33:51

that had parameters and the parameters

00:33:54

were ultimately resolved by the data

00:33:56

that was being generated and so these

00:33:58

models became much more complex and much

00:34:00

more predictive finer granularities uh

00:34:02

finer range then we used this term

00:34:04

machine learning and in the data science

00:34:06

era it was still like hey there's a

00:34:09

model and you would solve it statically

00:34:12

you would get a bunch of data you would

00:34:13

statically solve for the parameters and

00:34:15

that would be your model and it would

00:34:16

run machine learning then allowed those

00:34:18

parameters to become Dynamic so the

00:34:21

model was static but generally speaking

00:34:23

the parameters

00:34:24

that drove the model became dynamic as

00:34:27

more data came into the system and they

00:34:29

were dynamically updated and then this

00:34:31

era of AI became and that's the new

00:34:33

catch word and what AI is realizing is

00:34:36

that there's so much data that rather

00:34:38

than just resolve the parameters of the

00:34:40

model you can actually resolve a model

00:34:42

itself the algorithm can be written by

00:34:45

the data the algorithm can be written by

00:34:46

the software and so with a with AI

00:34:49

example so poker plug an Adaptive model

00:34:52

so people uh so you're playing poker and

00:34:55

the software begins to recognize

00:34:56

behavior and it builds a predictive

00:34:58

model that says here's how you're

00:34:59

playing and then over time it actually

00:35:01

changes not just the parameters of the

00:35:03

model but the model itself the algorithm

00:35:05

itself and so Ai and then it eventually

00:35:07

gets to a point where the algorithm is

00:35:09

so much more complex that a human would

00:35:11

have never written it and suddenly the

00:35:13

AI has built its own intelligence its

00:35:15

own ability to be predictive in a way

00:35:16

that a human algorithmic programmer

00:35:18

would have never done and and this is

00:35:21

all driven by statistics so none of this

00:35:23

is new science person say there's new

00:35:25

techniques that all on their underlying

00:35:28

use statistics as their basis and then

00:35:30

there's these techniques that allow us

00:35:31

to build these new systems of model

00:35:33

development like neural Nets and so on

00:35:35

and those statistics build those neural

00:35:37

Nets they they solve those parameters

00:35:38

and so on but fundamentally there is an

00:35:41

um geometric increase in data and a

00:35:44

geometric decline in the cost to

00:35:46

generate data from sensors because the

00:35:48

cost of sensors is coming down with

00:35:49

Moore's Law transmit that data because

00:35:52

the cost of moving data has come down

00:35:53

with Broadband Communications the cost

00:35:55

of storing data because the cost of dram

00:35:57

and and solid-state hard drives has come

00:36:00

down with Moore's Law and now the

00:36:02

ability to actually have enough data to

00:36:04

do this AI driven where people are

00:36:06

calling AI but it really is the same

00:36:07

it's part of the spectrum of things that

00:36:09

have been going on for 60 years to

00:36:11

actually drive predictions in the in the

00:36:13

world is really being realized in a

00:36:15

bunch of areas that we would have

00:36:16

historically been really challenged and

00:36:18

surprised to see and so my argument is

00:36:21

at this point Big Data played a big role

00:36:23

yeah yeah we've over the last decade

00:36:25

we've reached this Tipping Point in

00:36:27

terms of data generation storage and

00:36:28

computation that's allowed these

00:36:30

statistical models to resolve

00:36:32

dynamically and as a result they are far

00:36:35

more predictive and as a result we see

00:36:37

far more human-like behavior in the

00:36:39

predictive systems both physics both

00:36:41

those that are you know like a like a

00:36:43

robot is the same as one that existed 20

00:36:45

years ago but the way that it's run is

00:36:47

using the software that is driven by

00:36:49

this Dynamic model and that data is for

00:36:52

a better answer

00:36:55

okay I have two things to say but one

00:36:57

the first one is a total non-sequitur so

00:36:59

use the term data scientist do you know

00:37:01

where the term data scientist came from

00:37:04

as classically used in Silicon Valley it

00:37:07

came from Facebook and it came from my

00:37:09

team in a critical moment this was in

00:37:11

2007 I was trying to 2008 I was trying

00:37:13

to build the growth team

00:37:15

this is the team that became very famous

00:37:17

for getting 2 billion users and you know

00:37:20

building a lot of these algorithmic

00:37:21

insights and I was trying to recruit a

00:37:25

person from Google and he was like a PhD

00:37:28

in some crazy thing like astrophysics or

00:37:30

particle physics or something and we

00:37:33

gave him an offer

00:37:34

has a data analyst because this is what

00:37:36

I needed at the time this is what I

00:37:37

thought I needed an analyst you know to

00:37:39

analyze data and he said absolutely not

00:37:43

I'm offended by the job title and I

00:37:45

remember talking to my my HR you know

00:37:47

business process partner and I asked her

00:37:49

like I don't understand what is this

00:37:51

where is this coming from and she said

00:37:52

he Fashions himself a scientist and I

00:37:55

said well then call him a data scientist

00:37:57

so we wrote in the offer for the first

00:37:59

time data scientist and at the time

00:38:01

people internally were like this is a

00:38:04

dumb title what does this mean anyways

00:38:06

we hired the guy he was a star and uh

00:38:09

and that title just took off internally

00:38:11

so Rob it's funny because parallel we

00:38:13

started climate Corp in 2006 and the

00:38:15

original the first guy I hired was a

00:38:17

buddy of mine who was a 4.0 for in

00:38:18

applied math from Cal and then everyone

00:38:20

we hired on with him we called them the

00:38:23

math team and they were all applied math

00:38:25

and statistics phds and we called them

00:38:27

the math team and it was really cool to

00:38:29

be part of the math team but then we

00:38:31

switched the team name to data scientist

00:38:33

and then it obviously created this much

00:38:35

more kind of impressive role impressive

00:38:38

title Central function to the

00:38:39

organization that was more than just a

00:38:42

math person or data analyst as I think

00:38:44

it may have been classically treated

00:38:45

because they really were building the

00:38:47

algorithms that drove the models that

00:38:49

made the product work right Peter Thiel

00:38:51

is a very funny observation not funny

00:38:53

but you know observation which is you

00:38:55

should always be wary of any science

00:38:57

that actually has science in the name

00:38:59

political science social science I guess

00:39:02

maybe data scientists you know because

00:39:04

the real Sciences don't need to qualify

00:39:05

themselves physics chemistry biology

00:39:07

anyways that's so here's what I wanted

00:39:09

to talk about with respect to AI two

00:39:12

very important observations that I think

00:39:14

is useful for people to know the first

00:39:17

one Nick if you throw it up here is just

00:39:18

a baselining of you know when we have

00:39:21

thought about intelligence and compute

00:39:23

capability we've always talked about

00:39:24

Moore's Law and Moore's Law essentially

00:39:27

this idea that there is a fixed amount

00:39:28

of time where the density of transistors

00:39:32

inside of a chip would double and

00:39:34

roughly that period for many many years

00:39:36

was around two years and it was largely

00:39:38

led by Intel and we used to equate this

00:39:41

to intelligence meaning the more density

00:39:43

there was in a chip the more things

00:39:46

could be learned and understood and we

00:39:49

used to think about that as the

00:39:50

progression of how Computing

00:39:53

intelligence would grow and eventually

00:39:55

Ai and artificial intelligence would

00:39:57

would get to mass Market

00:39:59

well what we are now at is a place where

00:40:02

many people have said Moore's law has

00:40:04

broken why it's because we cannot cram

00:40:08

any more transistors into a fixed amount

00:40:10

of area we are at the boundaries of

00:40:12

physics

00:40:14

and so people think well does that mean

00:40:16

that our ability to compute

00:40:18

will essentially come to an end and stop

00:40:20

and the answer is no and that's what's

00:40:22

demonstrated

00:40:23

on this next chart just to make it

00:40:25

simple which is that what you really see

00:40:28

is that if you think about you know

00:40:30

super computing power so the ability to

00:40:33

get to an answer that has actually

00:40:36

