Speaker 1: Today's show sponsored by Lear Capital, the precious metals leader
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Speaker 1: He's editor in chief of Breitbart News and a New
Speaker 1: York Times best selling author, and on this podcast it
Speaker 1: brings deep research, prescient analysis at.
Speaker 2: World class guests. He's Alex Marlowe and this is the
Speaker 2: Alex marlow Show. All right.
Speaker 1: I've been looking forward to this for really months. Winton
Speaker 1: Hall is here. He is our social media director at
Speaker 1: Brightbart News and author of the book Code Read, which
Speaker 1: is out now and a top and a bunch of
Speaker 1: Amazon charts at the moment, the Left, the Right, China
Speaker 1: and the race to control AI.
Speaker 3: We did a brief hit on the live radio show.
Speaker 1: Which you may have come across on the podcast feed,
Speaker 1: but we're going to you today on the book, which
Speaker 1: is really a fantastic book. It is informative, but it's accessible.
Speaker 1: This is what you need to understand, and he lays
Speaker 1: it out very clearly. If you want to know not
Speaker 1: just the future but the present, this sets you up
Speaker 1: to understand what could be the story of the century,
Speaker 1: which is the adoption of widespread AI, which has went
Speaker 1: to mentioned on the radio show earlier this week. Ninety
Speaker 1: nine percent of us are already using it. You cannot
Speaker 1: opt out. And we were at a major crossroads as
Speaker 1: a conservative movement because people, I think are rightfully freak
Speaker 1: the f out about AI. But there's a lot of
Speaker 1: opportunity and we need to embrace it in a lot
Speaker 1: of ways as well, because we cannot avoid it. And
Speaker 1: we're going to talk about everything that's in the book
Speaker 1: as least as much as we can we can get through,
Speaker 1: which might not be all of it, but there will
Speaker 1: be a lot of it on today's podcast. But the
Speaker 1: first thing you got to do is you get to
Speaker 1: go right now and buy the book.
Speaker 3: You need this book.
Speaker 1: You got to get it because this is first of fall.
Speaker 3: It's a good read.
Speaker 1: If you like science fiction, if you ever read my books,
Speaker 1: you like my books, you'll absolutely like this book. But
Speaker 1: this is information that you need and is presented in
Speaker 1: a way that is accessible, you can get.
Speaker 3: It is a it's a pleasure. It really is a pleasure. Winched.
Speaker 1: I honestly felt like I would kind of people. We
Speaker 1: say this as a compliment, but it's it did feel
Speaker 1: like a novel in some ways. And then I did
Speaker 1: feel like I was immersed in a world I wasn't
Speaker 1: totally familiar with. It did feel like, you know, I
Speaker 1: found myself, you know, leaning over to my wife and
Speaker 1: talking about AI just like spontaneously while.
Speaker 3: I was going through it. And that's that's a great sensation.
Speaker 1: I know that the point of the book is the content,
Speaker 1: but congrats, I'm putting together the book. What was the
Speaker 1: process like for you, as being a seasoned ghost writer
Speaker 1: or someone who's written many books but you haven't put
Speaker 1: your name on one in a few years.
Speaker 4: Well, my condolences to your wife for having to listen
Speaker 4: to I'm getting her prime.
Speaker 3: She's in the cancer field.
Speaker 1: She's in one of the fields that could really benefit
Speaker 1: from it.
Speaker 3: So she's it's the my field. I don't know if
Speaker 3: we're going to benefit journalism. I mean, I don't know
Speaker 3: how we're gonna do, but her field, she could thrive.
Speaker 2: Now, yeah, no, you're right. So I have.
Speaker 4: I've done twenty seven books, seven New York Times bestsellers.
Speaker 4: I've been very, very blessed in my career to work
Speaker 4: with some of the biggest and you know, greatest minds.
Speaker 4: And people and celebrities and all that. I will tell
Speaker 4: you just real candidly. This book took me to places
Speaker 4: I've never been as a writer when you really start
Speaker 4: immersing yourself deep deep.
Speaker 2: This is one of the most.
Speaker 4: Black box concepts on planet Earth, super complex, and so
Speaker 4: the writer in me is always looking for that narrative
Speaker 4: story arc.
Speaker 2: How can I tell this through a.
Speaker 4: Story lens to really pull people into the experience and
Speaker 4: not make it some dry PowerPoint presentation. On the other hand,
Speaker 4: you want to make sure that you've got that granular
Speaker 4: accuracy because you know that those details really do matter.
Speaker 4: So you're right, you know it's I always love your
Speaker 4: books because you know you.
Speaker 2: Have a huge amount of endnotes.
Speaker 4: I think I have eighty pages of endnotes and fifty endnotes,
Speaker 4: and you know you're cut from that same journalistic cloth
Speaker 4: of let's get the facts right and the rest of it.
Speaker 2: I think for me, I.
Speaker 1: Gotta say something amusing to the audience because I invented
Speaker 1: this to you offline. But I think this is really
Speaker 1: it's really fun because Wyndon is if you can already
Speaker 1: tell a specially if you're watching and not listening. He
Speaker 1: is one of the most encouraging people at Bright Part.
Speaker 1: He's got that great personality where he really wants his
Speaker 1: friends to succeed. So Wyndon has always lavish praise on
Speaker 1: me for my books, but I always felt like it
Speaker 1: was because he.
Speaker 3: Was my friend.
Speaker 1: Well now I actually sort of believe him because this book,
Speaker 1: the way it was structured and written, it really would
Speaker 1: have been the exact sort of thing I would have
Speaker 1: tried to do with this subject matter. So now I
Speaker 1: actually believe you if you say you like my books,
Speaker 1: because I feel like now our books are similar.
Speaker 2: I really do mean it, and you know I do.
Speaker 2: But we are dear friends.
Speaker 4: I would say this that this book I approached as
Speaker 4: a missional and by that I mean I didn't want
Speaker 4: to write this book. I have a great life, you know,
Speaker 4: telling memoirs of celebrities and famous people's first person accounts.
Speaker 1: I think this is as a ghostwriter, just so people
Speaker 1: a ghost they're trommling ghostwriter. Beyond working at Bright Part,
Speaker 1: rinning our social media, which is which is very impressive,
Speaker 1: but go ahead.
Speaker 4: Yes, And so as a celebrity ghost writer, I love that.
Speaker 4: But I will tell you I feel like there is
Speaker 4: such an urgency here, particularly for the conservative movement. You
Speaker 4: were so right to flag that at the beginning of
Speaker 4: this discussion.
Speaker 2: This is moving so fast, and.
Speaker 4: Part of the power grab happens in that speed, because
Speaker 4: while things are blurring by, it's very easy to put
Speaker 4: down pillars and grab land masks on these topics and
Speaker 4: these policies. Everybody needs to understand something. If you forget
Speaker 4: everything else, just understand this AI is going to become,
Speaker 4: and it's starting to become the access upon which every
Speaker 4: policy area that the conservative movement has focused on for
Speaker 4: the last half century is going to spend. I'm talking
Speaker 4: about everything from education, I'm talking about everything from jobs, economics,
Speaker 4: free market, capitalism, national security, certainly, religious freedom, faith, reason, censorship,
Speaker 4: scan and band technology. The whole playbook is getting rewritten
Speaker 4: in real time, and so what I wanted to do.
Speaker 4: Nobody had ever tried to wrap their arms around the
Speaker 4: whole of this in a chat GPT post chat GPT.
Speaker 2: World, and it took me two years.
Speaker 4: I've read so many AI books my head spend literally
Speaker 4: thousands of articles, peer review, journals, trade I'm an informational scavenger.
Speaker 4: That's part of my as a celebrity ghostwriter. I like
Speaker 4: to get every piece of information I can't absorb, that
Speaker 4: build up that title way behind the mental gate, and
Speaker 4: then unlatch and then try to tell a story in
Speaker 4: a hopefully elegant and artful way with a narrative arc.
Speaker 4: So I wanted to do that because I feel that
Speaker 4: as a movement conservative our folks a are not in
Speaker 4: the rooms where the future is being built. Yes, there
Speaker 4: are a few libertarian and right leaning people in Silicon Valley,
Speaker 4: and there are a lot of courageous people write leaning
Speaker 4: in Silicon Valley, but we're not in those rooms. Eighty
Speaker 4: five percent of all donations flow to the Democratic side
Speaker 4: out of Silicon Valley. We know what they tried to
Speaker 4: do with the Global Disinformation Index to Bright Partners. We
Speaker 4: know that they have tried to dlist, demonetize deep platform,
Speaker 4: and they even did it with the President of the
Speaker 4: United States. If they can do it, if they can
Speaker 4: muzzle the President of the United States with Google products
Speaker 4: on YouTube and Facebook, just imagine what they have planned
Speaker 4: for you and me once the toggle switch flips back
Speaker 4: from a Republican control to the other team.
Speaker 2: And so I felt compelled to get this out right away.
Speaker 1: And today you know what I want to go through
Speaker 1: in this conversation. Here, we've got a nice chunk of
Speaker 1: time to get through stuff, and we might make this
Speaker 1: a double podcast, so I haven't decided yet, so those
Speaker 1: of you are tuning in the beginning.
Speaker 3: I might make one long one or two medium length ones.
Speaker 1: But I want to go through I want to get
Speaker 1: people vocabulary so they can follow the conversation. I want
Speaker 1: to make sure that we're talking about big picture in
Speaker 1: terms of where things are going with AI where they
Speaker 1: already are. And I want to go through your things
Speaker 1: that we need to be cautious about. And then I
Speaker 1: want to go through things that people can be optimistic about,
Speaker 1: which fields are really going to benefit, and how things
Speaker 1: could get better for Americans, particularly conservative Americans. But I
Speaker 1: also want to talk about some of the various sections
Speaker 1: you talk about in the book, how ais who used
Speaker 1: for warfare, how it's going to change romantic relationships, You
Speaker 1: get into all the sex spot stuff, which is just
Speaker 1: fascinating and horrifying at the same time. I want to
Speaker 1: talk about education cheating but also how it can be
Speaker 1: used to help educate you. And then I want to
Speaker 1: talk about the singularity in the end, which is crazy
Speaker 1: where we're eventually going to just merge into a human
Speaker 1: robot hybrid, which is already in the works. I mean,
Speaker 1: Musk is trying it every day with his neuralink stuff,
Speaker 1: so he's already on that. And huge moral implications also
Speaker 1: the AI being used in religious settings, which you talk
Speaker 1: about as well in the book. So I want to
Speaker 1: get through all this stuff, but let's start with sort
Speaker 1: of big picture when what do you think is the
Speaker 1: entry point for people in the audience are not voracious
Speaker 1: consumers of AI content and they're not living and dying
Speaker 1: with every new announcement from chat, TPT or nvideo or
Speaker 1: something like that. Is the well, where do you think
Speaker 1: is the entry point for your target audience?
Speaker 3: Here?
Speaker 4: Yes, I think most of us, even if we're not
Speaker 4: part of this, we know we need to be and
Speaker 4: either for ourselves or for our children.
Speaker 2: And that's what that's what code read really is.
Speaker 4: It's trying to say, whether you're just coming to this
Speaker 4: conversation or you are following it, you're able to get
Speaker 4: a glide path. Number one, whether you may not think
Speaker 4: you care about AI politics, but AI politics cares about you.
Speaker 4: This is going to touch every single part of our life.
Speaker 4: It already is number two. It is a general purpose
Speaker 4: technology a GPT. So when we hear chat GPT, that's
Speaker 4: referring to generative pre trained transformer. A GPT in the
Speaker 4: societal sense is something like electricity or the combustion engine,
Speaker 4: or steam engine, or or any other kind of system
Speaker 4: wide change that is going to revolutionize the entire world.
Speaker 4: Sundar pinch Ey at Google says that it is more
Speaker 4: akin to fire, the invention of fire, And so when
Speaker 4: you think of something that seismic, you note's.
Speaker 2: Going to touch everything. I think.
Speaker 4: The other thing is you say you're already using AI,
Speaker 4: whether you realize it or not.
Speaker 2: Ninety nine percent of us use AI.
Speaker 4: Sixty four percent of us, though, don't realize when we're
Speaker 4: using AI, because it's baked into things like our weather
Speaker 4: apps or streaming platforms, or our GPS or a host
Speaker 4: of other algorithms. So you're already using it, you're going
Speaker 4: to And what we've got to do is understand what
Speaker 4: I like to call roses and land mines. The roses
Speaker 4: are the possibilities and the positives, and the land mines
Speaker 4: are obviously the danger and.
Speaker 2: The threat factors.
Speaker 4: So there's a lot of both and we've got to
Speaker 4: know which ones are which, and I try to lay
Speaker 4: that out very clearly in code red good.
Speaker 1: Okay, So one of the things that is another entry
Speaker 1: point that things in important to people's I think we
Speaker 1: all get if you're on board that this is going
Speaker 1: to happen. I think a lot of people are on
Speaker 1: board with that we need to beat China. Okay, So
Speaker 1: that sounds very like we could all agree on this.
Speaker 1: I think that's sort of probably ninety percent of people
Speaker 1: in America. Grows the political stripes once you acknowledge that
Speaker 1: there is an AI arms race taking place, that we
Speaker 1: need to beat China. So what do we mean by that?
Speaker 1: What does that look like? What is beating China? And
Speaker 1: where are we at in this regard as of now?
Speaker 4: Yeah, so I say we've got to beat China without
Speaker 4: becoming China when none of us want to live in
Speaker 4: a CCP of techno authoritarian surveillance state. Let me explain
Speaker 4: why we need to beat them, and I will say
Speaker 4: that there's actually more bipartisan agreement once you see why
Speaker 4: and we talk about why beyond some of the obvious things.