continued unabated and if you look at

00:40:39

this chart the reason why this is

00:40:41

possible is entirely because we've

00:40:43

shifted from CPUs to these things called

00:40:46

gpus so you may have heard companies

00:40:48

like Nvidia why is companies like Nvidia

00:40:50

done so well it's because they said they

00:40:53

raised their hand and said we can take

00:40:54

on the work

00:40:55

and by taking on the work away from a

00:40:58

traditional CPU you were able to do a

00:41:00

lot of what Freeburg said is get into

00:41:02

these very complicated models so this is

00:41:05

just an observation that I think that we

00:41:08

are continuing to compound knowledge and

00:41:11

intelligence effectively at the same

00:41:14

rate as Moore's Law and we will continue

00:41:17

to be able to do that because this makes

00:41:20

it a problem of power and a problem of

00:41:23

money so as long as you can buy enough

00:41:26

gpus from Nvidia or build your own

00:41:29

and as long as you can get access to

00:41:31

enough power to run those computers

00:41:34

there really isn't many problems you

00:41:36

can't solve and that's what's so

00:41:38

fascinating and interesting and this is

00:41:40

what companies like open AI

00:41:42

are really proving you know when they

00:41:43

raise the billion dollars what they did

00:41:46

was they attacked this problem because

00:41:48

they realize that by Shifting the

00:41:49

problem to gpus it left all these

00:41:52

amazing opportunities for them to

00:41:55

uncover and that's effectively what they

00:41:56

have the second thing that I'll say very

00:41:59

quickly is that

00:42:00

it's been really hard

00:42:02

for us as a society

00:42:04

to build intelligence

00:42:06

in a multi-modal way like our brain

00:42:09

works so think about how our brain works

00:42:10

our brain works in a multimodal way we

00:42:13

can process imagery we can process words

00:42:16

and sounds we can process all of these

00:42:19

different modes text

00:42:22

into one system and then Intuit some

00:42:26

intelligence from it and make a decision

00:42:27

right so you know we could be watching

00:42:30

this YouTube video there's going to be

00:42:31

transcription there's video voice audio

00:42:33

everything all at once

00:42:35

and we are moving to a place very

00:42:37

quickly where computers will have that

00:42:40

same ability as well today we go to very

00:42:42

specific models and kind of balkanized

00:42:45

silos correct to solve different kinds

00:42:47

of problems but those are now quickly

00:42:49

merging again because of what I just

00:42:51

said about gpus

00:42:52

so I think what's really important about

00:42:55

AI for everybody to understand is the

00:42:58

marginal cost of intelligence is going

00:43:00

to go to zero

00:43:01

and this is where I'm just going to put

00:43:03

out another prediction of my own when

00:43:06

that happens

00:43:07

it's going to be incredibly important

00:43:10

for humans to differentiate themselves

00:43:12

from computers and I think the best way

00:43:14

for humans to differentiate ourselves is

00:43:17

to be more human it's to be less compute

00:43:20

intensive it's to be more empathetic

00:43:23

it's to be more emotional a lot less

00:43:25

emotional because those differentiators

00:43:27

are very difficult for Brute Force

00:43:29

compute to solve be careful the

00:43:31

replicants on this call are getting a

00:43:33

little nervous here they're not

00:43:35

processing that that was an emotional

00:43:36

statement do not want to process that

00:43:38

one well I to your point uh during this

00:43:41

AI day

00:43:42

um they were showing in self-driving as

00:43:45

you're talking about this balkanization

00:43:46

and trying to

00:43:48

um make decisions across many different

00:43:50

uh decision trees you know they're

00:43:52

looking at Lane changes they're looking

00:43:54

at other cars and pedestrians they're

00:43:56

looking at road conditions like fog and

00:43:58

rain and then they're using all this big

00:44:01

data to your point Freeburg to run uh

00:44:04

tons of different simulations so they're

00:44:05

building like this virtual uh World on

00:44:09

Market Street and then they will throw

00:44:11

people dogs cars people about that into

00:44:15

the simulation it's such a wonderful

00:44:16

example imagine that system hears a horn

00:44:20

yeah well you hear a horn so clearly

00:44:23

there's some auditory expression of risk

00:44:26

right there's something risky

00:44:28

and now you have to scan your visual

00:44:30

field you have to probabilistically

00:44:32

decide what it could be what the evasive

00:44:35

maneuver if anything should be so that's

00:44:38

a multimodal set of intelligence that

00:44:41

today isn't really available yeah but we

00:44:44

have to get there if we're going to have

00:44:45

real full self-driving so that's a

00:44:47

perfect example Jason a real world

00:44:48

example of how hard the problem is but

00:44:50

it'll get solved because we can brute

00:44:52

force it now with with chips and with

00:44:54

compute I think that's going to be the

00:44:55

very interesting thing with the robots

00:44:57

as well is all of these decisions

00:44:59

they're making moving cars through roads

00:45:03

all of a sudden we're going to see that

00:45:04

with vetoles vertical takeoff and

00:45:06

Landing

00:45:08

you know aircraft and we're going to see

00:45:10

it with this General robot and everybody

00:45:12

wanted to ask Elon about General AI you

00:45:14

know the Terminator kind of stuff

00:45:16

and his position is I think if we solve

00:45:19

enough of these problems Friedberg it'll

00:45:20

be an emergent

00:45:22

Behavior or an emergent phenomenon I

00:45:25

guess would be a better word based on

00:45:27

each of these cities crumbling you know

00:45:29

each of these tasks getting solved by

00:45:31

groups of people you have any thoughts

00:45:33

as we wrap up here on the discussion

00:45:34

about a general Ai and the timeline for

00:45:37

that because obviously we're going to

00:45:38

solve every vertical AI problem in short

00:45:40

order I spoke about this a little bit on

00:45:43

um the ask AMA on call in on Tuesday

00:45:46

night um once sax gets it out you can

00:45:49

listen to it but I really have this

00:45:51

strong belief that the servers crashes

00:45:55

this episode drops okay yeah you guys

00:45:59

can try to download the app but it might

00:46:00

crash so just be careful so so here's

00:46:02

here's my my course that you were 10

00:46:06

times more popular than jaycal so it's

00:46:08

unexpected levels of traffic

00:46:10

well you had you did have an account

00:46:11

with 11 000 followers I mean it might

00:46:14

look like you're right we'll put you on

00:46:16

that account next time yeah please yeah

00:46:18

I'm starting from zero yeah that's fair

00:46:21

that's fair yeah look my core thesis is

00:46:23

I think humans transition from being

00:46:26

um let's call it you know passive in

00:46:29

this system on Earth to being laborers

00:46:32

and then we transition from being

00:46:34

laborers to being creators and I think

00:46:36

our next transition with AI is to

00:46:38

transition from being creators to being

00:46:40

narrators and what I mean by that is as

00:46:42

as we started to do work on Earth and

00:46:45

engineer the world around us we did

00:46:47

labor to do that we literally plowed the

00:46:49

fields we walked distances we built

00:46:52

things and over time we built machines

00:46:55

that automated a lot of that labor

00:46:57

you know everything from a plow to a

00:47:00

tractor to a caterpillar equipment to a

00:47:03

microwave that cooks for US Labor became

00:47:05

less we became less dependent on our

00:47:07

labor abilities and then we got to

00:47:09

switch our time and spend our time as

00:47:10

creators as knowledge workers and a vast

00:47:13

majority of the developed world now

00:47:15

primarily spends their time as knowledge

00:47:18

workers creating and we create stuff on

00:47:20

computers we do stuff on computers but

00:47:22

we're not doing physical labor anymore

00:47:24

as a lot of the knowledge work gets

00:47:26

supplanted by AI as it's being termed

00:47:29

now but really gets supplanted by

00:47:31

software the role of the human I think

00:47:33

transitions to being one of a narrator

00:47:35

where instead of having to create the

00:47:37

the blueprint for a house you narrate

00:47:40

the house you want and the software

00:47:42

creates the blueprint for you dictate

00:47:43

and instead of yeah and instead of

00:47:45

creating the movie and not spending 100

00:47:47

million dollars producing a movie you

00:47:49

dictate or you narrate the movie you

00:47:51

want to see and you iterate with the

00:47:52

computer and the computer renders the

00:47:54