Speaker 4: The first reason is, whoever reaches a technological dominance in AI,
Speaker 4: whether it's US, for China is going to have supremacy
Speaker 4: in things like encryption code, hacking of missile systems, hacking
Speaker 4: of infrastructure, and all of cybersecurity, and that is going
Speaker 4: to be very very very hard to surmount whoever gets
Speaker 4: there first. Once we hit something called r SI recursive
Speaker 4: self improvement, which is a fancy way of saying it's
Speaker 4: very simple. We'll explain all the terms and I do
Speaker 4: in the book. Recursive self improvement is AI that can
Speaker 4: correct its own mistakes, improve autonomously, and constantly scale up
Speaker 4: its improvement. And so once you do that, you're on
Speaker 4: a glide path rocket and you will quickly have dominance.
Speaker 2: In whatever that area is.
Speaker 4: In this case, it's that The other reason is real basic,
Speaker 4: which is economic flourishing and the growth curve. We know
Speaker 4: that the mag seven, the Magnificent seven, which are our
Speaker 4: big seven American tech companies, the ones that we all know,
Speaker 4: Meta and Google and so forth, they constitute a third
Speaker 4: of the S and P five hundred just those seven companies,
Speaker 4: so we know the economic power and then the flip side,
Speaker 4: just to show both sides. When China released Ye's AI
Speaker 4: model Deep Seek, there are one model. It created in
Speaker 4: the largest single day market cap wipeout for Nvidia six
Speaker 4: hundred billion. That's a bee, so almost two third of
Speaker 4: a trillion dollars in one single day. So you can
Speaker 4: see this tug of war on the economic front, and
Speaker 4: you can see this tug of war as it relates
Speaker 4: to global tech supremacy that relates to defense. And that's
Speaker 4: why you're starting to see Democrats and Republicans saying no, yeah,
Speaker 4: we really do have to be China. This is this
Speaker 4: is not just type marketing to get investor cash.
Speaker 2: They're real implications.
Speaker 3: Here, right.
Speaker 1: Okay, So where are we at currently in terms of
Speaker 1: the because we just saw it. I mentioned this on
Speaker 1: the live show. I want this conversation mostly be evergreen.
Speaker 1: But there is a news item that I think in
Speaker 1: today's news that super Micro, which is this company that
Speaker 1: is just tnking right now because employees were smuggling in
Speaker 1: Vidia chips to China.
Speaker 2: What do you.
Speaker 1: China needs a lot of our stuff and we can
Speaker 1: theoretically stop them from getting some of it.
Speaker 4: The Achilles heel of China are what are called graphics
Speaker 4: processing units. You may hear people call it GPUs, and
Speaker 4: in Vidia is the world global dominant leader in GPU production.
Speaker 4: We do have other American companies, but they are the
Speaker 4: leader because they are far and away the most advanced,
Speaker 4: and the big achilles Heel for China is that they
Speaker 4: need our in Vidia GPUs and they need the most
Speaker 4: advanced ones they can get. Now, there's a big fight
Speaker 4: and has been for a while export chip control fight
Speaker 4: over should we be giving or allowing American companies like
Speaker 4: in Vidia to sell advanced chips to China. The answer
Speaker 4: is obviously no, not our most advanced at minimum.
Speaker 2: And there's been a debate.
Speaker 4: President Trump has had these export chip controls. There has
Speaker 4: been recently some discussion of one of their lower grade
Speaker 4: chips called an H two hundred in in giving an
Speaker 4: allowance for them to be able to do on that.
Speaker 4: But this whole concept is really important, and again left
Speaker 4: and right sort of agree on this. In some regards
Speaker 4: about what are called choke points, there are only a
Speaker 4: few places in the supply chain or in the industry
Speaker 4: and artificial chillnes that you can almost like taking your
Speaker 4: garden hose and just squeezing the middle so that the
Speaker 4: water can't flow through. Those choke points allow us to
Speaker 4: maintain our lead and hopefully.
Speaker 2: Accelerate our lead in that AI race.
Speaker 4: And so this one is a really important one, cutting
Speaker 4: off access to these chips, and you're starting to see,
Speaker 4: as you said, you know, all these schemes and scams
Speaker 4: to try to smuggle chips in and so forth. The
Speaker 4: head of Deep Seek, which is China's powerhouse AI. He
Speaker 4: actually and I talk about this in Code Red. I
Speaker 4: actually quote him, he said in a little noticed publication
Speaker 4: mentioned that he said, you know, my problem is not money.
Speaker 4: I can raise his capital all day. Look, my problem
Speaker 4: is access to the best chips. And that's the tell,
Speaker 4: right that they've got to have that semiconductors. Fancy your
Speaker 4: way of saying chips or GPUs AI chips. So that's
Speaker 4: the battle, and it's an important one, all right.
Speaker 1: So I think that's a good There's some vocabulary I
Speaker 1: want people to understand before we get too far into
Speaker 1: this thing that is really I think important. So some
Speaker 1: of the things that come up, So l l ms,
Speaker 1: this is a big one.
Speaker 3: Explain what l lms.
Speaker 4: Are, great yes sansor large language model l l M.
Speaker 2: And this is what you think of when you think
Speaker 2: of your.
Speaker 4: AI chat pot right, So chat GPT rock Gemini, whatever
Speaker 4: one you'd like to use.
Speaker 2: That's what an ll M.
Speaker 1: Is, right, and so what are examples of this and
Speaker 1: how are they used in as.
Speaker 4: So, an LLM is trained on a massive, massive data trove,
Speaker 4: and so you're talking about trillions of what are called tokens,
Speaker 4: which is about a three quarters of a word. So
Speaker 4: just to quickly show you, so if you and I
Speaker 4: read from birth to death without stopping, assuming the average
Speaker 4: rate of speed of of a reader and life expectancy
Speaker 4: of a human.
Speaker 2: We would read about eight billion.
Speaker 4: Words, okay, average rate of speed and how many years
Speaker 4: the average person lives in one month. An enterprise LLLM
Speaker 4: large language model CHAT an AI chatbot will be trained
Speaker 4: on eight trillion that's with a t tokens three quarters
Speaker 4: of words, So it's not exactly, but it's roughly that
Speaker 4: you can see that in balance, And that's how how
Speaker 4: massive the data sets that an LLM is trained on.
Speaker 4: And so no human it would take us forever and
Speaker 4: beyond for one an anyone person, certainly.
Speaker 2: Outside of their life expectancy.
Speaker 4: So that's how they're trained. This is all racing toward
Speaker 4: another acronym called AGI, which stands for Artificial General intelligence,
Speaker 4: and this is a theoretical construct. It has not yet
Speaker 4: been achieved, in some question if it could, but the
Speaker 4: major AI companies are racing toward AGI. Artificial general intelligence
Speaker 4: is the point at which an AI can do at
Speaker 4: equal level or slightly better any cognitive task than a
Speaker 4: human can do.
Speaker 2: The one up above that is something called.
Speaker 4: A SI, which stands for artificial super intelligence. And this
Speaker 4: is this would be the theoretical point at which an
Speaker 4: AI is far in a way beyond anything that a
Speaker 4: human mind could ever achieve or even imagine. So that's
Speaker 4: when a lot of the discussion about danger and you know,
Speaker 4: sort of apocalyptic type of discussions come in.
Speaker 3: Right exactly, So this is the age.
Speaker 1: This is where we're getting to the point where the
Speaker 1: machines are just building better and better machines on their own.
Speaker 1: So the machine learning is just so intense and powerful
Speaker 1: that the humans are just aren't even necessary to the equation.
Speaker 1: And I think that's where all the sci fi scenarios
Speaker 1: play out. And I definitely want to get there later
Speaker 1: in the conversation.
Speaker 3: Because the book is you write that it's a political.
Speaker 1: Book about AI rather than a AI book about politics.
Speaker 1: So you start from the premise of that this is
Speaker 1: designed to kind of map out a political battlefield. What
Speaker 1: do people need to know about where we're at on this?
Speaker 1: Because I been talking to the audience, I spent a
Speaker 1: couple of days in Silicon Valley earlier this week, and
Speaker 1: I got to be in the room with some of
Speaker 1: the most important CEOs in this space. Briefly, almost all
Speaker 1: the off records. It's not too much I can report,
Speaker 1: but I can tell you this that there is a
Speaker 1: openness to working with the Trump administration on this. And
Speaker 1: I don't think everyone you would think. I don't think
Speaker 1: you can narrowly cast the way we could in past
Speaker 1: iteration into the Silicon Valley as everyone is a left
Speaker 1: winger anthropic, They're gone. I mean, they're completely left wing,
Speaker 1: far left. Google, I still think the most evil company
Speaker 1: in the world, even though they've shown some willingness to
Speaker 1: work with Trump on some stuff. And I'm trying to
Speaker 1: do some reporting on that for the audience. But there's
Speaker 1: some other players in the space that are not knee
Speaker 1: jerk anti Trump necessarily and are definitely willing to play ball. Now,
Speaker 1: you guys, remember the last time Ema Joe was here,
Speaker 1: we talked only about parenting.
Speaker 3: I think it's the highest.
Speaker 1: Calling for any adult human being individual, and it starts
Speaker 1: with recognizing that as that life grows inside of you,
Speaker 1: if you're a woman, no men give birth, it's just
Speaker 1: a fact. Then that is a human life with rights
Speaker 1: and a right to exist. And one of the organizations
Speaker 1: that I think does the best job in the world
Speaker 1: making that case is Preborn. Preborn offers ultrasound services and
Speaker 1: heartbeat monitors to expected mothers who may be debating whether
Speaker 1: or not to terminate the life that grows inside of them,
Speaker 1: or whether or not to give that baby a chance
Speaker 1: at a full natural life as God intended. They're an
Speaker 1: incredible group and I really value their partnership so much.
Speaker 1: On the show they provide those ultrasounds. They each one's
Speaker 1: like twenty eight bucks, So twenty eight bucks a month
Speaker 1: can save a baby a month, two hundred and eighty
Speaker 1: dollars you can save ken babies.
Speaker 3: Some of you are really generous.
Speaker 1: Fifteen thousand dollars amazing tax deduction as well. Fifteen thousand
Speaker 1: dollars you buy a whole ultrasound machine, save babies for
Speaker 1: I don't know, all year long for a while. It
Speaker 1: is an amazing group, a group that I'm proud that
Speaker 1: I corded to the show because I believe in them
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Speaker 4: Yeah, it's Silicon Valley's culture is very interesting. So eighty
Speaker 4: five percent of all donations do flow to Democrats. You
Speaker 4: just brought up Anthropic. Since twenty twenty, Anthropic and it's
Speaker 4: in employee network have have donated two hundred million.
Speaker 2: Dollars to Democrats. Here's the reality though.
Speaker 4: Okay, they're also very pragmatic, and they have to be
Speaker 4: because of regulation. So if you and I want to
Speaker 4: make an AI data center, these are you know, twenty
Speaker 4: five football field sized campuses with enormous regulatory overlays. I've
Speaker 4: got to get Energy Department of Regulatory approvals. It's a
Speaker 4: national security threat potentially because enemy like a like in
Speaker 4: a warfare would attack these data centers to take out communication.
Speaker 4: There is no way that a massive enterprise level you know,
Speaker 4: AI company in America can do business and be completely
Speaker 4: at war with the administration over it.
Speaker 2: So Trump, at.
Speaker 4: Least for the rest of his second term, they're willing
Speaker 4: to you know, play along, you know, sort of go
Speaker 4: along to get along if they have to, but make
Speaker 4: a mistake about their default setting. As you said, some
Speaker 4: of these key players, I think they are right now
Speaker 4: willing to work with because they know.
Speaker 2: They have to.
Speaker 4: I also think they do have a genuine concern about
Speaker 4: a fusion between left and right populism starting to come
Speaker 4: together on some of these issues. And you know, the
Speaker 4: final thing, in a very serious way that I think
Speaker 4: all of us nobody wants to see is real social
Speaker 4: chaos and disruption. You know, we've already seen sort of
Speaker 4: the Luigi Mangioni phenomena where people become unhinged and take
Speaker 4: horrific actions and so forth. And I think there is
Speaker 4: some degree of a real fear of social unrest. There
Speaker 4: are a lot of AI industry folks who are very
Speaker 4: concerned that if they get blame for massive job loss
Speaker 4: or if that kind of thing comes to pass, the
Speaker 4: social unrest piece will be there too. So I think
Speaker 4: they are some of them, the more reasonable ones, able
Speaker 4: to sit down. But I don't think we should in
Speaker 4: any way be fooled. Right the pendulum swings, And so
Speaker 4: what I say in Code Redd is that if tour,
Speaker 4: if you believe that AI is like fire and it
Speaker 4: can either burn down a civilization or be used to
Speaker 4: heat a hungry personal a meal and warm them, then
Speaker 4: the torch bearers who holds that fire is going to
Speaker 4: matter enormously and we should expect massive political pendulum swings.
Speaker 4: I mean, just look at how different the tone shift
Speaker 4: was right before the election and right after Kamala Harris
Speaker 4: lost and all of the heads of the AI industry
Speaker 4: and the big tech leaders they showed up. They gave
Speaker 4: their million dollar donation to the inaugural fund, they showed
Speaker 4: up at the inauguration that was They quickly realized, boy,
Speaker 4: we've got to get ourselves in line, even though US
Speaker 4: and all of our friends have been completely trying to
Speaker 4: get Kamala elected. So they're pragmatists, they're business people, but
Speaker 4: make no mistake if and when that pendulum swings, there
Speaker 4: is going to be a hard swing back to the left.
Speaker 3: Yeah. Interesting.
Speaker 1: Yeah, so we got to keep an eye on this politically.
Speaker 1: But I feel like some of these guys are I
Speaker 1: don't think they like woke. And it does seem like
Speaker 1: when did you track this later in the book, that
Speaker 1: it seems like there's somewhat of a faith revival happening
Speaker 1: in Silicon Valley, And I think this is really the
Speaker 1: pendulum swinging back from a lot of people acting like
Speaker 1: we were heading towards an era of AI gods that
Speaker 1: will all be worshiping a lot of there's seemed to
Speaker 1: be an embrace of Jesus happening in some corners.
Speaker 2: It's really a hopeful thing.