entire film for you because those films

00:47:56

are shown digitally anyway so you can

00:47:57

have a computer render it instead of

00:47:59

creating a new piece of content you

00:48:03

narrate the content you want to

00:48:04

experience you create your own video

00:48:06

game you create your own Movie

00:48:07

experience and I think that there's a

00:48:09

whole Evolution that happens and if you

00:48:10

look Steve pinker's book Enlightenment

00:48:12

now has a great statistic a set of

00:48:14

statistics on this but the amount of

00:48:16

time that humans are spending on leisure

00:48:18

activities per week has climbed

00:48:20

extraordinarily over the past couple of

00:48:22

decades we spend more time enjoying

00:48:24

ourselves and exploring our creative

00:48:25

interests than we ever did in the in the

00:48:28

past in human history because we were

00:48:29

burdened by all the labor and all the

00:48:31

creative and knowledge work we had to do

00:48:32

and now things are much more accessible

00:48:35

to us and I think that AI allows us to

00:48:37

transition into an era that we never

00:48:39

really thought possible or realized

00:48:40

where the limits are really our

00:48:42

imagination of what we can do with the

00:48:44

world around us and the software

00:48:45

resolves to the um and automation

00:48:48

resolves to make those things possible

00:48:50

and that's making a really exciting kind

00:48:51

of vision for the future that I think AI

00:48:53

enables Star Trek had this right people

00:48:55

didn't have to work and they could

00:48:56

pursue things in the Holodeck or

00:48:58

whatever that they felt was rewarding to

00:49:01

them but speaking of jobs uh the job

00:49:04

reports for August came in we we talked

00:49:06

about this we were trimming 300 000 jobs

00:49:09

a month and we're wondering if the other

00:49:11

shoe would drop but boy did it drop 100

00:49:13

over a million jobs burned off in August

00:49:16

so without getting into the macro talk

00:49:18

it does feel like what the FED is doing

00:49:20

and companies

00:49:22

doing hiring freezes and cuts is finally

00:49:25

finally having an impact if we start

00:49:26

losing a million as we predicted could

00:49:28

happen here on the show

00:49:31

people might actually go back to work

00:49:33

and lift and Uber are reporting that the

00:49:36

driver shortages are over they no longer

00:49:38

have to pay people spiffs and stuff like

00:49:40

that to get people to come back to work

00:49:41

so at least here in America feels like

00:49:43

we're turning a corner do we want to go

00:49:45

can we let's talk about the marijuana

00:49:49

yeah yeah I was about to say we got a

00:49:51

couple of things we really want to get

00:49:52

to here uh Ukraine section 230 and then

00:49:55

this breaking news uh we'll pull it up

00:49:57

here on the screen

00:49:58

while we're recording the show President

00:50:00

Biden says and I'm just going to quote

00:50:02

here

00:50:04

first

00:50:06

I'm pardoning all prior Federal offenses

00:50:08

of simple marijuana possession there are

00:50:10

thousands of people who are were

00:50:12

previously convicted of simple

00:50:13

possession who may be denied employment

00:50:15

housing or educational opportunities

00:50:16

there's not my pardon will remove this

00:50:18

burden that's big news second I'm

00:50:20

calling on Governors

00:50:21

to part in simple State marijuana

00:50:24

possession offenses just as no one

00:50:26

should be in a federal prison solely for

00:50:28

possessing marijuana nobody should be in

00:50:29

a local jail or state prison for that

00:50:31

reason either finally this is happening

00:50:33

third and this is an important one we

00:50:36

classify the marijuana at the same level

00:50:38

as heroin and even and more serious than

00:50:40

fentanyl makes no sense I'm asking

00:50:43

secretary bakara and the Attorney

00:50:46

General to initiate the process of

00:50:48

reviewing how marijuana is scheduled

00:50:49

under federal law

00:50:51

I'd also like to note that as federal

00:50:53

and state Regulators change we still

00:50:56

need important limitations on

00:50:57

trafficking marketing and under eight

00:50:58

hours of marijuana

00:51:00

thoughts on this breaking news is this

00:51:03

giving the the timing on this is kind of

00:51:06

midterm

00:51:07

related it just seems is this is this I

00:51:10

guess is this a politically popular

00:51:11

decision to do

00:51:13

I think so I mean look I support it so

00:51:16

buying finally did something I like

00:51:18

great I mean I thought that we should

00:51:21

decriminalize marijuana for a long time

00:51:24

or specifically you know I agree with

00:51:27

this idea of descheduling it it does not

00:51:29

make sense to treat marijuana the same

00:51:31

as heroin as a schedule one narcotic

00:51:34

just doesn't make any sense it should be

00:51:35

regulated separately and differently

00:51:38

obviously you want to keep it out of the

00:51:40

hands of minors but no one should be

00:51:42

going to jail I think for simple

00:51:43

possession so I do agree with this and I

00:51:45

think the thing they need to do I don't

00:51:48

see it mentioned here is they should

00:51:49

pass a federal law that would allow for

00:51:53

the normalization of let's call it legal

00:51:57

legal

00:51:58

um you know cannabis companies so so

00:52:01

companies that are allowed to operate

00:52:03

under state laws like in California

00:52:06

should have access to the banking system

00:52:08

should have access to payment rails

00:52:09

because right now the reason why the

00:52:12

legal cannabis industry isn't working at

00:52:14

all in California is because they can't

00:52:16

bank they can't take payments so so it's

00:52:19

this weird all-cash business that makes

00:52:20

no sense so so listen if we're not going

00:52:23

to criminalize it as a drug like heroin

00:52:25

if we're going to allow states to make

00:52:28

it legal then allow it to be a more

00:52:31

normal business where the state can tax

00:52:33

it and it can operate in a more above

00:52:36

board way

00:52:38

is what you're saying the federal medic

00:52:40

I think it could still be regulated on a

00:52:42

state-by-state basis but I think you

00:52:44

need the feds to bless the idea that

00:52:47

Banks and payment companies can take on

00:52:49

those clients which states have already

00:52:52

said are legally operating companies and

00:52:54

right now they can't and it's a huge gap

00:52:57

in the laws so maybe that's the one

00:52:58

thing I would add to this but I don't

00:53:00

have any complaints about this right now

00:53:01

based on what we know from this tweet

00:53:03

storm and I would say this by the way

00:53:06

was an about face this was an about

00:53:07

faced by Biden yeah do you know what the

00:53:09

polling data says I mean is is there I'm

00:53:12

assuming there's big support in kind of

00:53:14

the independence and the middle

00:53:16

uh for this it was 70 at one point yeah

00:53:19

yeah

00:53:20

so so look this to me this is the kind

00:53:22

of thing that Biden should be doing with

00:53:24

the 50 50 Senate finding these sorts of

00:53:26

bipartisan compromises right

00:53:29

so yeah I look this is good news for us

00:53:31

why hasn't this happened in the past

00:53:33

like what's been the political reason

00:53:35

that other presidents Obama even

00:53:40

didn't that that have there was a

00:53:42

similar ideology like why why but why

00:53:44

does anyone know why this hasn't been

00:53:45

done in the past there was rumors he was

00:53:47

going to do in the second term

00:53:49

they just didn't have the political

00:53:50

Capital why to do it why I don't I don't

00:53:53

well it's hard ones doesn't require yeah

00:53:55

the pardon doesn't require political

00:53:57

capital I think it's probably the

00:53:58

perception that this is soft on crime in

00:54:01

some way or there wasn't enough

00:54:03

broad-based support as David said I mean

00:54:05

I think the the United States population

00:54:07

has moved pretty meaningfully in the

00:54:09

last 20 years look at the chart here

00:54:12

um you know we were talking about 2000

00:54:14

it was only 31 percent uh and then you

00:54:17

look at 2018 it's up at 60 plus percent

00:54:20

so when people saw the states doing it

00:54:22

and they saw absolutely no problem you

00:54:25

know in every state and I think what

00:54:26

people will see next I think that's a

00:54:28

Gallup poll that's a Gallup pollution

00:54:29

yeah yeah so I mean it's increased

00:54:31

dramatically MDMA psilocybum and some of

00:54:34

these other plant-based medicines

00:54:35

Ayahuasca are next and they're doing

00:54:37

studies on them now I don't want to take

00:54:39

away from how important this is for uh

00:54:41

all the people for whom this will

00:54:43

positively impact I just want to talk

00:54:45

about the schedule change for marijuana

00:54:47

as a parent one of the things that I'm

00:54:50

really really concerned about is that

00:54:52

through this process of legalization

00:54:55

getting access to marijuana has frankly

00:54:57

become too easy particularly for kids

00:55:00

at the same time I saw a lot of really

00:55:03

alarming evidence that the the intensity

00:55:06

of these marijuana-based products have

00:55:09

gone you know I think it's like five or

00:55:11

six times more intense than I don't know

00:55:13

50 or 100 tomorrow much higher right so

00:55:16

so it's no longer you know this kind of

00:55:19

like you know Do no harm drug that it

00:55:22

was 20 years ago this is this could be

00:55:24

actually David the way that it's

00:55:27

productized today as bad as some of

00:55:30

these other

00:55:31

you know uh narcotics so

00:55:34

in June of this year

00:55:36

the Biden Administration basically made

00:55:38

this press release that said the FDA is

00:55:41

going to come out with regulations that

00:55:43

would cap the amount of nicotine in

00:55:45

cigarettes and I think that was a really

00:55:47

smart move because it basically set the

00:55:49

stage to taper nicotine out of uh out of

00:55:53

cigarettes which would essentially you

00:55:55

know decapitate it as a an addictive

00:55:58

product and I think by

00:56:01

thinking about how it's how it's dealt

00:56:03

with what I really hope the

00:56:05

administration does is it empowers the

00:56:08

FDA if you're going to legalize it you

00:56:11

need to have expectations around what

00:56:14

the intensity of these drugs are because

00:56:16

if you're delivering drugs OTC and now

00:56:18

any kid can go in at 18 years old and

00:56:20

buy them which means that 18 year olds

00:56:23

are going to buy them for 16 year olds

00:56:24

16 year olds are going to get fake IDs

00:56:26

to buy them for themselves you need to

00:56:28

do a better job so the parents you're

00:56:30

helping parents do our job here's what

00:56:32

you need

00:56:33

one like alcohol

00:56:36

if alcohol is 21 then of course yeah

00:56:39

fine but even alcohol David you know

00:56:40

that there are there are we know what

00:56:42

the intensity of these are their labels

00:56:43

and there's warnings and you know the

00:56:45

difference between they're they're

00:56:46

getting wine versus hard alcohol but let

00:56:49

me just give you some statistics here

00:56:50

chamoth if you think about the the

00:56:52

Cannabis in the 90s uh and prior to that

00:56:55

uh they've been very you've been a ton

00:56:57

of studies on this in Colorado it was uh

00:56:59

the THC content was less than two

00:57:01

percent

00:57:02

and then in 2017

00:57:04

we were talking about you know things

00:57:06

going up to uh 17 to 28 for a specific

00:57:11

strain so they have been building

00:57:12

strains like Girl Scout cookies Etc that

00:57:15

have just increased and increased and

00:57:16

then there are things like shards and

00:57:18

obviously Edibles you can create

00:57:20

whatever intensity you want so you have

00:57:22

this incredible there you know

00:57:24

variation you could have an edible

00:57:26

that's you know got one milligram of THC

00:57:29

one that has a hundred or you could have

00:57:31

a pack of Edibles and you see this

00:57:33

happen in the news all the time some kid

00:57:34

gets their parents pack or somebody

00:57:36

gives one and the kids don't know um and

00:57:38

this dabbing phenomenon combined with

00:57:40

dabbing is like the shards like this

00:57:42

really intense uh stuff

00:57:45

combined with the Edibles is really the

00:57:46

issue and the labeling of them so you

00:57:49

got to be incredibly careful with this

00:57:50

it's not good for kids it screws up

00:57:52

their brains and so

00:57:53

yeah be very careful I have a I have a

00:57:56

zero tolerance policy on this stuff I

00:57:57

don't care if it's legal illegal like I

00:57:59

don't want my kids touching any of this

00:58:00

stuff until it's not for kids obviously

00:58:02

yeah but we also should not be over

00:58:03

there until they're 35 or 40 and even

00:58:05

then I hope they never do it but but I

00:58:07

need some help

00:58:09

and I'm not sure I'm the only parent

00:58:10

that's asking you can't have this stuff

00:58:12

be available effectively sold like in a

00:58:14

convenience store no no that's not going

00:58:17

to happen where there isn't even

00:58:18

labeling at least like cigarettes are

00:58:19

labeled it's very clear how bad this

00:58:22

stuff is for you oh do you guys have any

00:58:23

feedback on the job report or anything

00:58:25

they're all going away when when the

00:58:26

when the AI wins

00:58:28

well that's why I brought it up it's

00:58:30

like we're now going to see a potential

00:58:32

you know a situation where Jobs go away

00:58:35

and a lot of the stuff like even

00:58:36

developers right don't you think

00:58:37

Freiburg developers are going to start

00:58:39

development tasks

00:58:42

everyone assumes a static lump of work I

00:58:45

think what happens particularly in

00:58:47

things like developer tools is the

00:58:49

developer can do so much more and then

00:58:52

we generate so much more output and so

00:58:54

the overall productivity goes up not

00:58:55

down

00:58:56

um so it's pretty exciting as these and

00:58:59

remember like like we were talking on

00:59:01

the AMA the other night Adobe Photoshop

00:59:03

was a tool for photographers so you

00:59:05

didn't have to take the perfect

00:59:06

photograph and then print it you could

00:59:08

you know you could use the software to

00:59:10

improve the quality of your photograph

00:59:11

and I think that that's what we see

00:59:13

happening with all software

00:59:15

um in the creative process is it helps

00:59:17

people do more than they realized they

00:59:18

could do before and that's pretty

00:59:20

powerful and it opens up all these new

00:59:21

avenues of interest and things we're not

00:59:23

even imagining today all right so scotus

00:59:25

is going to hear two uh cases for

00:59:27

Section 230

00:59:28

the family of nohima Gonzalez a 23 year

00:59:31

old American college student who was

00:59:33

killed in an Isis terrorist attack in

00:59:35

Paris back in 2015. you remember those

00:59:37

horrible attacks is claiming that

00:59:39

YouTube helped and aided and abetted

00:59:41

Isis uh the family's argument is

00:59:43

YouTube's algorithm was recommending

00:59:46

videos that make it that makes it a

00:59:48

publisher of content as you know it's

00:59:49

section 230 common carrier now if you

00:59:52

make editorial decisions if you promote

00:59:53

certain content you lose your 230

00:59:55

protections uh in court papers filed in

00:59:58

2016 they said the company quote

01:00:00

knowingly permitted Isis to post on

01:00:02

YouTube hundreds of radicalizing videos

01:00:04

inciting violence which helped the group

01:00:06

recruit including some who were actually

01:00:09

involved in the terrorist attack so they

01:00:10

have made that connection well look

01:00:12

let's let's be honest we can we can we

01:00:13

can put a pin in this thing because I

01:00:15

think it would be shocking to me if this

01:00:18

current scotus

01:00:19

uh all of a sudden founded in the

01:00:22

cockles of their heart to protect big

01:00:23

Tech I mean they've dismantled

01:00:27

um a lot of other stuff that I think is

01:00:31

a lot more controversial than this

01:00:34

um and so you know we've we've basically

01:00:37

looked at gun laws we've looked at

01:00:39

affirmative action we've looked at

01:00:41

abortion rights sorry well I mean I

01:00:44

think as as we've said I think we all

01:00:46

know where that dye is unfortunately

01:00:48

going to get cast

01:00:49

um so to me it just seems like this

01:00:52

could be an interesting case where it's

01:00:53

actually nine zero

01:00:55

in favor for complete for completely

01:00:58

different sets of reasons I mean if you

01:00:59

think of the liberal left part of the

01:01:01

Court they have their own reasons for

01:01:03

saying that there aren't 230 protections

01:01:04

for big Tech and if you look at the the

01:01:06

far right or the right-leaning Parts

01:01:09

members of this of scotus they have they

01:01:11

have another set of different do you

01:01:12

think you're gonna make a political

01:01:13

decision not illegal no but even even in

01:01:15

their politics they actually end up in

01:01:17

the same place they

01:01:19

have protections but for different

01:01:20

reasons

01:01:21

so there there's a reasonable outcome

01:01:23

here where you know uh Roberts is going

01:01:26

to have a really interesting time trying

01:01:27

to pick who writes the majority opinion