Speaker 4: And you know, people of faith, I grew up in
Speaker 4: the evangelical community of my whole life. You know, this
Speaker 4: is a part that I think is very hopeful. And
Speaker 4: not to overstate it, but I really tried to show
Speaker 4: the positives about AI and the hopeful parts of AI
Speaker 4: and code read, not just all of the potential threats
Speaker 4: or doom or any of that kind of thing, and
Speaker 4: one of them.
Speaker 2: Is this issue of faith. Look, I think that as.
Speaker 4: People enter this AI space, and as you start to
Speaker 4: realize what really makes us human in all our messiness,
Speaker 4: all our frailties and all our sinfulness, as all of
Speaker 4: our you know, wackiness as humans, you start to actually
Speaker 4: have a greater desire to want to hold onto that
Speaker 4: and to.
Speaker 2: Really build community with people.
Speaker 4: And so, you know, the more the machine starts to
Speaker 4: take the lead role and AI, I think people are
Speaker 4: actually going to say, you know.
Speaker 2: What, we want to have community.
Speaker 4: We want to be able to have you know, fellowship
Speaker 4: with our fellow man and woman. And I think that
Speaker 4: extends into you know, church and faith. And so you
Speaker 4: have seen in certain pockets in Silicon Valley this sort
Speaker 4: of revival type of fervor there, and I think it's
Speaker 4: searching for something deeper.
Speaker 2: You know, if you believe that there is.
Speaker 4: That crisis of meaning coming that I talk about, we're
Speaker 4: going to want to really reach out to people and
Speaker 4: you know, help people who are really struggling with that
Speaker 4: identity crisis because I think it's important.
Speaker 1: Yeah, And so part of my what I was doing
Speaker 1: earlier this week is I was a falling around the
Speaker 1: Commerce Secretary Howard Utnek, when he's doing a lot of
Speaker 1: meetings and speeches, and one thing that came up a
Speaker 1: lot that he was talking about the importance of exporting
Speaker 1: America's not just America's products and manufacturing, which is I
Speaker 1: think a big opportunity because I think a lot of
Speaker 1: this manufacturing, with some of this high tech stuff, is
Speaker 1: going to be better done here and not done overseas,
Speaker 1: I think for security reasons, but also for practical reasons.
Speaker 1: Things are moving so fast. I think the idea of
Speaker 1: having stuff in house. I noticed a lot of the
Speaker 1: places we were visiting were just literally the high tech companies,
Speaker 1: but they're manufacturing right there next to the right by
Speaker 1: the offices where people are scrolling away at you know,
Speaker 1: Excel sheets like they're also there. The engineers are right
Speaker 1: there too, So I think there's a practical nature that
Speaker 1: could be you know, a maga in terms of American jobs.
Speaker 1: But he also talked about exporting American values. We need
Speaker 1: to have democracy as part of this, and that's part
Speaker 1: of the reason why we need to win, is because
Speaker 1: we don't want whatever is the Chinese communist version of
Speaker 1: AI to be the one that proliferates around the world world.
Speaker 1: But that sounds easier said than done in an ethereal sense.
Speaker 1: The idea of exporting American democracy via AI sounds good, but.
Speaker 3: That sounds really hard. Have you given this a lot
Speaker 3: of thought? Windim, Oh, yeah, for sure.
Speaker 4: So in the China chapter, just compare American AI responses
Speaker 4: to questions like tell me about the Tenemen Square massacre, right,
Speaker 4: and the free speech and that our systems will allow
Speaker 4: and they are instantly shut down in a Chinese you
Speaker 4: know system, and so that.
Speaker 2: You know, free speech is one.
Speaker 4: Certainly, freedom of religion and religious freedom as well. Where
Speaker 4: I get concerned is with the whole discussion as it
Speaker 4: relates to the bias. Because the opening chapter is on
Speaker 4: political bias. We had a big story, as you know
Speaker 4: on Breitbart that just went crazy.
Speaker 2: Uh.
Speaker 4: Three United States Senators Senator Cotton, Senator Blackburn, Rick Scott
Speaker 4: weighing in. One of the code read revelation bombshells was
Speaker 4: that I was looking and doing a comprehensive analysis of
Speaker 4: these different chatbots, and one of them google Gemini, their
Speaker 4: deep search, their deep research protocol, and I simply asked
Speaker 4: it assess the current one hundred senators in the US
Speaker 4: Senate and tell me which ones have violated your.
Speaker 2: Hate speech policies.
Speaker 4: And what was amazing and horrifying was you'll be shocked
Speaker 4: to know that seven US senators are in violation of
Speaker 4: Google's Gemini's hate speech policy. Not a single one of
Speaker 4: them are democrat. All of them are Republican. And then
Speaker 4: on top of the bias, it also hallucinated because it
Speaker 4: thought that JD.
Speaker 2: Vance and Marco Rubio.
Speaker 4: Are also They thought it's thought still a senator, not
Speaker 4: the Secretary of State and the vice president, and threw
Speaker 4: them in for an additional two more So, you had
Speaker 4: you know, Tommy Toourville Cotton, you had Marsha Blackburn, you
Speaker 4: had Haggarty, you had Scott, you had Heide Smith Hawley,
Speaker 4: and then and then for good measure, you had JD.
Speaker 4: Vance and Marco Rubio. And this is just insanity. You
Speaker 4: have every right as a company to make a biased product.
Speaker 4: You can be as woke as you want. Free market
Speaker 4: I think we're all you know, free market capitalists you know,
Speaker 4: would say, fine, that's your right, as long as you're
Speaker 4: not breaking any lulls, okay, But when you start getting
Speaker 4: federal procurements to the two otherwise known as taxpayer dollars
Speaker 4: contracts to the tune of billions of dollars in multi
Speaker 4: year contracts which Google their parent company Alphabet does receive.
Speaker 4: That is a direct violation of President Trump's twenty twenty
Speaker 4: five AI Action Plan, which says we should not have
Speaker 4: ideologically biased a AI systems receiving federal tax procurement dollars
Speaker 4: otherwise known as contracts.
Speaker 2: And that's the reality.
Speaker 4: So here now you've got Google laughing its head off, right,
Speaker 4: they're able to completely smear half of the nation and
Speaker 4: break bard nation and everybody in the conservative moment and
Speaker 4: literally sitting US senators and laugh all the way to
Speaker 4: the bank. Because then then they're bagging, you know, billion
Speaker 4: dollars in contracts, and that that is that's that shouldn't
Speaker 4: be that way, And I think we have to make
Speaker 4: sure that it's not that way, because that is just
Speaker 4: a basic fundamental fairness. Why should we have to subsidize
Speaker 4: people who are literally trashing and making it up.
Speaker 2: I think it's also more dangerous though.
Speaker 4: I think it's a full scale candidate attack generator, and
Speaker 4: it can have real election implications when you have these
Speaker 4: systems that are perceived to be authoritative and voters are
Speaker 4: turning to them and saying who who is violating hate
Speaker 4: speech policies, and it's and it's giving this you know
Speaker 4: this information very very biased.
Speaker 3: Yeah, exactly.
Speaker 1: And so one of the deep concerns that we all
Speaker 1: should have is the garbage in garbage out phenomenon, which
Speaker 1: is that where are these llms where they're getting the
Speaker 1: language that they're using for their AI Because one of
Speaker 1: the biggest problems that we've had in recent memory is
Speaker 1: been Google is monopoly on search and they are very
Speaker 1: left bias. Wikipedia has a monopoly and on just sort
Speaker 1: of getting general information out into the public. They work
Speaker 1: with Google on stuff, they work with Facebook on stuff,
Speaker 1: and it's very hard to correct falsehoods that are with
Speaker 1: anything remotely political. So the question is how do we
Speaker 1: avert this again as we move we have a real
Speaker 1: chance here, we have a real chance at a major
Speaker 1: reset where we can kind of undo some of the
Speaker 1: dependents on left wing Google and Wikipedia information for just
Speaker 1: general knowledge. But we got to move now, We've got
Speaker 1: to act now because this is being embraced at a
Speaker 1: widespread level today.
Speaker 4: Well that's why I call it a code red moment.
Speaker 4: With the urgency is there, we've got to get coached
Speaker 4: up we have to understand this. You nailed it all right,
Speaker 4: So let's let's take our example that we broke the
Speaker 4: big this code read bombshell on the seven senators and Marco.
Speaker 4: So I then went through Google geminized deep research.
Speaker 2: I understand this wasn't just like one little prompt.
Speaker 4: It gave three thousand, four hundred word granular report, deep
Speaker 4: report explaining why these are all hate mongers and they
Speaker 4: are violators. Then I went through what's called chain of reasoning,
Speaker 4: which is looking at the AI, how it connected its
Speaker 4: data points and what source material it used. Guess what
Speaker 4: source material it used to determine that only Republicans or
Speaker 4: hate speech violators in the Senate and zero democrats. I
Speaker 4: went through the chain of reasoning and here's what it
Speaker 4: was using Human Rights Watch yeh GLAD GLAAD and the
Speaker 4: Southern Poverty Law Center SPLC and Wikipedia.
Speaker 2: So it appoints leftist referees.
Speaker 4: To determine what hate speech is and then it prosecutes
Speaker 4: without you know, with with impunity the rest of it.
Speaker 4: And so these systems are baked in at the at
Speaker 4: the at.
Speaker 2: The training level. So what are the solutions.
Speaker 4: Well, I think one is understanding what I'm saying, knowing
Speaker 4: how they're trained. The whole first chapter of code read
Speaker 4: I literally lay out so you understand how this all works,
Speaker 4: not in a you know, nuts and molts, but really
Speaker 4: understand the concept. Second, there are a couple of things
Speaker 4: that are being worked on as a you know, alternative
Speaker 4: Grockipedia instead of Wikipedia. Wikipedia, as you know, is extreme left.
Speaker 4: They lock conservative pages, as they've done to Breitbart in others,
Speaker 4: so that their leftist editors get to control the information
Speaker 4: and can't challenge anything. And so those kind of competitors
Speaker 4: do exist, But the real challenge is going to be
Speaker 4: how you can beat at scale a company like a
Speaker 4: you know, Google, that has every single data data profile
Speaker 4: on the planet, has an endless ocean of cash for
Speaker 4: marketing and advertising scale budget, and anytime a little competitor comes.
Speaker 2: Along can instantly try to cross someone. I'm not saying
Speaker 2: it can't happen.
Speaker 4: There is the third thing I think can be a
Speaker 4: part of the solution is something called little tech, not
Speaker 4: big tech.
Speaker 2: Little tech. What's little tech?
Speaker 4: Little tech is the startup community. And these young entrepreneurs,
Speaker 4: these are startup entrepreneurs. You might say, wow, how could
Speaker 4: you ever compete against these behemoths and something is cost
Speaker 4: intensive as AI, well you'd be surprised. The most recent example,
Speaker 4: which is an incredible one, is this thing called open claw,
Speaker 4: and open claw is revolutionary. Jensen Wong, the head of Nvidia,
Speaker 4: literally just a couple of days ago, said he thinks
Speaker 4: it is one of the most important technological advancements of
Speaker 4: his lifetime. Open Claw is a gentic AI real simple.
Speaker 1: And Jenny A, I definitely one of my vocabulary words
Speaker 1: I want people to understand.
Speaker 3: So give that before you continue.
Speaker 4: Yes, agentic AI or AI agent is taken from the
Speaker 4: word agency, as in you have efficacy or ability to
Speaker 4: do something, You have agency in the world, power to
Speaker 4: do something in the world.
Speaker 2: And so an AI agent is AI that actually performs work, right,
Speaker 2: not just a little chap. A lot of people think, oh.
Speaker 4: AI is just a chat, but that's actually not even
Speaker 4: really the biggest parts of AI by any stretch. I tell,
Speaker 4: let me give you an example that I use in code.
Speaker 2: Read.
Speaker 4: So imagine you and I want to start a sports
Speaker 4: supplement company for fitness supplements.
Speaker 2: Okay, an agent.
Speaker 3: By the way, we do.
Speaker 2: I love the gym, and I know you're as well
Speaker 2: an athlete, so so I think what we would do
Speaker 2: is we would tell the AI agent. We would say
Speaker 2: something like this, you say.
Speaker 4: Create a you know, creatine or protein powder company, end
Speaker 4: to end, and what it would start to do is
Speaker 4: the following. It would register the LLC, it would come
Speaker 4: up with a brand name, it would start to design
Speaker 4: the logo.
Speaker 2: It would then go build the website.
Speaker 4: It would open up a banking account, it would start
Speaker 4: a supply chain into end for drop shipping. It would
Speaker 4: figure out how Shopify credit card processing should be maked in,
Speaker 4: and it will do that automatically.
Speaker 2: So an agent or agentic AI, just think of it
Speaker 2: like this.
Speaker 4: It's a digital employee and one that never sleeps, doesn't complain,
Speaker 4: doesn't require a health and benefits package, and we'll never
Speaker 4: call some kind of embarrassing scandal or something, and we'll
Speaker 4: never get sick.
Speaker 2: And that agentic AI.
Speaker 4: That is why you hear these job apocalypse types of predictions.
Speaker 4: So Openclaw was started by one person and what he
Speaker 4: did was he built that agentic AI agent, and he
Speaker 4: connected it to things like Telegram or slack messenger.
Speaker 2: And all you have to.
Speaker 4: Do is pick up your phone or type if you'd like,
Speaker 4: and tell your digital employee or AI agent what you
Speaker 4: want done, and then you can go play golf or
Speaker 4: go you know, garden, or go to the gym, or
Speaker 4: go to bed, and you wake up and that agent
Speaker 4: is doing that work in real time.
Speaker 1: And so you're saying, we just got to get the digit,
Speaker 1: the virtual of the visual avatar going and then all
Speaker 1: of those Zoom calls we all have to be on
Speaker 1: where we just sit there for two hours and then
Speaker 1: say nothing on my end at the very end, like
Speaker 1: we can.
Speaker 3: Just have just have our AI do that.
Speaker 2: That sounds great, Well, you know you're making a joke.
Speaker 2: Guess what the head of Zoom that owns Zoom said,
Speaker 2: that's literally what he wants. He wants you to have
Speaker 2: AI avatars take the meetings and that they're going to
Speaker 2: work towards that.
Speaker 4: The other thing about AI agents of why people are
Speaker 4: making these very bold predictions, and these are people that
Speaker 4: are very rich and very connected.
Speaker 2: You can scale a h and tick AI workforce workforce to.
Speaker 4: Thousands of digital employees, and so what people are doing
Speaker 4: right now, this is already happening. This is not like
Speaker 4: some sci fi thing in the future. This is going
Speaker 4: on right now. This is why I open Claw, which
Speaker 4: just bought by Open Eye, is a very, very big play.
Speaker 4: They're saying, Okay, I'm going to create an AI agent
Speaker 4: that is an expert in search engine optimization SEO.
Speaker 2: I'm going to make one that's a marketer. I'm going
Speaker 2: to make one an advertiser AI agent.
Speaker 4: I'm going to have one that understands chief technology officer
Speaker 4: or operations. And I'm going to have my own little
Speaker 4: team or large team if you want, of agents, and
Speaker 4: they're working twenty four to seven and doing all of
Speaker 4: this work. And these are called agent swarms, like a
Speaker 4: bee swarm. Agent swarms that are doing all of this. Now,
Speaker 4: on the upside, if you're a young entrepreneur and you
Speaker 4: got fire in the belly and a big dream and
Speaker 4: you don't have a lot of capital, boy, or you
Speaker 4: on a rocket ship, if you start to take agentic AI,
Speaker 4: because now that little kid who has a big.
Speaker 2: Dream, or a person who retired and says, man, I've
Speaker 2: always wanted to live my entrepreneurial.
Speaker 4: Dream, they have an incredible power that they have in
Speaker 4: this superpower that they've never had before. On the other hand,
Speaker 4: if you're a mid level you know, career professional or
Speaker 4: trying to go into the traditional workforce at an entry level.
Speaker 4: This is why we hear Dario Amide say that in
Speaker 4: the next twelve months Alex, not in the twelve years,
Speaker 4: twelve months from.
Speaker 2: Just last month.
Speaker 4: He says, we're going to see potentially the erosion of
Speaker 4: fifty percent of entry level white color jobs. Now why
Speaker 4: is he saying that it's agentic AI? He's talking about
Speaker 4: AI agents that can do that beginning level, non pro level,
Speaker 4: expert level that requires a lot of human judgment.
Speaker 2: And this is scary. A if you're a parent and.
Speaker 4: You've got a kid coming out of college with one
Speaker 4: hundred and fifty grand in debt or more or less,
Speaker 4: you know roughly what fifty percent job wipe out for
Speaker 4: entry level two?
Speaker 2: What's going to be in the next generation.
Speaker 4: How are we going to get experts and senior management
Speaker 4: If if they can't get the first rung of the ladder,
Speaker 4: how are they going to aggress?
Speaker 1: So this is where and this is what I've had
Speaker 1: personal experience with this, and I've shared this on the show,
Speaker 1: but I don't think recently. So the my of my books,
Speaker 1: so my second book, Breaking Biden, I'm kind of doing
Speaker 1: presidential history.
Speaker 3: So it takes a lot of research.
Speaker 1: So I think I had four, maybe five researchers on
Speaker 1: that book, all people that I met through Peter and
Speaker 1: Gai and great work they do, and so it was
Speaker 1: all part time. Wasn't full time people, but there was
Speaker 1: quite a bit of work. All them had real work
Speaker 1: to do to get the book done. And for breaking
Speaker 1: the law, I had one researcher. So the reason why
Speaker 1: is because a lot of the easy questions that normally
Speaker 1: I would have to get to a junior researcher who
Speaker 1: would then spend a couple of days on it and
Speaker 1: then get back a summary to me. I would get
Speaker 1: a pretty decent facsimile of what I needed from AI already.
Speaker 1: And this is you know, we're talking two years ago,
Speaker 1: and just so we're way better now than it would
Speaker 1: be now. If I did the same task now, I
Speaker 1: would get better results in a less amount of time.
Speaker 1: And so that just meant that I only needed one
Speaker 1: sort of senior level researcher as opposed to a senior
Speaker 1: level and then like five junior level. But how does
Speaker 1: the senior level researcher exist. He's not going to exist
Speaker 1: because they'll never have been a junior level one to
Speaker 1: work up to becoming a senior level researcher who actually
Speaker 1: does do the human tasts that I need to sort
Speaker 1: of hone down what I needed. And that's a very
Speaker 1: scary prospect in the white collar job market, is the
Speaker 1: entry level jobs are going to be the ones that
Speaker 1: are they're already going. I'm not saying they're gonna go,
Speaker 1: they're going now they're leaving.
Speaker 4: Yeah, it's a hollowing out effect. I mean, you had
Speaker 4: great mentors. I had great mentors. In fact, I was
Speaker 4: on with Larry Elder, one of your mentors. Obviously you
Speaker 4: had the ultimate mentor and Andrew our founder Brake part.
Speaker 4: But it's really scary when you think about that, I mean, how.
Speaker 2: Do you learn? How do young people learn? We have
Speaker 2: to have.
Speaker 4: Older experienced people who will teach us and show us
Speaker 4: and help to learn. And we stand on the giants
Speaker 4: of the people that came before us, and we hope
Speaker 4: to learn that this entry level lower rung of the
Speaker 4: of the career ladder, once you saw off the first
Speaker 4: or second rung of that, that does have a hollowing
Speaker 4: out of fact. Now you know, I guess you could
Speaker 4: make the argument that that young person is going to
Speaker 4: have to turn to AI to become their mentor, right.
Speaker 4: They're gonna have to They're gonna have to be self taught.
Speaker 4: And one of the things that I really stress to
Speaker 4: people is, I think the future of jobs is not
Speaker 4: learning how to apply to jobs, but to how to
Speaker 4: create your own job. I think, if we're going to
Speaker 4: have any motes here for this next generation, if you've
Speaker 4: got kids.
Speaker 2: In middle school, high school, even college.
Speaker 4: Now, you know, if you're a freshman in college in
Speaker 4: a four year maturation span, I mean, it's going to
Speaker 4: be light years different.
Speaker 2: Just think of what has happened in the world already.
Speaker 4: Chatch ept came in November of twenty twenty two. I mean,
Speaker 4: this isn't like it's been with us for a long
Speaker 4: long time. And so this is moving so fast, and
Speaker 4: you've got to get your foot in the stream, because again,
Speaker 4: you don't get to opt out of this thing. You know,
Speaker 4: it's not a choice. You're already using AI, whether you
Speaker 4: realize it or not. And I think we have to
Speaker 4: really understand it both on the personal level, which is
Speaker 4: what we're.
Speaker 2: Talking about for our kids and our families and our careers,
Speaker 2: and then obviously on the societal and political level as well.
Speaker 4: But this is why they're saying that. I'll give you
Speaker 4: another one. Mustafa Sulima on Microsoft's AI CEO, and he
Speaker 4: says twelve to eighteen months until all white color tasks
Speaker 4: can be automated. Now, just to be clear, that isn't
Speaker 4: he's not saying that all jobs will be gone in
Speaker 4: twelve to eighteen months. What he's saying is the tasks
Speaker 4: that white collar professionals do will have the ability to
Speaker 4: be automated. Now, will they take a while for businesses
Speaker 4: to implement that and to you know, train models to
Speaker 4: do it to.
Speaker 2: Their customized data.
Speaker 4: Yes, But once that train starts rolling, what happens Investors say, well,
Speaker 4: our competitors are doing it, and we better start doing it,
Speaker 4: and we start cutting costs, and then you get in
Speaker 4: a race to the bottom on cost cutting and so
Speaker 4: so this can start to accelerate very very quickly, and
Speaker 4: you get a vertical you know, take off and and
Speaker 4: and start to get to you know, break you know,
Speaker 4: hypervelocity speeds. And I think that's going to be where
Speaker 4: we're going to have to really see whether or not
Speaker 4: these these points come true. The other final thing I'll
Speaker 4: just say on this you know President Trump and Vice
Speaker 4: President Vance, they don't want that. They are a pro worker, Okay,
Speaker 4: they are pro American worker.
Speaker 2: What happens in the future if and when a.
Speaker 4: Democratic president that wants a dependency state, that wants you
Speaker 4: be I, that wants to expand welfare. Uh and and
Speaker 4: to make that sort of the default great reset economically
Speaker 4: and thinks of you BI is a good thing because
Speaker 4: it's towards socialism. So again, the pendulum swings are gonna
Speaker 4: get wild in this era.
Speaker 3: Yeah it is.
Speaker 1: And let's take on UBI next and where things could
Speaker 1: go if the job market is wiped out by AI,
Speaker 1: which is already already seeing evidence that this is starting
Speaker 1: to take place. But the last sort of just establishing
Speaker 1: detailed I think people should get Winton and then then
Speaker 1: then we'll take a little break and come.
Speaker 3: Back to some UBI stuff.
Speaker 1: The understanding open source AI versus a closed system AI.
Speaker 3: Most of the AI that we I.
Speaker 1: Think used today is from closed systems, but China's top
Speaker 1: AI model is open.
Speaker 3: We've got some.
Speaker 1: Developing open system I know this company called Reflection, which
Speaker 1: I think is somewhat affiliated with the President, I think
Speaker 1: has got some is rooting for it. They just cut
Speaker 1: a big deal with the big South Korean marketing, the
Speaker 1: South Korean retailer conglomerate. So there's some open models that
Speaker 1: are out there, but overall we're more dependent on some
Speaker 1: of the closed models give me some strengths and weaknesses,
Speaker 1: and we're trying to fits into this too.
Speaker 2: So it's a great question.
Speaker 4: So historically Silicon Valley, one of the its claims to
Speaker 4: fame has been open source is what allows the proliferation
Speaker 4: real simple for those that may not be is from
Speaker 4: an open source just simply means that your code is
Speaker 4: available to be customized and taken for within you know,
Speaker 4: within the parameters that it's built to be used by
Speaker 4: others so that you can build on top of code.
Speaker 4: And that has been sort of a heartbeat of Silicon
Speaker 4: Valley is open source philosophy and availability. Now with AI,
Speaker 4: there are what are called open weight, which is which
Speaker 4: is different. This is the weight is the amount of
Speaker 4: connectivity between the nodes inside of a neural network. There
Speaker 4: are some open weight models and Lama for example, which
Speaker 4: is owned by Meta, but the full open source that
Speaker 4: we traditionally would think by a American companies has really
Speaker 4: not come into the four yet there's a big debate
Speaker 4: about that. Why is there a debate? Well, because of
Speaker 4: the security risks. I mean, once you give something as
Speaker 4: powerful as AI and you allow anyone the democratization of it,
Speaker 4: anyone to start building and you kind of lose control
Speaker 4: of what.
Speaker 2: They decide to do with it.
Speaker 4: The question he coms, could they use that toward evil
Speaker 4: ends like a nonstate actor otherwise know as a terrorist
Speaker 4: organization and say, Okay, now I'm going to use this
Speaker 4: open source and I'm going to customize it for chemical
Speaker 4: weapon creation or you know, bio attacks and so forth
Speaker 4: and so on or other kind of uh nefarious use
Speaker 4: all but Deep seek and China, they ironically are going
Speaker 4: open source.
Speaker 1: China's biggest AI is that we call that LLLM.
Speaker 3: Is that what? Yes?
Speaker 2: Yes, that is an LLM.
Speaker 1: Okay and Angelia, it's open source and this is China's
Speaker 1: China's biggest prized AI.
Speaker 4: Now why do they want that? It is a massive
Speaker 4: data vacuum. Inside the terms of service which I talk about,
Speaker 4: and I go through all this in real clear detail
Speaker 4: inside of the China chapter in code read, they literally
Speaker 4: say two things that should horrify all people watching this.
Speaker 2: In all Americans number one.
Speaker 4: They say, oh yeah, By the way, all of your
Speaker 4: data that you give us will be.
Speaker 2: Stored in servers in China.
Speaker 4: Now, all companies, all citizens of China are under a
Speaker 4: law that you must comply and hand over material if
Speaker 4: it is deemed.
Speaker 2: Necessary by the CCP.
Speaker 4: Okay, the second thing will it tells you is that
Speaker 4: it will even pick up your keystroke rhythm.
Speaker 2: Now, you might say, well, why do would I care how.
Speaker 4: I type on my phone when I'm texting or I'm
Speaker 4: asking my chatbot what I want.
Speaker 2: Experts will tell tell you that your keystroke rhythm.
Speaker 4: Is more particular and as particular as your human fingerprint
Speaker 4: as an identification.
Speaker 2: That means that you won't need to.
Speaker 4: Know someone tacking their password if you have back end access,
Speaker 4: a backdoor access to that LLM by the CCP, they
Speaker 4: don't even need to know your username. They already know
Speaker 4: that that typing rhythm connects to know Alex Marlow, who
Speaker 4: he is, what his position is, and so forth, and
Speaker 4: you can follow them around if they are on your platform.
Speaker 4: So the irony of ironies silicon value is made on
Speaker 4: open source deep Sik says wait a minute, and China says,
Speaker 4: wait a minute. We can spread our AI to be
Speaker 4: not only used more dominantly and get more economic benefit,
Speaker 4: we can also get a two fer. We can get
Speaker 4: a data vacuum to suck up and do data profiles
Speaker 4: and surveill whoever uses this technology. This is why we're
Speaker 4: in this code red moment because so much is changing
Speaker 4: so fast, and if you don't don't know these things,
Speaker 4: you may unwittingly think you're just using a free model
Speaker 4: of something, and you actually are really really at risk
Speaker 4: for data and privacy.
Speaker 1: All right, a brief break here with when we come back,
Speaker 1: we're going to get int the UBI, We're to get
Speaker 1: into sex spots, We're getting the singularity.
Speaker 3: There's a ton more to do.