01:01:28

there was a related case in the fifth

01:01:30

circuit in Texas where do you guys see

01:01:33

this fist circuit decision where

01:01:36

Texas passed a law imposing common

01:01:39

carrier restrictions on social media

01:01:41

companies the idea being that social

01:01:44

media companies need to operate like

01:01:45

phone companies and they can't just

01:01:47

arbitrarily deny you service or deny you

01:01:49

access to the platform and the argument

01:01:53

why previously that had been viewed

01:01:56

actually is unconstitutional was this

01:01:58

idea of compelled speech that you can't

01:02:00

compel a corporation to support speech

01:02:03

that they don't want to because that was

01:02:04

a violation of their own First Amendment

01:02:06

rights and with the first the fifth

01:02:09

circuit said is no that doesn't make any

01:02:10

sense Facebook or Twitter can still

01:02:12

advocate for whatever speech they want

01:02:14

as a corporation but as a platform they

01:02:17

if Texas requires them to not

01:02:20

discriminate against people on the base

01:02:22

of their Viewpoint then Texas has the

01:02:24

right to to impose that because that

01:02:26

doesn't it their quote was that does not

01:02:28

chill speech if anything it chills

01:02:30

censorship so what's the right legal

01:02:32

decision here in your mind putting aside

01:02:34

politics if you can for a moment but on

01:02:37

your legal hat what is the right thing

01:02:38

for society what is the right legal

01:02:40

issue around section 230 specifically in

01:02:43

the YouTube case and just generally

01:02:45

should we look at YouTube should we look

01:02:47

at a blogging platform like medium or

01:02:49

blogger Twitter should we look at those

01:02:52

as common carrier

01:02:54

and they're not responsible for what you

01:02:56

publish on them obviously they have to

01:02:58

take stuff down if it breaks their terms

01:02:59

of service Etc or if it's illegal I've

01:03:01

made the case before that I I do think

01:03:03

that common carrier requirements should

01:03:05

apply on some level of the stack to

01:03:07

protect the rights of ordinary Americans

01:03:10

to have their speech in the face of

01:03:12

these giant monopolies which could

01:03:14

otherwise de-platform them for arbitrary

01:03:16

reasons just to you know just explain

01:03:18

this a little bit so

01:03:20

historically there was always a debate

01:03:22

between so-called positive rights and

01:03:25

negative rights so where the United

01:03:28

States start off as a country was with

01:03:30

this idea of negative rights that what a

01:03:32

right meant is that you'd be protected

01:03:34

from the government taking some action

01:03:36

against you and if you look at the Bill

01:03:37

of Rights you know the original rights

01:03:39

are all about protecting the citizen

01:03:42

against intrusion on their Liberty by by

01:03:45

a state or by the federal government in

01:03:46

other words Congress shall make no law

01:03:48

it was always a restriction so the right

01:03:50

was negative it wasn't sort of

01:03:52

positively a force and then with the

01:03:54

Progressive Era you started seeing you

01:03:56

know more uh Progressive rights like for

01:03:59

example uh American citizens should have

01:04:01

the right to health care right that's

01:04:03

not protecting you from the government

01:04:04

that's saying that the government can be

01:04:06

used to give you a right that you didn't

01:04:09

otherwise have and so that was sort of

01:04:11

the big Progressive Revolution my take

01:04:13

on it is I actually think that the

01:04:15

problem we have in our society right now

01:04:17

is that free speech is only a negative

01:04:19

right it's not a positive right I think

01:04:21

it actually needs to be a positive right

01:04:23

I'm embracing a more Progressive version

01:04:26

of Rights but on behalf of sort of this

01:04:29

original negative right so and the

01:04:31

reason is because the Town Square got

01:04:33

privatized right I mean you used to be

01:04:35

able to go anywhere in this country

01:04:36

there'd be a multiplicity of town

01:04:38

squares anyone could pull out their

01:04:39

soapbox draw a crowd they could listen

01:04:41

that's not how speech occurs anymore

01:04:43

it's not on public land or public spaces

01:04:46

the way that speech political speech

01:04:48

especially occurs today is in these

01:04:50

giant social networks that are that have

01:04:52

giant Network effects and are basically

01:04:54

monopolies so if you don't protect the

01:04:57

right to free speech in a positive way

01:04:58

it no longer exists so you not only

01:05:01

believe wow that YouTube should keep it

01:05:04

section 230 you believe they YouTube

01:05:06

shouldn't be able to de-platform as a

01:05:09

private company

01:05:10

you know uh Alex Jones as but one

01:05:12

example they should have their free

01:05:14

speech rights and we should lean on that

01:05:16

side of forcing YouTube to put Alex

01:05:18

Jones or Twitter to put Trump back on

01:05:21

the platform besides your position

01:05:23

I'm not saying that the constitution

01:05:25

requires YouTube to do anything uh what

01:05:28

I'm saying is that if a state like Texas

01:05:31

or if the federal government wants to

01:05:33

pass a law saying that YouTube If you

01:05:37

are say of a certain size you're a

01:05:38

social network of a certain size you

01:05:39

have Monopoly Network effects I wouldn't

01:05:41

necessarily apply this to all the little

01:05:43

guys but for those big monopolies we

01:05:45

know who they are if the if the federal

01:05:48

government or state wanted to say that

01:05:50

they are required to be a common carrier

01:05:53

and they cannot discriminate against

01:05:54

certain viewpoints I think the

01:05:56

government should be allowed to do that

01:05:57

because it furthers a positive right

01:05:59

historically they have not been able to

01:06:02

do that because of this idea because

01:06:04

this idea of compelled speech meaning

01:06:06

that it would infringe on YouTube's

01:06:08

speech rights I don't think it would I

01:06:10

mean Google and YouTube can advocate for

01:06:11

whatever positions they want they can

01:06:13

produce whatever content they want yeah

01:06:15

but but the point that and I think

01:06:17

section 230 kind of makes this point as

01:06:18

well is that they are platforms they're

01:06:20

distribution platforms they're not

01:06:22

Publishers so if they don't once so

01:06:24

especially if they want section 230

01:06:25

protection they should not be engaging

01:06:27

in Viewpoint discrimination okay so now

01:06:29

there is a rub here wait can I just say

01:06:30

can I just say go ahead your explanation

01:06:32

David your explanation that you just

01:06:33

gave before was so excellent thank you

01:06:36

that it allows me to understand it even

01:06:39

more clearly that was really so tremoff

01:06:41

do you think the algorithm is an act of

01:06:44

editorialization yes yes yes and so then

01:06:48

should YouTube look at the end of the

01:06:50

day let me let me break down an

01:06:52

algorithm for you okay effectively it is

01:06:54

a mathematical equation of variables and

01:06:57

weights

01:06:59

an editor 50 years ago was somebody who

01:07:03

had that equation of variables and

01:07:06

weights in his or her mind

01:07:08

okay and so all we did was we translated

01:07:11

again this multimodal model that was in

01:07:14

somebody's brain

01:07:16

into a model that's mathematical that

01:07:19

sits in code you're talking about the

01:07:21

front page and the New York Times yeah

01:07:23

and I think it's a fig Leaf to say that

01:07:25

because there is not an individual

01:07:27

person who writes 0.2 in front of this

01:07:29

one variable and 0.8 in front of the

01:07:31

other

01:07:32

that all of a sudden that this isn't

01:07:34

editorial decision making is wrong we

01:07:36

need to understand the current moment in

01:07:39

which we live which is that these

01:07:41

computers are thinking actively for us

01:07:45

they're providing this you know

01:07:47

computationally intensive

01:07:50

decision making and reasoning

01:07:53

and I think it's

01:07:55

it's pretty ridiculous to assume that

01:07:57

that isn't true that's why when you go

01:07:59

to Google and you search for you know

01:08:01

Michael Jordan we know what the right

01:08:04

Michael Jordan is because it's reasoned

01:08:06

there is an algorithm that is doing that

01:08:09

it's making an editorial decision around

01:08:11

what the right answer is they have

01:08:12

deemed it to be right and that is just

01:08:15

true and so I think we need to

01:08:16

acknowledge that because I think it

01:08:18

allows us at least to be in a position

01:08:20

to rewrite these laws through the lens

01:08:23