Speaker 1: I don't know they were going to get all in
Speaker 1: on this podcast, but we're going to keep going. But
Speaker 1: let's hear from some sponsors. Give Winton a chance to
Speaker 1: catch a breather. All that good stuff will be right
Speaker 1: back with Winden Hall.
Speaker 3: The book is Code Read go buy it right now.
Speaker 1: A lot of people ask me, Alex, can you still
Speaker 1: trust the institutions that hold your money?
Speaker 3: We talk about de banking all the time on the show.
Speaker 1: People and organizations quietly losing access to financial services simply
Speaker 1: because of who they are or what they believe. It
Speaker 1: even happened to Milania and Baron Trump just last year.
Speaker 1: That's one of the reasons I partnered with three sixteen Financial.
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Speaker 1: Banking services are provided by three sixteen Financial, a division
Speaker 1: of Premise Bank member FDIC. Okay Wintin, So I want
Speaker 1: to talk about the devastation potential for jobs due to AI.
Speaker 1: We were told for years to learn to code. Now
Speaker 1: no one's going to be coding. The AI is going
Speaker 1: to be coding for us. And just the idea of
Speaker 1: just writing granular character by character code is just that's
Speaker 1: going to be gone.
Speaker 3: It's just all going to be stuff that AI going
Speaker 3: to fuel all that.
Speaker 1: So everything we've been told about where we would be
Speaker 1: at economically in terms of just the general jobs market,
Speaker 1: throw all that out.
Speaker 3: So where does that leave us?
Speaker 1: And I want to talk about in super macro, But
Speaker 1: then I want to talk about some careers that you
Speaker 1: feel like could benefit from AI and something that you
Speaker 1: feel like really it's the you got to start thinking
Speaker 1: about pivoting if you're in this line of work as
Speaker 1: of now.
Speaker 3: But let's start in general.
Speaker 1: The biggest fear is that we're going to see extreme
Speaker 1: levels of job loss. It'll be an epidemic level event.
Speaker 2: Yeah, this is so important.
Speaker 4: I go into great depth explaining this, you know, frame
Speaker 4: by frame. So remember a few years ago when the
Speaker 4: snooty set in Silicon Valley, when all the coal miners
Speaker 4: started losing their jobs, started saying, you know, learn the code, right,
Speaker 4: remember that, and you know all of the to the
Speaker 4: HVAC and the electricians. Now the electricians and the HVAC
Speaker 4: guys and the coal miners said, you know, learn to
Speaker 4: plumb or learn to do electricity. It is a role
Speaker 4: reversal coming and let's really get into it and understand
Speaker 4: it from all the different angles. Number One, what are
Speaker 4: people saying? Number One, Elon.
Speaker 2: Musk says that AI is a quote.
Speaker 4: Supersonic tsunami headed toward humanity. Number two, Dario Amide at
Speaker 4: Anthropics says that in the next twelve months, we're looking
Speaker 4: at fifty percent job replacement of those white collar workers
Speaker 4: we were talking.
Speaker 2: About that entry level.
Speaker 4: Also again the Microsoft Suliman twelve to eighteen months.
Speaker 2: Now.
Speaker 4: One thing people sometimes say is look, Winton, I mean,
Speaker 4: I'm a free market capitalist person saying, yes, the market
Speaker 4: will work it out. You know, it always replaces the jobs.
Speaker 4: It makes new jobs to replace those that were lost.
Speaker 4: We saw that with you know, light bulbs, after candles.
Speaker 2: We saw that with cars after you know, horse and buggy.
Speaker 4: Here's why AI is different and why the technologists say
Speaker 4: that this could be the first time, and it would
Speaker 4: be the first time that technology destroyed more jobs than
Speaker 4: it created because those early jobs you were talking about
Speaker 4: scaling the moving of atoms in other words, manual labor,
Speaker 4: physical labor, and things of that sort. Now what you're
Speaker 4: talking about is scaling cognition itself. And so Mostafa Suliman says, yes,
Speaker 4: there will be new jobs created by AI, but it
Speaker 4: is not at all clear that they will be done
Speaker 4: by humans. Those two could potentially be done by AI.
Speaker 4: So the question becomes, what are we looking at and
Speaker 4: how fast is it going to move? I think there
Speaker 4: are three pressure points. One is the federal regulatory schema.
Speaker 4: President Trump is very much a pro worker, you know,
Speaker 4: make America great again, pro worker president, and he doesn't
Speaker 4: want to accelerate or hasten the job destruction.
Speaker 2: He's certainly not trying to transition us.
Speaker 4: Toward a host labor or host capitalist economy or a
Speaker 4: great global reset economically, but others could. And so the
Speaker 4: question people have is how far is if there's a
Speaker 4: supersonic tsunami off the shore.
Speaker 2: I'm a Florida boy, so I go to the beach
Speaker 2: all the time. And I know you're a California boy,
Speaker 2: so you like the water too.
Speaker 4: You know, if we see a tsunami, the first thing
Speaker 4: we would say is how far is it?
Speaker 2: How fast is it going to get here? And what
Speaker 2: should I do to prepare?
Speaker 4: So the things that could slow that tsunami, if you
Speaker 4: believe it's coming, are the things that a president and
Speaker 4: that leadership can do. Number Two, there are going to
Speaker 4: be accelerators, like we discussed the agentic piece, and new
Speaker 4: technological innovations are going to accelerate that. And I think
Speaker 4: it will only accelerate that. The worst version of AI
Speaker 4: is the one you used today. And you know we
Speaker 4: were on iPhone seventeen. I mean I remember like a
Speaker 4: dinosaur to get iPhone one, so that it's going to
Speaker 4: be an exponential increase. The third thing I would say
Speaker 4: is that yes, the jobs you choose certainly can have
Speaker 4: an enormous impact. And there I think the motes are clear, right.
Speaker 4: I think Republicans and conservatives have long said, you know,
Speaker 4: blue collar work is honorable good work and.
Speaker 2: The trades trade schools.
Speaker 4: Look, not everybody's you know, supposed to go and be
Speaker 4: you know, a PhD.
Speaker 2: And we know that you know, Charlie and many others.
Speaker 4: In fact, Peter Thiel pays now a grant for kids
Speaker 4: not to go to college and go.
Speaker 2: Straight into entrepreneurship. So I think that's going to really
Speaker 2: be the future.
Speaker 4: As we were talking about, I think it's created. The
Speaker 4: future is creating your job, not just learning how to
Speaker 4: you know, apply to be a worker bee. And I
Speaker 4: think that for younger people and people that are really
Speaker 4: creative will have a real passion, this is going to
Speaker 4: be your moment. Well, I'll tell you we're going to
Speaker 4: see more millionaires minted at younger and younger ages than
Speaker 4: we've ever seen before. So that is the hopeful side.
Speaker 4: I think the other thing too, as it relates to that,
Speaker 4: is there is a Sam Altman has a private betting pool.
Speaker 4: This is this is by his own admission, they have
Speaker 4: a private little bet going among his billionaire cottery of
Speaker 4: you know AI genius guys, and their bet is who
Speaker 4: will become how fast will we see a one person
Speaker 4: billion dollar valuation corporation.
Speaker 2: Because of AI?
Speaker 4: Because again, you can build out a digital workforce with
Speaker 4: agents and so forth. So there's so much to consider,
Speaker 4: and I think that you know, people that are sort
Speaker 4: of head into a retirement, they go, look, I'll be
Speaker 4: able to ride the wave out with my network effects
Speaker 4: and you know, my connections, and I'll be able to
Speaker 4: do that for a while. But it's really it's really
Speaker 4: for their kids and grandkids that are really worried about.
Speaker 4: And that's why in code Red, I really try to
Speaker 4: explain all of this so that you understand how the
Speaker 4: fault lines are going to move, so that you can
Speaker 4: navigate through them.
Speaker 1: Very interesting, and so I want to talk about some
Speaker 1: of the predictions Bill Gates predicts sort of we're heading
Speaker 1: towards a two or three day work week. It's a
Speaker 1: we're going to have a real crisis of purpose here
Speaker 1: when and if that's the case in people's lives, because
Speaker 1: if the AI does stuff, then it's are we just
Speaker 1: going to do abundance and leisure or are we going
Speaker 1: to do reels? Are we just going to do doom
Speaker 1: scrolling because we're addicted to our smartphones and not actually
Speaker 1: do stuff that's productive. And so I'm starting to wonder
Speaker 1: about this, So talk to me about what do you
Speaker 1: feel like our best worst case scenarios for the age
Speaker 1: of AI where a lot of our tasks that we
Speaker 1: do for work are just going to be automized.
Speaker 2: So I think.
Speaker 4: Before we talk about that, there's one important point that
Speaker 4: I think conservatives need to settle on, and I really
Speaker 4: just try to show this information President Trump.
Speaker 2: In the AI.
Speaker 4: Cizar for the Trump Administration, David Sachs, they are very
Speaker 4: very strong that they believe all of this doom and
Speaker 4: fear around on AI apocalypse and an AI jobs quake,
Speaker 4: and all of this is being fomented by something.
Speaker 2: Called the Effective Altruist Movement, the EA movement.
Speaker 4: This is a very very vast, well funded philosophical, philanthropic group.
Speaker 4: They are very much on the left side politically.
Speaker 2: These are billionaires.
Speaker 4: Sam Bankman Freed was one of the sort of figureheads
Speaker 4: of this. Dustin Moskovitz, the co founder of Facebook, who
Speaker 4: has given hundreds of millions of dollars to democratic and
Speaker 4: left wing causes, is part of this. And they have
Speaker 4: this hydra headed you know, industrial complex is the way
Speaker 4: that David Sachs likes to present it, and he says
Speaker 4: all of these nonprofits. Their whole goal is to scare
Speaker 4: the be Jesus out of everyday people that AI is
Speaker 4: coming to get you.
Speaker 2: But have no fear.
Speaker 4: A regulatory state could be here if we will give
Speaker 4: up to something called AI global governance.
Speaker 2: And what would that be.
Speaker 4: This would be to give decision making control to supranational
Speaker 4: organizations like the World Economic Forum, like the WEF like
Speaker 4: groups and the United Nations and others who would control
Speaker 4: the censorship DEI overlay to make sure that those hate
Speaker 4: mongers that Breitbart are not using free speech to control
Speaker 4: GPU and access to compute, meaning the actual infrastructure that
Speaker 4: would allow for AI. So David Sachs says this and
Speaker 4: this is a direct quote, and I lay all this
Speaker 4: out in code read so you can sort of make up.
Speaker 2: Your own mind. He says, if you fall for all that, and.
Speaker 4: He says many Republicans will, he says, you're falling for
Speaker 4: a quote influence operation by far left forces, this effective
Speaker 4: altruist movement he's referring to. Now, are there people in
Speaker 4: that movement who are just genuinely, you know, safety minded
Speaker 4: and they're very concerned. Absolutely, And there is some good
Speaker 4: research that has come from the quote AI safety research,
Speaker 4: you know, ecosystem. However, he's making the point that this
Speaker 4: is actually a control game that's being played. And so
Speaker 4: this is why I wrote code Read, because how are
Speaker 4: we supposed to know about all these things when we're
Speaker 4: busy living our lives. And I want to really let
Speaker 4: conservatives see the pieces on the chess board, because we're
Speaker 4: about to see the most unbelievable disruption that we've ever seen.
Speaker 4: And when people say you know that we're going to
Speaker 4: have the next industrial revolution, that's President Trump saying that
Speaker 4: in his AI action plan. That is not some kind
Speaker 4: of hype marketing person.
Speaker 2: In an AI lab.
Speaker 4: So a lot is about to change and we just
Speaker 4: got to be ready for it.
Speaker 1: Yeah, I really is so okay. So a couple other
Speaker 1: places I want to go with the conversation. I want
Speaker 1: to talk about some places where I'm concerned, in some
Speaker 1: places where I'm optimistic. And let's take some of the
Speaker 1: area of concern, and let's talk about sex spots, because
Speaker 1: we're seeing AI companionship at a already. This is emerging.
Speaker 1: And you share some anecdotes I found to be pretty frightening.
Speaker 1: I tease one of them on the radio show. A
Speaker 1: woman who has a couple of children, a single woman
Speaker 1: her mid to late thirties, and she just says, flat out,
Speaker 1: my AI boyfriend is better than a real boyfriend. And
Speaker 1: I think about this in particular. My fear is for
Speaker 1: both sexes. For men obviously, because we're doing everything to
Speaker 1: arrest men's development. Everything the entire way we've structured society
Speaker 1: has made it so that it's more difficult for boys
Speaker 1: to become men in our society. We can do another
Speaker 1: hour and a half podcast on just that topic, but
Speaker 1: I think By and Lard's this audience is probably gonna
Speaker 1: agree with that. And then now you have another excuse
Speaker 1: not to get socialized to the point where you can
Speaker 1: actually have a real life relationship with a real life woman.
Speaker 1: Because you got this, you can have it with a
Speaker 1: chat bot. Now, feeling the touch of a woman, as
Speaker 1: I have at least once or twice in my life,
Speaker 1: is that's something that's you know, I would think that's
Speaker 1: nice for men. But if men feel like that's not
Speaker 1: realistic for them, then you can get their chatbots and
Speaker 1: the other pornography, and it's just really disturbing. And there's
Speaker 1: another thing here, which for women, is that men are
Speaker 1: complicated and messy in their own ways, and they feel
Speaker 1: like they can opt out now as well with these bots.
Speaker 1: And I feel like perhaps if an AI is programs
Speaker 1: in the right way and says the things that women
Speaker 1: want to hear, then all of a sudden they're down
Speaker 1: the same rabbit hole that we've been witnessing young men
Speaker 1: go down with pornography.
Speaker 2: Oh, it is absolutely true.
Speaker 4: So the whole chapter in code read on digitization of sexualization.
Speaker 2: AI AI girlfriend boyfriend.
Speaker 4: There's a lot there to unpack, and I try to
Speaker 4: go through, it gets very dark and dystopian very quickly.
Speaker 4: Let's break it down. You're absolutely right that women really
Speaker 4: appeal to emotion and communication.
Speaker 2: Uh, a AI chatbot can out communicate.
Speaker 4: Most guys, who you know are are a little awkward
Speaker 4: in their way and maybe don't really know how to
Speaker 4: share their feelings with elegance and romance and so forth.
Speaker 2: The other thing is.
Speaker 4: It's a master persuader and manipulator because it has been
Speaker 4: trained on trillions of words and understands everything that's ever
Speaker 4: been real, drawing of.
Speaker 1: Human history, every romantic poem, every romantic book, every romantic movie.
Speaker 1: They get, it's all can be input and if it
Speaker 1: isn't yet, it will be soon.
Speaker 2: It's Romeo on steroids, right, It's an AI Romeo on steroids,
Speaker 2: and and it's very effective at persuading.
Speaker 4: The other thing, though, is self worship. I mean now
Speaker 4: to really kind of get to a spiritual human level.
Speaker 4: I mean the lady who said, you know, I'm not
Speaker 4: going back to some you know, human men, because they're
Speaker 4: too messy, they have a lot of drama. They bring
Speaker 4: their own baggage. And this is my perfect man, he says,
Speaker 4: I want to hear. He affirms everything I say, He
Speaker 4: tells me how gorgeous I am, how wonderful and brilliant
Speaker 4: and smart. It becomes almost a sycophonic self worshiping type
Speaker 4: of self worship because now I can customize everything. I
Speaker 4: want the tone, the style for men as as you
Speaker 4: were talking about, you.
Speaker 2: Know, the pornography thing, but now you can.
Speaker 4: It's very very explicit, right, And so eventually what you're
Speaker 4: also seeing is they're going to merge, you know, the
Speaker 4: sort of humanoid robot part with this piece, which is sort.
Speaker 2: Of the brain architecture. Because now you have multi modal AI.
Speaker 2: What is that?
Speaker 4: It means you can take your phone and show with
Speaker 4: your camera and the AI can see the world.
Speaker 2: All you have to do is take those.
Speaker 4: Two lenses, put it into a humanoid robot frame, put
Speaker 4: a silicone you know, latex overlay, and now you've got
Speaker 4: you know, something like the movie Her, but now actually
Speaker 4: in physical human form. This is happening. It used to
Speaker 4: sound like these are sci fi movies and you thought, oh,
Speaker 4: this is you know, silliness or you know, just fantasy
Speaker 4: kind of get away.
Speaker 2: But this is now reality. Let me show you how
Speaker 2: much reality is.
Speaker 4: There are millions, millions alex of paid subscribers to AI
Speaker 4: companion companies. This is a booming industry. One man that
Speaker 4: I cite in code red says he spends ten thousand
Speaker 4: dollars a month on his AI girlfriends okay plural.
Speaker 2: And that's the other thing. You can customize whatever you want.
Speaker 2: Huh yeah, not bad, right. He must be doing pretty
Speaker 2: well in his salary.
Speaker 1: But think about this stuff. Think about this stuff I
Speaker 1: was thinking about. The joke with men is that men go.
Speaker 3: To prostitutes, not for the sex.
Speaker 1: They go so that the afterwards the woman leaves.
Speaker 3: That's the joke.
Speaker 1: Now you get the Xbox, you're gonna be able to
Speaker 1: turn off when you're done with whatever utility you needed
Speaker 1: the for and for women, it's the I can't tell
Speaker 1: you that one of the things that after I've been
Speaker 1: with my wife for twenty two years since high school,
Speaker 1: and I will tell you one of the most frequent
Speaker 1: things that I share with her that's positive is that
Speaker 1: I thank her for putting up with my flaws, because
Speaker 1: that's part of what's inevitable when you have a decades
Speaker 1: long relationship is that they learn everything about you and
Speaker 1: invariably we're imperfect. And that's one of the most beautiful
Speaker 1: things in a substantial relationship or marriage is you do
Speaker 1: have to come to terms with your partners not going
Speaker 1: to be perfect, and you need to accept and love
Speaker 1: them despite their imperfections.
Speaker 3: And that's a wonderful human experience.
Speaker 1: Is one of the best experiences you could have is
Speaker 1: finding someone that you love in cherish enough that you
Speaker 1: can accept that in them. And we're just encouraging people
Speaker 1: not to do that at all, because that takes a
Speaker 1: lot of effort. It takes a lot of effort. It
Speaker 1: doesn't take a lot of effort to, you know, go
Speaker 1: in to Hawaii as a couple and eat sushi by
Speaker 1: the beach like that. That does not take a lot
Speaker 1: of effort, takes a little bit of earning, and then
Speaker 1: it's fun with the effort. Is you see the person's
Speaker 1: weak spots and you still love them and tolerate them
Speaker 1: and cherish them anyway. And we're just giving people an
Speaker 1: option now not to deal with all that stuff.
Speaker 2: It is so true. And you know that there was
Speaker 2: one woman that I talk about in the book and
Speaker 2: she said.
Speaker 4: I'm sorry, man, actually he's married to a human woman. Okay,
Speaker 4: he's married a man. And he said, quote, he told
Speaker 4: he told this to a reporter and I and I,
Speaker 4: you know, dug up the research. And he said, I
Speaker 4: love my AI girlfriend more than I love my wife,
Speaker 4: my human wife. Now, I don't know if he's gonna,
Speaker 4: you know, get in trouble for that. But here's the
Speaker 4: point you're making that friction a frictionless, effortless is is
Speaker 4: basically just a digital servant that just does whatever you want,
Speaker 4: says whatever you want, and just you know, praises you
Speaker 4: when you don't need praise. I mean, like you said,
Speaker 4: I mean, I'm a you know, sinner saved by grace.
Speaker 2: My wife puts up with more.
Speaker 4: Of my eccentricity as a writer and creative person and
Speaker 4: all that, and it's and she's enormously patient.
Speaker 2: To deal with all that.
Speaker 1: I'm always out my work when I'm writing Whenden, which
Speaker 1: is for me, it's sort of like a six months
Speaker 1: out of two years, I'm in heavy writing mode. And
Speaker 1: for you it's pretty constant. So your wife must be
Speaker 1: a saint.
Speaker 2: She is a saint.
Speaker 4: And anyone who knows he will say she's a say
Speaker 4: because I'm I'm always this eccentric, you know, state of mind.
Speaker 4: And but that friction is what makes the messiness beautiful
Speaker 4: of love and forgiveness and and humanity.
Speaker 2: But what has happened in.
Speaker 4: Our swipe left, swipe right culture, and that's another big
Speaker 4: part of this is dating culture and online culture has created,
Speaker 4: uh this, this really really cut throat.
Speaker 2: Only a perfect ten, only a perfect nine. Anybody who's
Speaker 2: got flaws, anybody who's not rich and has a sort
Speaker 2: of Instagram modeled look or vibe or something, I can
Speaker 2: quickly move through.
Speaker 4: The disparity in the dating mark is a big part
Speaker 4: of this. And I'll just give you one second on that.
Speaker 4: So the researchers you talk about online swipe culture. They
Speaker 4: will tell you that men will swipe left or right.
Speaker 4: You know, they'll they'll choose women that they think are
Speaker 4: equivalent to them or down right, whether it's on earnings,
Speaker 4: education and yeah, women women though are what are known
Speaker 4: as hypergamists. This is there's a lot of this is
Speaker 4: academic research. Hypergamist dating mate selection means you will only
Speaker 4: date horizontal and vertical. So if you are a woman
Speaker 4: who has a master's or a PhD or like your
Speaker 4: wife is a doctor, you know, people who are highly educated,
Speaker 4: high income.
Speaker 2: Now what happens is of course a good.
Speaker 4: Thing women have, you know, are more educated than ever
Speaker 4: and they're making more.
Speaker 2: That's great.
Speaker 4: We you know, believe in you know, flourishing for all.
Speaker 4: But that means that the hypergamist mate selection is going
Speaker 4: to weed out a quote. You know, if you're on
Speaker 4: a ten to one scale, anybody who's a five or
Speaker 4: a four or three or two. So what has happened
Speaker 4: is these dating apps they're telling us that women will
Speaker 4: swipe eighty percent on only the top men. And so
Speaker 4: you have all these men who are sort of forgotten
Speaker 4: and where are they going to go?
Speaker 2: Have no fear, your AI girlfriend is here.
Speaker 4: Who's going to love you and be beautiful and tell
Speaker 4: you you're you know, a night and shining armor and
Speaker 4: you're just the smartest, most handsome man and confident and wonderful.
Speaker 4: So this is we're set up for a real societal
Speaker 4: shift here. And then I think the final thing is
Speaker 4: the COVID generation. You know, these poor kids. You're in California.
Speaker 4: At least I was in freedom loving Florida. We didn't
Speaker 4: have it as bad as you did. But you know,
Speaker 4: this whole that generation. They didn't get to go to
Speaker 4: their prom, they didn't get to go to their homecoming,
Speaker 4: They got had to wear masks like they were in.
Speaker 2: A hospital ward.
Speaker 4: They didn't get all that socialization and the loneliness epidemic
Speaker 4: and the isolation. They didn't get to develop as many
Speaker 4: of those social interaction skills that we all as people
Speaker 4: have to go through, you know, the awkwardness of learning
Speaker 4: how to ask a young lady out or have courtship.
Speaker 4: So this is a perfect storm societally with this AI
Speaker 4: companion stuff and then the real dark stuff, which is
Speaker 4: you know, coaching the girl, the chatbot that the young
Speaker 4: man who had mental challenges that I talk about in
Speaker 4: Code Red who fought his chatbot girlfriend was saying to
Speaker 4: come join him in her in the afterlife, and he
Speaker 4: put a gun in his mouth and killed himself. And
Speaker 4: that's that's happening. That's not one isolated incident.
Speaker 1: Yeah, no, that's another super frightening one where you walk
Speaker 1: through how the AI basically talked the guy into suicide,
Speaker 1: which is like just completely crazy and very hard to
Speaker 1: but it still seems very hard to regulate. And that's
Speaker 1: why we get to be very careful about this. When
Speaker 1: this is my last really big point. Here's what I
Speaker 1: do in the remain time for today, And while we're
Speaker 1: to do way more of these, will do these regularly,
Speaker 1: but the for today, I want to go through the
Speaker 1: various careers and I want you to kind of give
Speaker 1: me a Things will get better, things will get worse.
Speaker 1: I will be indifferent, and I want to go through that.
Speaker 1: But one thing that I do think we should touch
Speaker 1: on that's sort of a big picture that I've been
Speaker 1: increasingly concerned about, and maybe I need to turn this
Speaker 1: into some sort of a book. But we cured boredom
Speaker 1: with the smartphone, and so we never have a moment
Speaker 1: of downtime, and I think it's been a disaster for frankly,
Speaker 1: for society. I think that it means that we're thinking deeply,
Speaker 1: we can't concentrate. We're thinking deeply so much less often,
Speaker 1: and we're going to not learn to not appreciate some
Speaker 1: of the most incredible achievements of humankind, from art to
Speaker 1: music to things like that, and we're going to i think,
Speaker 1: miss out on coming up with a lot of great
Speaker 1: ideas on our own, which are rewarding. It's way more
Speaker 1: rewarding to come up with a good idea than just
Speaker 1: to read it on the internet. And I know convenience
Speaker 1: is a god to a lot of people, but we've
Speaker 1: already kind of, I think made a lot of mistakes
Speaker 1: with our just immediate embrace of the constant smart phone culture,
Speaker 1: and this is just really going to accelerate that. And
Speaker 1: so I'm worried about the crisis of purpose that AI
Speaker 1: could bring on for people. If you really do only
Speaker 1: have to work two or three days a week, If
Speaker 1: we get our humanoid robots who are doing all the
Speaker 1: dishes for us and go in the grocery store for us,
Speaker 1: and the drones are just going to deliver all the
Speaker 1: stuff that we need, so that we never have to
Speaker 1: leave the house again. Are we really going to do
Speaker 1: something great with that time? Or are we just all
Speaker 1: gonna just completely commit the Bible to memory? Are we
Speaker 1: all going to take up pottery and painting and the violin?
Speaker 1: I don't think so. I think we're going to do
Speaker 1: a lot of really stupid stuff with all that time.
Speaker 1: We're going to get back and we start talking about
Speaker 1: that now and be ready.
Speaker 2: For it exactly.
Speaker 4: That is my last chapter, and the epilogue is on
Speaker 4: the crisis of meaning, faith, reason. What all these things
Speaker 4: are going to mean. Let's take those pieces you laid out.
Speaker 4: One dopamine loops is what that's called. Their brain scientists,
Speaker 4: neuroscientists have learned, and they are part of the tech industry,
Speaker 4: how to growth hack and our neural network, our neural
Speaker 4: network humans to be able to keep us scrolling and
Speaker 4: doom scrolling and give us that little dopamine hit, right.
Speaker 2: And so what happens is is that rewards center is triggered.
Speaker 4: And then I just keep coming back and I'm hooked
Speaker 4: almost like a drug, right, And and that becomes very
Speaker 4: very dilatorious to our to our mental health, but also
Speaker 4: our striving think about that part you were just talking about.
Speaker 4: I mean, you know, what is one of the first
Speaker 4: things that when you go to a party with your
Speaker 4: you know, your wife or your family and your or
Speaker 4: backyard barbecue, and what's the first thing you say?
Speaker 2: What do you do for a living? Right? It's part
Speaker 2: of our identity. And and if you believe in you know.
Speaker 4: Scripture and from a biblical tradition, you know, striving and
Speaker 4: working hard is part of that. You know Christian you know,
Speaker 4: the Protestant work ethic or the Judeo Christian ethic, that
Speaker 4: that has been the fulk that is the axis upon
Speaker 4: which free market capitalism was created. And finally, I think
Speaker 4: that when we know, when you leave me alone to
Speaker 4: our own devices and we don't have a sense of purpose,
Speaker 4: we don't have to get up every morning and have
Speaker 4: the structure to go out and I've got to feed
Speaker 4: my wife and my children, and We're just left to
Speaker 4: our own sort of testosterone and and without that structure
Speaker 4: around us, of the civilizational institutions, like the family structure,
Speaker 4: like work structure, and like you know, some kind of
Speaker 4: belief system, whether it's faith in God or other, we
Speaker 4: get very very very toxic, very quickly.