of the 21st century

01:08:25

we need to update our understanding for

01:08:28

how the world works today and you know

01:08:30

jamaat there's such an easy way to do

01:08:32

this if you're Tick Tock if you're

01:08:34

YouTube if you want section 230 if you

01:08:36

want to have common carrier and not be

01:08:38

responsible if it's there when a user

01:08:40

signs up it should give them the option

01:08:42

would you like to turn on an algorithm

01:08:44

here are a series of algorithms which

01:08:46

you could turn on you could bring your

01:08:48

own algorithm you could write your own

01:08:50

algorithm with a bunch of Sliders or

01:08:52

here are ones that other users and

01:08:54

services provide like like an App Store

01:08:55

so YouTube moth could pick one for your

01:08:58

family your kids that would be I want

01:08:59

one that's leaning towards education and

01:09:02

takes out conspiracy theories takes out

01:09:03

cannabis use takes out this one it's a

01:09:06

wonderful what you're saying is so

01:09:07

wonderful because for example like you

01:09:08

know this organization Common Sense

01:09:10

Media yes I love that website every time

01:09:12

I put in a movie I put Common Sense

01:09:14

Media decide if we should watch it or

01:09:16

like an I use it a lot for apps because

01:09:18

they're pretty good at just telling you

01:09:19

which which apps are reasonable and

01:09:21

unreasonable but you know if Common

01:09:23

Sense Media could raise a little bit

01:09:25

more money and and create an algorithm

01:09:26

that would help filter

01:09:28

stories in Tick Tock for my kids I'd be

01:09:32

more likely to give my kids tick tock

01:09:33

when they turn 14. right now I know that

01:09:36

they're going to sneak it by going to

01:09:37

YouTube and looking at YouTube shorts

01:09:39

and all these other things because I

01:09:41

cannot control that algorithm and it

01:09:43

does worry me what kind of content that

01:09:46

they're getting access to and you could

01:09:48

do this by the way chamath on the

01:09:49

operating system level or on the router

01:09:51

level in your house you could say I want

01:09:53

the common sense algorithm I will pay 25

01:09:55

a month a hundred dollars a year

01:09:59

and then any IP that goes through it

01:10:01

would be programmed properly I want less

01:10:03

violence I want less sex you know

01:10:05

whatever I think we are as a society

01:10:07

sophisticated enough now yes um to have

01:10:10

these controls and so I think we need

01:10:12

them and so I think we do need to have

01:10:15

the right observation of the current

01:10:18

state of play Friedberg

01:10:21

where do you sit on this do you think

01:10:22

the algorithm should be I don't I don't

01:10:24

I don't know right out of 230. yeah I I

01:10:27

don't fully agree with Saks on

01:10:30

um the monopolistic assumption I I think

01:10:33

that there are I think there are other

01:10:35

places to access content and I think

01:10:37

that there is still a free market to

01:10:39

compete

01:10:40

and it is possible to compete I think

01:10:43

that we saw this happen with Tick Tock

01:10:44

we saw it happen with Instagram we saw

01:10:46

it happen with YouTube uh competing

01:10:49

against Google video and Microsoft video

01:10:51

prior to that there has been a very

01:10:53

significant battle for the attention of

01:10:57

kind of being the next gen of media

01:10:59

businesses and we have seen Spotify

01:11:00

compete and we're seeing Spotify

01:11:01

continue to be challenged by emerging

01:11:04

competitors

01:11:05

so I don't buy the assumption that these

01:11:09

are built-in monopolies and therefore it

01:11:11

allows

01:11:12

some regulatory process to come in and

01:11:15

say hey Free Speech needs to be actively

01:11:17

enforced because they're monopolies this

01:11:18

isn't like when utilities laid power

01:11:21

lines and Sewer lines and and trains

01:11:24

across the country and they had a

01:11:26

physical Monopoly on being able to

01:11:28

access and move goods and services the

01:11:30

internet is still thank God knock on

01:11:32

wood open and the ability for anyone to

01:11:34

build a competing service is still

01:11:36

possible and there is a lot of money

01:11:38

that would love to disrupt these

01:11:40

businesses that is actively doing it and

01:11:42

I think every day look at how big Tick

01:11:44

Tock has gotten it is bigger than

01:11:45

YouTube almost or will be soon

01:11:48

and there is a competition that happens

01:11:50

and because of that competition I think

01:11:52

that the the market will ultimately

01:11:54

choose where they want to get their

01:11:56

content from and how they want to

01:11:57

consume it and I don't think that the

01:11:58

government should play a role Zach's

01:12:00

rebuttal to that you buy that well so

01:12:02

not all these companies are monopolies

01:12:05

but I think they act in a monopolistic

01:12:07

way with respect to restricting Free

01:12:09

Speech which is they act as a cartel

01:12:11

they all share like best practices with

01:12:13

each other on how to restrict speech and

01:12:16

we saw the The Watershed here was

01:12:18

remember when Trump was thrown off first

01:12:20

Twitter made the decision you know Jack

01:12:22

I don't even know if it was Jack but

01:12:24

basically the company Jack said it

01:12:26

wasn't him actually he said it was the

01:12:27

woman who was running it specifically

01:12:29

that's it for that yeah yeah Jack

01:12:31

actually said it was a mistake but any

01:12:32

event Twitter did it first and then all

01:12:34

the other companies followed suit I mean

01:12:36

even like Pinterest and OCTA and

01:12:39

Snapchat like officially YouTube

01:12:42

everybody yeah but Trump was actually on

01:12:44

Facebook he wasn't on all these other

01:12:45

companies they still threw him off so

01:12:47

they all copy each other and Jack

01:12:49

actually said that in his comments where

01:12:51

he said it was a mistake he said he

01:12:53

didn't realize the way in which

01:12:55

Twitter's action would actually Cascade

01:12:58

he said that he thought originally that

01:13:01

the action was okay because it was just

01:13:03

Twitter deciding to take away Trump's

01:13:05

right to free speech but he could still

01:13:07

go to all these other companies and then

01:13:08

all these other companies basically you

01:13:10

know they are all subject to the same

01:13:13

political forces the the leadership of

01:13:15

these companies are all sort of they all

01:13:17

drink from the same monocultural found

01:13:19

they all have the same political biases

01:13:21

the polls show this so the problem of

01:13:23

Freeburg is yeah I agree a bunch of

01:13:24

these companies aren't quite monopolies

01:13:26

but they all act the same way but I

01:13:28

agree with you I'm a pretty Collective

01:13:30

effect is of a speech cartel so the

01:13:33

question is how do you protect the

01:13:34

rights of Americans to free speech in

01:13:37

the face of a speech cartel that wants

01:13:39

to basically block them go ahead

01:13:40

Freeburg respond here's my argument my

01:13:42

argument is that these are not public

01:13:43

service providers they're private

01:13:45

service providers and the market is

01:13:47

telling them what to do the market is

01:13:49

saying and I think I don't think so I

01:13:51

think that the pressure that was felt by

01:13:53

these folks was that so many consumers

01:13:55

were pissed off that they were letting

01:13:57

Trump rail on or they were pissed off

01:13:58

about Jam 6 or pissed off about whatever

01:14:01

whatever the current fat is the trend is

01:14:04

they respond to the market and they say

01:14:06

you know what this has crossed the line

01:14:08

and this was the case on public

01:14:09

television when nudity came out and

01:14:11

they're like okay you know what we need

01:14:13

to take that off the TV we need to

01:14:14

because the market is telling us they're

01:14:16

going to boycott us and I think that

01:14:18

there's a market pressure here that

01:14:19

we're ignoring that is actually pretty

01:14:21

pretty relevant that as a private

01:14:23

service provider if they're going to

01:14:24

lose half Their audience because people

01:14:26

are pissed about one or two pieces of

01:14:28

content showing up that they're acting

01:14:30

in the best interest of their

01:14:32

shareholders and in the best interest of

01:14:33

their platform they're not acting as a

01:14:35

public service look I love Market forces

01:14:37

as much as the next libertarian but I

01:14:40

just think that fundamentally that's

01:14:42

just not what's going on here this has

01:14:43

nothing to do with Market forces has

01:14:44

everything to do with political forces

01:14:46

that's what's driving this look do you

01:14:48

think the average consumer the average