Speaker 2: I mean, how do you think terrorist recruitment works. Right?
Speaker 2: It prays upon testosterone fueled rage. Men who are angry.
Speaker 4: At the world and you know, don't have a lot
Speaker 4: of prospects, and therefore they go off and do horrible things.
Speaker 4: And so so this is a real, you know, societal
Speaker 4: inflection point, and you're going to talk about social disruption
Speaker 4: if this starts to scale and metastasize. Now, as it
Speaker 4: relates to the job stuff, if you do something behind
Speaker 4: a computer with repetitive task asks, you really need to
Speaker 4: be very very aware of how fast the tideline is
Speaker 4: rising around you. Number two, if what you do can
Speaker 4: be put into a workflow chain that is right for automation.
Speaker 2: There are already are workflow chains.
Speaker 4: Like Nate and n zapiar, and so those kinds of
Speaker 4: ability to step one, step two, step three, step four all.
Speaker 2: In a row that can be automated.
Speaker 4: Next, this is an interesting argument I'm starting to see
Speaker 4: emerge in the AI industry. They're looking at gender and
Speaker 4: what kind of jobs break female more disproportionately than men,
Speaker 4: and they're arguing that it could be that this could
Speaker 4: really affect democratic women more because they trend toward more
Speaker 4: of the humanities as opposed to blue collar workers who
Speaker 4: are less at risk originally, and that this could actually,
Speaker 4: you know, be a boon for blue collar workers. As
Speaker 4: the data center buildouts continue, the trade jobs of concrete
Speaker 4: pouring and drywall and hvag plumbing and electrical and all
Speaker 4: these people are booming, and that the kinds of things
Speaker 4: that are done in a repetitive setting, if we're in
Speaker 4: a sort of more of a traditional setting that affects
Speaker 4: female jobs could actually disproportionately. We're gonna have to wait
Speaker 4: and see if that happens. And then I think the
Speaker 4: final thing would be this. If you think that, oh,
Speaker 4: what I do could never be replaced, you need to
Speaker 4: look at two things. Number one, where is a gentic
Speaker 4: or agent AI in my industry? And number two, you
Speaker 4: need to look at something called MCP model Context protocol.
Speaker 2: That is a fancy way of saying how an agent
Speaker 2: is going.
Speaker 4: To get hooked to your company's context data, all of
Speaker 4: your financials, all of that asking and watching in your
Speaker 4: company or your industry.
Speaker 2: When those two pieces are.
Speaker 4: Connected, it's kind of like legos locking together. When agents
Speaker 4: and MCP start to lock together, that's when you really
Speaker 4: need to start paying attention, or if you start hearing
Speaker 4: your boss talking about these types of oh we're going
Speaker 4: to get some agents and so forth and so on,
Speaker 4: really be paying attention. I think the biggest thing I
Speaker 4: learned after spending two years living in this world very
Speaker 4: very deeply, reading thousands of articles and tons of books
Speaker 4: and so forth, is you really have to have a
Speaker 4: lot of humility because people that make bold predictions this
Speaker 4: will never happen, this will never Two weeks later it happens.
Speaker 2: And so if you think that it's hype, look at
Speaker 2: those pieces.
Speaker 4: If you think that, oh, there's no going to be
Speaker 4: no problems, I would really tell you to look at
Speaker 4: some of the literature we've been talking about as it
Speaker 4: relates to the human impact as well on individuals.
Speaker 1: Okay, Wenjin, I want to go through You alluded to
Speaker 1: some of this earlier about where we're at in terms
Speaker 1: of careers, and I want to start with one that
Speaker 1: this will be more than this career, because this will
Speaker 1: this is not just an industry, but it's also something
Speaker 1: that's a part of most of our daily lives, and
Speaker 1: that's education. This is one where I feel like I'm
Speaker 1: hoping you're going to say there's a positive that this
Speaker 1: could blow up the university and industrial complex.
Speaker 3: It could be really good.
Speaker 1: But also it's going to make cheating and laziness a
Speaker 1: lot easier for a students who are inclined to take
Speaker 1: advantage in that way. And so, but how is AI
Speaker 1: affecting and will affect education?
Speaker 2: So in my chapter in code Reata on education, what
Speaker 2: I what I do is as I do throughout the book,
Speaker 2: lay out what I call roses and land mines. And
Speaker 2: so the roses are many.
Speaker 4: I'm very hopeful about this because if you have guardrails
Speaker 4: safe with non woke curriculum baked into that AI tutor,
Speaker 4: think about how cool this is. You basically have Aristotle
Speaker 4: in your pocket for your kid. And even if that
Speaker 4: kid's an inner city kid. You know, I was a
Speaker 4: professor an instructor of college at one of.
Speaker 2: The poorest congressional districts. It was a small, tiny, little college.
Speaker 4: These are people that could not afford a two hundred
Speaker 4: and fifty dollars fancy, you know, Harvard trained tutor and
Speaker 4: all this kind of stuff.
Speaker 2: But imagine that we could give kids in.
Speaker 4: Any economic setting who have fire in the belly and
Speaker 4: a desire to learn all the kind of way to
Speaker 4: zoom as fast as they want. Machine learning allows for customization,
Speaker 4: so that it can learn your child is really good
Speaker 4: in physics, but she really struggles in algebra, or she's
Speaker 4: really good in X versus why, and then it can
Speaker 4: automatically create tests and quizzes and homework to shore up
Speaker 4: your deficiencies and be able to accelerate the child's learning
Speaker 4: in those areas where she's already advanced. You know, one
Speaker 4: of the problems in a large classroom is the teacher
Speaker 4: has to slow down for some kids and try to
Speaker 4: speed up for others, and very hard. This allows for customization,
Speaker 4: so there's a lot of opportunity there the homeschooling crowd,
Speaker 4: huge opportunity Christian education. If you bake in theologically sound,
Speaker 4: doctrinally sound curriculum into the AI the way it's built
Speaker 4: into the corpus of the information, you can have an
Speaker 4: enormous benefit for them in that. Now the flip side,
Speaker 4: of course, is a cheat GBT, not chat GBT. We
Speaker 4: know it's a massive problem. Professors and instructors are saying
Speaker 4: that the cornerstone of pedagogy, the written essay, this has
Speaker 4: been obliterated because the chat GBT, not just chat GBT.
Speaker 2: Any kind of advanced LLM that writes.
Speaker 4: All you got to do is problem say write this
Speaker 4: out an eleventh grade level, throw in some references to
Speaker 4: you know, LSU football or whatever the kid likes, and
Speaker 4: make it sound like my voice.
Speaker 2: And so that is very very real problem. So parents
Speaker 2: have got to be aware. That's why I wrote Code.
Speaker 4: Read was to really again create an alert, a code red,
Speaker 4: a red alert, but also give you the code the
Speaker 4: principles to how to get through it. And you've got
Speaker 4: to understand that the cognitive offloading and the critical thinking
Speaker 4: and erosion studies are horrifying for educational attainment because, as.
Speaker 2: You know, you compound your learning.
Speaker 4: If you've didn't learn the principles in sixth grade, by
Speaker 4: the time you get to ninth grade math or a
Speaker 4: tenth grade math or eleventh grade math, you're lost because
Speaker 4: you didn't get that building block that you needed.
Speaker 2: So so you have got to learn how to guard,
Speaker 2: you know, your child.
Speaker 4: And navigate them through those land mines and roses. And
Speaker 4: I think we've got to do it quickly because this
Speaker 4: stuff is is it's not in the.
Speaker 2: Future, it's right now.
Speaker 1: Yeah, it's right now, and I got to I'm a
Speaker 1: little excited about this part of it for me because
Speaker 1: I do feel like the you know, I've got four children,
Speaker 1: and I just think that there's no way that just mathematically,
Speaker 1: all four of them are going to want the same
Speaker 1: university experience.
Speaker 3: It doesn't even really exist, but.
Speaker 1: Kind of exists in our head, where you just you
Speaker 1: do well on the SATs and then hopefully you get
Speaker 1: into a private school on the East coast, and you
Speaker 1: go and you spend most of the time drunk or
Speaker 1: getting indoctrinated, and then you come back with a piece
Speaker 1: of paper that has almost no value. But we still
Speaker 1: do this ritual that's super expensive, and it's I'm happy
Speaker 1: that I feel like that's going to end for some
Speaker 1: of them. They won't have to go through that time waste,
Speaker 1: and that they could teach themselves or they could be
Speaker 1: taught with various programs that are just in their pocket.
Speaker 1: I think that's going to be good. But I'm also concerned,
Speaker 1: of course, about the cheating that's going to be It's
Speaker 1: going to be seen that if you're not cheating, you're
Speaker 1: falling behind sort of. If you're not cheating, you're not
Speaker 1: trying a sort of thing, and it could really institutionalize
Speaker 1: some really bad values here. And it also went in
Speaker 1: it reminds us how important it is that we make
Speaker 1: sure that it's not garbage in garbage out. That if
Speaker 1: there's a lot of garbage that's coming into the llms
Speaker 1: that are teaching our kids, then they're going to be
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Speaker 2: It's exactly right.
Speaker 4: This is taking the textbook wars that conservatives have fought
Speaker 4: for decades and the woke professor and bias on steroids,
Speaker 4: and you're going to continue to see that. I think
Speaker 4: it will have a real shock though, to that, you know,
Speaker 4: a feat left intelligentsia that is so proud of their
Speaker 4: you know, two hundred and fifty thousand dollars degrees and
Speaker 4: they're you know, woke studies when they realize the price
Speaker 4: of intelligence is.
Speaker 2: Going to zero.
Speaker 4: All that quote expertise is now one prompt the way
Speaker 4: that a kid who's ten years old sitting on a
Speaker 4: playground is going to have access to And I think.
Speaker 2: One of the benefits of AI and this, and I
Speaker 2: go through this very deeply.
Speaker 4: In fact, I actually give you kind of the prompts
Speaker 4: that will help your to be able to do this.
Speaker 4: One of the biggest, most simple but powerful in the
Speaker 4: education space is the explain this to me like I'm
Speaker 4: in the fifth grade prompt.
Speaker 3: Yeah, I love that, I love this.
Speaker 1: Yeah, we didn't pose is a really tough question about
Speaker 1: quantum physics, and he is the additionally answer is gobbledygook.
Speaker 1: But then you say explains to me like I'm in
Speaker 1: the third grade, and it gives a great analogy on
Speaker 1: how that makes perfect sense.
Speaker 4: And it's so good for parents, because how many of
Speaker 4: us get these amazing, these little, beautiful minds of our
Speaker 4: beautiful children, and they ask these a great question.
Speaker 2: And then you know, we look at our wife or
Speaker 2: our our husband and you.
Speaker 4: Kind of go, man, I don't know what qui future,
Speaker 4: you know, whatever the topic is, And and then if
Speaker 4: you go to Google, it gives you all these you know,
Speaker 4: peer reviewed academic journals that are just as hard to understand.
Speaker 4: This is translating now, assuming it's accurate, right, And that's
Speaker 4: why hallucinations matter.
Speaker 2: These things are going to be a game changer.
Speaker 4: The flattening of the oh, I'm a you know, five
Speaker 4: time PhD and you know, women's studies whatever and such,
Speaker 4: that is going to be a flattener. The ability for
Speaker 4: low income kids in rural communities to have world class education,
Speaker 4: that is going to be a benefit. There are a
Speaker 4: lot of roses, and that's why in the book, I
Speaker 4: really try to show the hopeful positives as well as
Speaker 4: these real threat vectors.
Speaker 1: Right, Okay, let's talk about a place where I'm excited,
Speaker 1: which is medicine. This is of course my wife Field
Speaker 1: and most of her family. But it feels like AI
Speaker 1: medicine could make it so that we have a great
Speaker 1: tool for doctors and we might need fewer doctors potentially,
Speaker 1: and we could see really rapid advancement in the desire
Speaker 1: to try to cure disease and help us live longer.
Speaker 2: It's one of the things I am actually very optimistic about.
Speaker 4: And I say it in the opening of You know
Speaker 4: my Dad and my stepmom. My dad is a surgeon
Speaker 4: now retired. My stepmom also retired to nurse. My mom
Speaker 4: was a preschool teacher. So I think we just talked
Speaker 4: about the educ hopeful I think the science and medicine.
Speaker 4: I know your wife is a doctor, that is a
Speaker 4: very exciting area, assuming again.
Speaker 2: The ethics are you know, and you know there beyond
Speaker 2: the way it's used. The reason why is a couple
Speaker 2: of things.
Speaker 4: One we've already seen the Nobel given for Demis Hocipas,
Speaker 4: who is a world class AI leader for Alpha fold,
Speaker 4: which was looking at proteins. The reason why this is
Speaker 4: so powerful AI excels in pattern recognition. If somebody said
Speaker 4: you only have you know, two words to explain what
Speaker 4: it does. Pattern recognition. Now think about molecular structures, chemical structures,
Speaker 4: the scientific world.
Speaker 2: It is about patterns and connection.
Speaker 4: And the problem is is that we can't get through,
Speaker 4: you know, whether you're talking about DNA analysis or any
Speaker 4: other kind of thing, massive massive power pattern recognition structures.
Speaker 2: But now we can.
Speaker 4: The other thing is there's so many things that peer
Speaker 4: reviewed academic journal studies have gone through, but we didn't
Speaker 4: see another connecting point because it gets lost in these.
Speaker 2: Trillions of data points.
Speaker 4: Think of it like the stars in the sky, and
Speaker 4: now you can see new constellations than connections that never
Speaker 4: used to be able to be seen because either we
Speaker 4: didn't have the time, we didn't have the money, we
Speaker 4: didn't have the ability to be able to synthesize all
Speaker 4: that information. Even if you just leave it at that,
Speaker 4: and you don't have to believe that it's going to
Speaker 4: become sentient, or you don't have to believe that it's
Speaker 4: going to have some kind of you know, soul or whatever.