01:14:50

user of PayPal is demanding that they

01:14:53

engage in all these restrictive policies

01:14:55

throwing off all these accounts who have

01:14:57

the wrong viewpoints no that's nothing

01:14:58

to do with it it has to do with the

01:15:00

vocal mind

01:15:04

who work at these companies and create

01:15:07

pressure from below it's also the you

01:15:09

know the the people from outside the

01:15:10

actors who create these boycott

01:15:12

campaigns and pressure from outside and

01:15:14

then it's basically people on Capitol

01:15:16

Hill who have the same ideology who

01:15:18

basically create threats from above so

01:15:20

these companies are under enormous

01:15:21

pressure from above below and sideways

01:15:24

that and it's 100 political hold on it's

01:15:26

not it's not about maximizing profits I

01:15:29

think it's about maximizing you know

01:15:32

political outcomes yeah I don't know

01:15:33

that is that is what the American people

01:15:35

need to be protected from now I will I

01:15:37

will add one Nuance to my theory though

01:15:40

which is

01:15:41

I'm not sure what level of the stack we

01:15:44

should declare to be common carrier so

01:15:46

in other words you may be right actually

01:15:49

that at the level of YouTube or Twitter

01:15:52

or Facebook maybe we shouldn't make them

01:15:54

commentary and I'll tell you why because

01:15:56

just to take the other side of the

01:15:57

argument for a second which is you know

01:15:59

if you don't because those companies do

01:16:02

have legitimate reasons to take down

01:16:04

some content I don't like the way they

01:16:06

do it but I do not want to see bots on

01:16:08

there I do not want to see fake accounts

01:16:10

and I actually don't want to see like

01:16:12

truly hateful speech or harassment and

01:16:15

the problem is I do worry that if you

01:16:18

subject them to common carrier they

01:16:19

won't actually be able to engage in

01:16:21

let's say legitimate curation of their

01:16:24

social networks yeah right however so so

01:16:27

there's a real debate to be had there

01:16:28

and it's going to be messy but I think

01:16:31

there's one level of the stack below

01:16:32

that which is at the level of pipes like

01:16:34

in AWS like a cloud flare like a PayPal

01:16:37

like the the isps like the banks they

01:16:40

are not doing any content moderation or

01:16:43

they have no legitimate reason to be

01:16:44

doing content moderation none of those

01:16:45

companies should be able allow to engage

01:16:47

in Viewpoint discrimination we have a

01:16:48

problem right now where American

01:16:50

citizens are being denied access to

01:16:52

payment rails into the banking system

01:16:54

you're saying because of their view AWS

01:16:56

shouldn't be able to deny service to the

01:16:58

Ku Klux Klan or some hate speech group I

01:17:00

think that they should be under the same

01:17:02

requirements the phone companies under

01:17:05

okay

01:17:08

you know the question is like look I

01:17:10

could frame the same question to you

01:17:12

should you know something such a

01:17:14

horrible group should such and such

01:17:15

horrible group be able to get a phone a

01:17:17

phone account right yeah no no and you'd

01:17:19

say no they shouldn't get anything but

01:17:20

they have that right that has been

01:17:22

litigated and that's been pretty much

01:17:24

protected by the Supreme Court you know

01:17:26

even if it's a government-conferred

01:17:28

monopoly the Supreme Court has said okay

01:17:30

listen like it's not violating one's

01:17:32

constitutional right for example if your

01:17:34

water bill gets terminated without you

01:17:36

getting due process

01:17:38

and the the inverse is also true so

01:17:41

for what whether we like it or not that

01:17:43

Jason that issue has been litigated I

01:17:45

think

01:17:47

I think I think for me again just like

01:17:49

practically speaking for the functioning

01:17:52

of Civil Society I think it's very

01:17:54

important for us

01:17:55

to now introduce this idea of

01:17:57

algorithmic choice

01:17:59

and I don't think that that will happen

01:18:01

in the absence of us rewriting section

01:18:04

230 in a more intelligent way I don't

01:18:06

know I don't know whether this specific

01:18:08

case

01:18:10

create an upstanding for us to do all of

01:18:12

that

01:18:14

but I think it's an important thing that

01:18:17

we have to revisit as a society because

01:18:19

Jason what you described

01:18:21

as having a breadth of algorithmic

01:18:23

choices over time where there are

01:18:25

purveyors and sellers could you imagine

01:18:27

that's not a job or a company that the

01:18:29

four of us would ever have imagined

01:18:31

could be possible five years ago but

01:18:33

maybe there should be an economy of

01:18:35

algorithms and there are these really

01:18:36

great algorithms

01:18:38

that one would want to pay a

01:18:40

subscription for because One Believes In

01:18:42

the quality of what it gives you

01:18:44

we should have that choice and I think

01:18:46

it's an important set of choices that

01:18:47

will allow actually YouTube as an

01:18:50

example to operate more safely as a

01:18:52

platform because it can say listen I've

01:18:54

created this set of abstractions you can

01:18:56

plug in all sorts of algorithms there's

01:18:58

a default algorithm that works but then

01:19:00

there's a Marketplace of algorithms just

01:19:02

like there's a Marketplace of ideas I

01:19:04

don't discriminate and let people choose

01:19:06

this is the key thing with this model

01:19:08

like if if it was on a blockchain if all

01:19:11

the videos all the video content was

01:19:12

uploaded to a public blockchain and then

01:19:15

distributed on distributed computing

01:19:16

system then your ability to search and

01:19:19

use that media would be a function of a

01:19:22

service provider you're willing to pay

01:19:23

for that provides the best service

01:19:24

experience and by the way this is also

01:19:26

why I think over time to sax to to kind

01:19:29

of sax and I are both arguing both sides

01:19:31

a little bit but I think that what will

01:19:33

happen

01:19:34

I don't think that the government should

01:19:35

come in and regulate these guys and tell

01:19:37

them that they can't take stuff down and

01:19:39

whatnot I really don't like the

01:19:40

precedent it sets period I also think

01:19:43

that it's a terrible idea for YouTube

01:19:45

and Twitter to take stuff down

01:19:48

um and I think that there's an

01:19:49

incredibly difficult uh balance that

01:19:52

they're gonna have to find because if

01:19:53

they do this as we're seeing right now

01:19:54

the quality of the experience for a set

01:19:57

of users declines and they will find

01:19:58

somewhere else any Market will develop

01:20:00

for something else to compete

01:20:01

effectively against them and so I that's

01:20:03

why I don't like the government

01:20:04

intervening because I want to see a

01:20:06

better product emerge when the big

01:20:08

company makes some stupid mistake and

01:20:10

does a bad job and then the market will

01:20:12

find a better outcome and it just it's

01:20:14

messy in the middle and as soon as you

01:20:16

do government intervention on these

01:20:18

things and tell them what they can and

01:20:19

can't take down

01:20:21

I really do think that over time you

01:20:23

will limit the user experience to what

01:20:24

is possible if you allow the free market

01:20:26

and this is where the the industry needs

01:20:29

to police itself if you look at the

01:20:30

movie industry with the MPAA and Indiana

01:20:33

Jones and the the Temple of Doom they

01:20:35

came out with the PG-13 rating

01:20:37

specifically for things that were a

01:20:38

little too edgy for PG this is where our

01:20:41

industry could get ahead of this they

01:20:43

could give algorithmic Choice an

01:20:45

algorithmic app store and if you look at

01:20:48

the original sin it was these lifetime

01:20:49

bands like Trump should not have been

01:20:51

given a lifetime van they should have

01:20:52

given them a one-year ban they should

01:20:54

have had a process they overreached we

01:20:57

wouldn't be in this position

01:20:59

when you talk about like having a

01:21:02

industry Consortium like the MPAA what

01:21:04

you're doing is formalizing the

01:21:05

communication that's already taking

01:21:07

place is already happening between these

01:21:08

companies and what is the result of that

01:21:10

communication they all standardize on

01:21:12

overly restrictive policies because they

01:21:13

all know there is no free the same

01:21:14

political bias no but if they did it

01:21:16

correctly it's all in the execution

01:21:18

sacks it has to be executed properly

01:21:20

like the movie industry it doesn't

01:21:21

matter you'll end up with the same

01:21:23

problem as having the government

01:21:24

intervene if you have the government

01:21:25

intervene or private body intervene any

01:21:27

sort of set standard intervention that

01:21:29

prevents the market from company I just

01:21:31

I disagree with you I think you can

01:21:33

create more competition if the

01:21:34

government says

01:21:35

um okay folks you can have the standard

01:21:37

algorithm but you need to make a a

01:21:39

simple

01:21:41

abstracted way for somebody else to

01:21:43

write some other filtering mechanism and

01:21:45

to basically you so that users can pick

01:21:46

the power users yes

01:21:48

what the mpia did was I don't know why

01:21:52

isn't that more choice because that's a

01:21:54

product that's a product company I don't

01:21:56

want to be told how to make my product

01:21:57

right if you're not on YouTube you have

01:21:59

you have an algo you're now saying that

01:22:01

there is this distinction of the algo

01:22:02

from the ux from the data and my choice

01:22:04

might be to create different content

01:22:06

libraries for example YouTube has

01:22:08

YouTube kids and it's a different

01:22:09

Content Library and it's a different

01:22:11

user interface and it's a different

01:22:12

algorithm and you're trying to create an

01:22:14

abstraction that may not necessarily be

01:22:15

natural for the evolution of the product

01:22:17

set of that company I would much rather

01:22:19

see them figure it out that's not a good

01:22:21

argument that again if you were not a

01:22:23

monopoly I would be more sympathetic but

01:22:25

because like somebody somebody's

01:22:27

feelings would get hurt a product

01:22:29

manager's feelings will get hurt inside

01:22:30

of Google feelings

01:22:32

reason to not protect free speech I

01:22:34

think you're unnaturally disrupting the

01:22:35

product Evolution and I tough luck

01:22:37

that's what that's what happens when

01:22:38

you're worth two trillion dollars when

01:22:40

you impact a billion people on the

01:22:42

planet when you start having massive

01:22:44

impact in society you have to take some

01:22:46

responsibility those companies are not

01:22:48

taking responsibility if you're not

01:22:50

super super successful if this is not

01:22:52

going to affect you so you don't have

01:22:53

nothing to worry about you'll see you'll

01:22:55

see apps offshore and you'll see Tick

01:22:57

Tock and other things compete because

01:22:58

they'll have a better product experience

01:23:00

no no nobody's going to create a new

01:23:03

Google because they're downranking one

01:23:07

to ten percent of the search results

01:23:09

agreed some accountability hold on in

01:23:12

the ideal World Companies like Google

01:23:13

and so forth would not take sides in

01:23:15

political debates to be politically

01:23:17

neutral but they're not you look at all

01:23:19

the data around the political leanings

01:23:20

the people running these companies and

01:23:22

then you look at the actual actions of

01:23:23

these companies and they have become

01:23:25

fully political and they've waded into

01:23:26

all these political debates with the

01:23:28

result that the American people's rights

01:23:30

to speech into earn have been reduced

01:23:33

you have companies like PayPal which are

01:23:35

just engaging in retaliation basically

01:23:37

Financial retaliation purely on based on

01:23:41

what political viewpoints they have why

01:23:43

it's not like face it's not like PayPal

01:23:45

needs to be in the business content

01:23:47

creation let's continue this

01:23:48

conversation

01:23:49

call in ama uh if they can get some

01:23:53

servers over that I don't know maybe so

01:23:55

you got to raise some money stacks for

01:23:56

this app and get some more service all

01:23:58

right listen for the dictator who needs

01:24:00

to hit the Lou to do a number two yes I

01:24:04

am the world's greatest moderator

01:24:06

Friedberg is the Sultan of Science and

01:24:08

David Sachs is the prince of

01:24:12

peace see you all next week on the

01:24:16

episode wait wait is this 98 or 99 no

01:24:19

it's 99 it's 99. only one episode left

01:24:21

Wayne Gretzky get it well less enjoy it

01:24:24

well less that we're wrapping it up here

01:24:25

all right we'll see you all next time

01:24:27

have a great movement bye bye

01:24:30

we'll let your winners ride

01:24:34

[Music]

01:24:38

we open source it to the fans and

01:24:41

they've just gone crazy with it

01:24:44

[Music]

01:24:47

somehow

01:24:50

[Music]

01:25:14

we need to get Mercies

01:25:19

foreign

01:25:22

[Music]

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Elon Musk's Twitter Deal Uncertainty
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Elon's Challenge with Twitter
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Twitter Shareholders' Advantage
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AI Advancements
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The Rise of Data Scientists
The term 'data scientist' emerged from a need for a more impressive title, leading to a new role in tech.
“We wrote in the offer for the first time data scientist.”
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AI and the Future of Work
As AI evolves, humans will transition from creators to narrators, shaping their experiences rather than creating them from scratch.
“I think humans transition from being creators to being narrators.”
@ 46m 23s
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Biden's Marijuana Pardon
President Biden announces pardons for federal offenses of simple marijuana possession, a significant political move.
“I'm pardoning all prior Federal offenses of simple marijuana possession.”
@ 50m 06s
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The Dangers of Cannabis for Kids
Discussing the need for better regulations around cannabis products to protect children.
“It's not good for kids; it screws up their brains.”
@ 57m 50s
October 07, 2022
The Role of Algorithms in Free Speech
Exploring how algorithms can influence free speech and the need for updated laws.
“We need to acknowledge that these computers are thinking actively for us.”
@ 01h 08m 16s
October 07, 2022
Market Forces vs. Political Forces
A discussion on whether market pressures or political ideologies drive content moderation.
“It's about maximizing political outcomes, not profits.”
@ 01h 15m 29s
October 07, 2022
Political Neutrality in Tech
Debating the need for tech companies to remain politically neutral.
“Companies like Google should not take sides in political debates.”
@ 01h 23m 13s
October 07, 2022

Episode Quotes

Key Moments

Personal Responsibility11:00
Biden's Marijuana Announcement50:06
Cannabis Regulations57:52
Zero Tolerance Policy57:56
Algorithmic Influence1:08:16
Market Pressures1:14:19
Algorithmic Choice1:18:35
Political Neutrality1:23:13

Words per Minute Over Time

Vibes Breakdown

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01:26:10

E38: Bestie brawl, Robinhood's $70M fine & S-1, Delta variant, next gen candidates & more

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01:17:38

E75: Fast shuts down, board culpability, Elon buys 9% of Twitter, deplatforming's evolution & more

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October 09, 2021

01:23:12

E50: Crypto investing deep dive, Facebook's whistleblower fallout, Chappelle's new special & more

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February 15, 2025

01:50:19

JD Vance's AI Speech, Techno-Optimists vs Doomers, Tariffs, AI Court Cases with Naval Ravikant

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November 03, 2023

01:28:38

E152: Real estate chaos, WeWork bankruptcy, Biden regulates AI, Ukraine's “Cronkite Moment” & more

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01:52:45

IPOs and SPACs are Back, Mag 7 Showdown, Zuck on Tilt, Apple's Fumble, GENIUS Act passes Senate

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01:39:26

Mag 7 sell-off, Wiz rejects Google, UBI, Kamala in, China's nuclear buildout, Sacks responds to PG

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01:38:12

E170: Tech's Vibe Shift, TikTok ban debate, Vertical AI boom, Florida bans lab-grown meat & more

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October 02, 2021

01:29:00

E49: Coinbase CEO reflects on controversial blog, state of the markets, 1000 unicorns & more

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October 16, 2021

01:33:25

E51: Supply Chain Shortages, Inflation, DeSantis, Ted Sarandos Netflix Memo, Cancel Culture, Fan Q&A

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October 24, 2025

01:23:29

NBA Gambling Scandal, Billionaire Tax, Tesla's Future, Amazon Robots, AWS Outage, Dangerous AI Bias

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02:06:34

Tariffs, Trump's Economic Endgame, Market Chaos, Bitcoin Reserve, CoreWeave IPO