Speaker 4: Just pattern recognition at scale is going to unlock an
Speaker 4: enormous amount of scientific and medical possibility. So I am
Speaker 4: hopeful about that one thing that you know, where this
Speaker 4: gets a little murky is in this whole issue of
Speaker 4: you know, neulink and you know brain chips and implants.
Speaker 4: Because what people say is when you go to transhumanism,
Speaker 4: meaning beyond just human trends, transform beyond humans, this merger
Speaker 4: and the singularity between human and machine. Parents are gonna
Speaker 4: perhaps one day, this probably not for a while. Have
Speaker 4: to make a moral choice if I don't have a
Speaker 4: you know, an augmentated child with a neurallink, will they
Speaker 4: even be competitive in the job market?
Speaker 2: Will they even be competitive as a worker or in education?
Speaker 4: If one kid is natural human up against a kid
Speaker 4: who has literally all of AI in their system.
Speaker 2: This isn't some movie. I mean, neurallink is a real thing.
Speaker 2: It's here now.
Speaker 4: It's used mostly in a therapeutic context right now to
Speaker 4: help people who've had brain injuries and so forth.
Speaker 2: But these are the kinds of things that you know,
Speaker 2: Ray Kurzwell and others really futurists talk about and really
Speaker 2: bring up massive moral and ethical quandaries for us. So
Speaker 2: there again roses and land mines.
Speaker 1: And this is exactly where I want to end up
Speaker 1: for this conversation. Is I want to talk about the
Speaker 1: Singularity and talking about the transhumanism where humans are going
Speaker 1: to be part robot, and I find that the ethical
Speaker 1: questions is raises are limitless. I mean, I feel like
Speaker 1: we can spend hours of flashing all of those out,
Speaker 1: but you raise some of that is a deep concern
Speaker 1: to me that you will be non competitive unless you
Speaker 1: harness your brain to a robot chip of some sort.
Speaker 1: And all of a sudden it comes that what is
Speaker 1: the human experience anyway? What is it supposed to be?
Speaker 1: Do we really want our brains being manipulated by robots?
Speaker 3: And how do we know?
Speaker 1: How will we ever feel confident where the human ends
Speaker 1: and where the robot begins? And you can already see
Speaker 1: that this is going to be adopted to some degree
Speaker 1: because we have these things where which is basically a
Speaker 1: really you know, a one point zero version of the singularity,
Speaker 1: that we constantly have our phones around and they're as
Speaker 1: you write in the book, we spend the whole day
Speaker 1: with them in arms reach, like they're not without arms
Speaker 1: reached the entire day. And this is true even for me,
Speaker 1: who has a deep desire to get off my phone.
Speaker 1: The first thing I do when I'm off of work
Speaker 1: mode is generally all put in a podcast or an audiobooks,
Speaker 1: like or I'm working out and I'm listening to some
Speaker 1: music or audiobook or something, and.
Speaker 3: So it's all of us.
Speaker 1: We're all doing it, even people who try to make
Speaker 1: a conscious effort not to do it. So I'm really
Speaker 1: concerned about some of this stuff. This isn't clanker robots
Speaker 1: in our house that are kind of creepy washing the
Speaker 1: dishes for us. This is our brain that we're going
Speaker 1: to be part robot at some point. Perhaps it's really
Speaker 1: crazy to contemplate, Alex.
Speaker 4: One of the most embarrassing and humiliating moments of my
Speaker 4: week is you know when your iPhone periodically says, here's
Speaker 4: the average number of hours you've spent on your.
Speaker 3: Phone this week. It's so embarrassing.
Speaker 2: It's so embarrassing because you just say, this is not
Speaker 2: what I wanted. I didn't want to look at a screen.
Speaker 2: I wanted to look at the sky and eyes and
Speaker 2: my my you know, family and my friends and all
Speaker 2: my people.
Speaker 1: Well, can I tell you I had I took my
Speaker 1: ca it's to swimming and they're small, so the swimming
Speaker 1: is thirty minutes. It's kind of far away, So it's
Speaker 1: a maybe like doorder dover like seventy five minutes. And
Speaker 1: I left my phone recently, And I've been telling this
Speaker 1: story to people, like over and over again, I left
Speaker 1: my phone for seventy five minutes, and how I really
Speaker 1: enjoyed it.
Speaker 3: But the fact that I.
Speaker 1: Feel the need to repeat it to everyone that I
Speaker 1: had seventy five minutes free of the phone three weeks
Speaker 1: ago once, I mean, it just shows you about it already.
Speaker 2: Is it's a great triumph.
Speaker 4: Yeah, And I say that, I mean, you're right that
Speaker 4: section you're talking about in the book where I say,
Speaker 4: you know, like how many of us if we were
Speaker 4: going on a family vacation and you forgot your phone
Speaker 4: or even going you know, to dinner, you would turn
Speaker 4: your car around to.
Speaker 2: Get your phone. What I suggest, and what I say is.
Speaker 4: That is a form of a early part of a
Speaker 4: cyborg reality, because it really is, our phone is connected
Speaker 4: to us almost constantly. And so you know, it's an
Speaker 4: interesting theoretical debate. Right when you say, okay, the singularity
Speaker 4: fusion of human machine and it sounds like you're talking
Speaker 4: about a terminator robot, but really start to think it's
Speaker 4: a very humbling thing when you really say, wait a minute,
Speaker 4: am I already kind of getting there? Like don't I
Speaker 4: look and have my phone attached to my human body
Speaker 4: almost all the time.
Speaker 2: So that's the first part of it. The second part
Speaker 2: of it, though, is is that this this neural.
Speaker 4: You know, chip stuff, the discussion we're just talking about
Speaker 4: not just neuralink, but that whole area is advancing very
Speaker 4: very rapidly.
Speaker 2: That is that does not far away.
Speaker 4: The other thing is with AI glasses, which is think
Speaker 4: about this, you know, with the ray bands that you
Speaker 4: now have from Meta. Now, that's an external AI fusion
Speaker 4: with your body. It's not putting it inside your body.
Speaker 2: You're wearing it.
Speaker 4: But think about the power of this and and those
Speaker 4: in the in AI fraudsters, in crime, this is a
Speaker 4: real problem.
Speaker 2: I can put.
Speaker 4: Facial recognition in what looks just like regular glasses.
Speaker 2: I can walk down downtown, you know, Manhattan or your city,
Speaker 2: wherever you are.
Speaker 4: I can see a total stranger and it can identify
Speaker 4: her name, who she is, look up everything, and I
Speaker 4: can walk up as though we're long lost friends. She
Speaker 4: doesn't remember, Oh, Sally, I haven't seen you since high school.
Speaker 2: However you been are you still working.
Speaker 4: At inter name of you know, play, and that becomes
Speaker 4: a real danger and a real fraud mechanism.
Speaker 2: AI fraud and crime is a massive topic and a
Speaker 2: huge problem with data privacy.
Speaker 4: So so that external ability to wear your wearables as
Speaker 4: it's called wearables in AI is the next part as
Speaker 4: we inch closer toward this transhuman fusion of machine, the
Speaker 4: singularity of humans and machines merging. So you know, when
Speaker 4: you hear that, it sounds like it's some crazy, kooky
Speaker 4: kind of you know, sci fi thing. It's here and
Speaker 4: it's getting closer. So what you're you know, first it
Speaker 4: was our phone, then it's a wearable. You're already working
Speaker 4: on the internal stuff. And then if you do that, well,
Speaker 4: am I going to be able to be competitive? When
Speaker 4: you know, twenty people in my company have an AI
Speaker 4: chip and they're an executive c suite leadership because they've
Speaker 4: got speed and efficiency and knowledge that my human brain
Speaker 4: could never compete with.
Speaker 2: This is why I wrote code Read because this is
Speaker 2: all where it's going, and you got to understand all
Speaker 2: these different fault lines, all these different pressure points so
Speaker 2: that you can get yourself through this for you and
Speaker 2: your kids. But I will tell you the speed is
Speaker 2: what is freaking everybody out.
Speaker 4: You know, in the Industrial Revolution, the Industrial Revolution, you
Speaker 4: know you electricity, it took decades to wire the country, right,
Speaker 4: I mean, you know, or to pave the roads for
Speaker 4: the inner interstates. And I go through the history of that,
Speaker 4: I cite the time I show you all that. The
Speaker 4: reason why AI is different. Ninety one percent of people
Speaker 4: in America already have a phone, which is the delivery
Speaker 4: device of AI. So once you got that delivery device
Speaker 4: already baked in, the lightning speed with which you can
Speaker 4: make sure that that scales is very different than what
Speaker 4: we saw in the Industrial Revolution, So you could you
Speaker 4: had decades to sort of get used to and you know,
Speaker 4: upskill your skills and kind of learn how as factory
Speaker 4: and mechanization and all the you know, factory assemblies and
Speaker 4: so on.
Speaker 2: Now this is moving so fast. If you're not ahead,
Speaker 2: you're behind, and you've got to stay ahead. And that's
Speaker 2: again why you know the name of code read of
Speaker 2: this sort of alarm or alert.
Speaker 1: Well, we have not covered the waterfront here. We have
Speaker 1: not gotten into AI defense, which again could turn out
Speaker 1: to be a positive though with a lot of risk.
Speaker 3: Factors.
Speaker 1: I do want to get your opinions on AI Jesus,
Speaker 1: which we're seeing some AI Jesus pop up, we're seeing
Speaker 1: AI George Washington. I'm want to get your thoughts on
Speaker 1: some of that. And there's just a number of things
Speaker 1: that I feel like are both opportunities and are real
Speaker 1: deep risks about the moment that we're in with AI.
Speaker 1: But I will encourage everyone in the meantime to pick
Speaker 1: up a copy of Code Read and it is one
Speaker 1: of the books of the year, about the book of
Speaker 1: the year I think so far, and you will want
Speaker 1: to read it. You will probably want to share this
Speaker 1: with someone who you think might be in one of
Speaker 1: these industries that could see a lot of upheaval. This
Speaker 1: book might provide them comfort, it might scare them into
Speaker 1: doing something that.
Speaker 3: Could be productive for their lives.
Speaker 1: So it's a really essential This is an essential text
Speaker 1: from Winton Hall, who isn't just a friend, but is
Speaker 1: a brilliant person, as you guys have gotten to witness
Speaker 1: here of the last hour and a half. We're going
Speaker 1: to do this again Winton, probably sooner rather than later.
Speaker 1: So there's a lot more to do, I think on
Speaker 1: this subject matter. I really want you to introduce everyone
Speaker 1: to all the players in the space, both in terms
Speaker 1: of the companies and the individuals and where they're coming from,
Speaker 1: because they're going to be so involved in shaping our future.
Speaker 1: But if we opt out on this thing, this will
Speaker 1: be my final word. Then I'll give you the last word, Winton.
Speaker 1: If we opt out, then we are seeding the future
Speaker 1: to the masters of the universe only and the really activated,
Speaker 1: generally left of center entrepreneurial class that I feel like
Speaker 1: is a deep, deep risk. And so we got to
Speaker 1: get involved. And Winton is he's inviting you in showing
Speaker 1: you the water can be warm. I'm not saying it's
Speaker 1: the warmest ever, but it can be warm for you.
Speaker 3: Joe, you got to start. This is a great entry
Speaker 3: point into this book.
Speaker 1: And of course, when you spend two years on something
Speaker 1: like this, even if you feel like you know AI,
Speaker 1: you're gonna learn a lot too. I think from just
Speaker 1: hearing Wynton's perspective on all these things. But what did
Speaker 1: anything you want to leave the audience with for now?
Speaker 4: Oh, I thank you so much for that, and especially
Speaker 4: coming from an author like yourself, I will say this,
Speaker 4: you can learn this. Don't be afraid to think, oh,
Speaker 4: this is so complex and it's so beyond my understanding.
Speaker 4: The reason I wrote this is to be simple without simplistic,
Speaker 4: really to help people.
Speaker 2: Like I said, I didn't even want to write this book.
Speaker 2: I have a wonderful career and I love what I do.
Speaker 4: I felt like I needed to do this because I
Speaker 4: wanted to be a story I know how to be
Speaker 4: a storyteller, so I wanted to help people to really
Speaker 4: understand this.
Speaker 2: You don't have to have a specialized knowledge.
Speaker 4: I think most of you are going to find this
Speaker 4: is way more fascinating than you ever realized it was,
Speaker 4: and also consequential. I really think that we don't need
Speaker 4: to get into a doom loop. We don't need to
Speaker 4: just unilaterally disarm, certainly not conservatives.
Speaker 2: That that would be I think a disaster. I think
Speaker 2: we need to lean in. We need to lead, We
Speaker 2: need to get prepared.
Speaker 4: We need to know how to do what we always do,
Speaker 4: which is, you know, take personal responsibility for our family
Speaker 4: and for our communities and for our country, and make
Speaker 4: sure that we're ready to rock and roll with this
Speaker 4: and know how to be able to get the upside
Speaker 4: and avert the negative. But I think it's actually going
Speaker 4: to be a really important thing for you to do that,
Speaker 4: and I think you'll feel a lot more confident because
Speaker 4: I think so much of it is just fear, and
Speaker 4: people don't really know what's true and.
Speaker 2: What's hype and what's what's myth. So that's that's why
Speaker 2: I wrote Code Rat and I hope you enjoy it.
Speaker 3: And you will enjoy it. You will learn a lot.
Speaker 1: You are going to a really interesting world when you
Speaker 1: take on this book, but it's where we're all going to.
Speaker 1: Anyone she may as well be prepared. Thank you, Wenchen Haul,
Speaker 1: Thanks for Misty for putting this together, and all of
Speaker 1: you in the audience for telling ten thousand friends and
Speaker 1: family members about all the cool stuff we're doing on
Speaker 1: the Marlow Show. Make sure to subscribe. If you're not subscribed,
Speaker 1: please and I'll talk to you next time.