ReadMultiplex.com: You Have 5000 Days: Navigating the End of Work as We Know It. Part 20: Your Rural CyberCab Company.

WEBVTT
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Imagine just for a second that you're looking
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at the rapidly shifting technological landscape
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right now. Right. And instead of feeling completely
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overwhelmed, you actually see a completely clear
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path forward. Yeah. A roadmap. Exactly. Imagine
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becoming a multiple business owner in this new
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era. Yeah. Not by raising, you know, millions
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in venture capital. Or working a hundred hour
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week. Right. Not with some massive corporate
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backing. Yeah. But by starting with a down payment
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of just $6 ,000. Which sounds completely wild
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on the surface. It sounds like pure science fiction.
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Or maybe some late night infomercial you'd scroll
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past at 2 a .m. Yeah. But today, we're going
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to walk you through exactly how that mathematical
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reality could play out. So welcome to our deep
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dive. Glad to be here for this one. Today, we're
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looking at something truly special. This is the
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Reed Multiplex material. And we're pulling from
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an incredibly detailed article, specifically
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part 19 of the 5 ,000 Day Series, at reedmultiplex
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.com. It's a genuinely remarkable road map to
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dive into because we spend so much time analyzing
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different visions of the future. And so often
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the prevailing narrative you see everywhere leans
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heavily toward, well. Oh, massive pessimism.
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Right. We're constantly told that emerging technology
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is going to replace us, displace us or just make
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life generally harder. But the material we have
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today operates on a completely different, highly
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pragmatic frequency. It's the complete opposite
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of that doom and gloom. We are cooked mentality
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that you see floating around Reddit and social
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media right now. Absolutely. The author of this
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series, Brian, delivers these lifelong practical
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ways to not just survive the upcoming technology.
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shifts, but to absolutely thrive in them. And
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for the listener, I think it's vital to provide
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some context on why we take these numbers so
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seriously. Yeah, Brian isn't just theorizing
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from a basement somewhere. No, not at all. He's
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been in the top 100 of the fastest growing companies
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on the INC 500. Which is huge. It is. And he's
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been signing up hundreds of thousands of merchants
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for credit card processing since 1986. Since
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86. So, okay, let's unpack this. The mission
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for our deep dive today is to explore the exact
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economics, the scalable frameworks, and the genuinely
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surprising global use cases of the Tesla cybercap.
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But we need to make sure we're not just looking
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at it as a car. Right. If you take away anything
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today... It's that you need to stop thinking
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of this thing as a car. Yeah, that's a trap.
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We're evaluating an autonomous, wealth -generating
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robot that could serve as your ultimate vehicle,
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literally and figuratively, for financial independence.
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Because the core premise here is that in this
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period we're entering, which the author calls
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the interregnum, you have the potential to become
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a multiple business owner by running operations
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on as little as six grand. And that word interregnum.
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We should probably define that for the listener
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before we go further. We should. The concept
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of the interregnum is the absolute foundation
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of everything we're going to discuss today. Historically,
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an interregnum is a period of discontinuity.
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Like a gap between kings. Exactly. A gap between
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reigns or regimes. In this context, it refers
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to this very specific transitional period we
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are living through right now. The gap between...
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Human effort, as we've historically understood
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it, where you trade your physical time for wages
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and the fully realized capabilities of emerging
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machine intelligence. What is so striking about
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Brian's framework is how it takes these grand,
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sweeping technological concepts like artificial
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intelligence, battery tech, robotics, and distills
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them into a tangible, executable spreadsheet.
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It asks you to view this transition not as a
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spectator, but as an active participant. Right.
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You aren't just watching the robots take over.
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You are owning the capital. Yes. Let's start
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where the analysis starts, the historical context.
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Right. Because you really cannot appreciate where
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we're going without looking at where we've been.
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And how fundamentally broken the current model
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of transportation ownership actually is. So broken.
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To understand the magnitude of the shift to autonomous
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capital, we have to look back at the late 19th
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and early 20th centuries. The shift from horse
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-drawn carriages to mechanized mobility. Led
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by pioneers like Carl Benz and Henry Ford, it
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was arguably one of the most significant economic
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catalysts in human history. Without a doubt.
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Think about what the Model T did. It didn't just
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get people from point A to point B faster. It
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fueled massive economic expansion. It created
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the modern suburb. It drove urban development.
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And it connected local economies in ways that
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were previously... unimaginable but there's been
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a massive century -old problem with this model
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that we've all just collectively accepted as
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a necessary evil yeah for over a hundred years
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cars have been the ultimate depreciating tools
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they are arguably the most inefficient major
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capital allocation the average person makes in
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their lifetime. I mean, they demand constant
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human involvement. You have to drive them. You
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have to maintain them. You have to insure them.
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And statistically, this always gets me, they
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sit idle, parked, and doing absolutely nothing
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for about 95 % of their usable lifespan. All
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the while, they are losing value. I always think
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back to my early 20s. I saved up for months to
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buy this slightly used sedan. I was so proud
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of it. But the second I drove it off a lot, I
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felt this invisible clock ticking. Every mile
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I put on it, every scratch, it was just hemorrhaging
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money. Traditional car ownership right now is
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basically like buying a very expensive, rapidly
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depreciating lawnmower that you have to push
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yourself. That is the perfect way to put it.
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You do all the physical work, you pay for the
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gas, you pay for the maintenance, and the machine
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loses value every single day. What's fascinating
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here is the philosophical shift away from that
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exact trap. We are moving from a passive depreciating
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tool to an active network system. OK. Break that
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down. Well, for a century, a vehicle was simply
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a mechanical object that required your physical
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labor and consumed your time. The paradigm shift
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introduced by the cyber cab developed under Elon
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Musk at Tesla is that the vehicle is no longer
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just a mode of transport. Right. It is fundamentally
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an autonomous robot equipped with wheels. And
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the physical description of this thing. really
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hammers home how different it is from the sedan
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I bought in my 20s. I mean, it lacks traditional
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controls entirely. No steering wheel. No pedals.
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You couldn't drive it yourself even if you wanted
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to. It relies purely on data from cameras, sensors,
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and cloud -based AI to maneuver through varied
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environments. Exactly. It's engineered specifically
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for operation without human intervention. This
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is achieved through the integration of massive
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compute power, artificial intelligence, battery
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technology, and robotics. The full self -driving.
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Yes. The FSD software, which is driven by neural
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networks designed to replicate and, crucially,
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to exceed human decision -making in accuracy,
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reaction time, and consistency. So to go back
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to that lawnmower analogy, owning a cyber cab
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is no longer like buying a push mower. It's like
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buying a highly sophisticated robotic landscaper.
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Right. But instead of just mowing your own lawn,
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this robot goes out into the neighborhood and
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mows your neighbor's lawns for cash while you
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sit inside and watch TV. And while you're at
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your day job. Or sleeping. It works tirelessly.
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And that is the bridge between the industrial
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era we've known and a future dominated by intelligent
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machines. Mobility is shifting to being managed
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by algorithms that prioritize safety, efficiency
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and economic empowerment. Sure, an individual
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might buy a cyber cab just for their own personal
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use to get to work. But the real innovation,
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the actual wealth generating mechanism we are
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here to discuss, is allowing that vehicle to
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operate independently within a networked system,
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transporting passengers or goods continuously.
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OK, this is the part I am most excited about.
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Because we're going to get into the real math
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of a robot fleet. Let's do it. And if you're
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listening, we are going to break these numbers
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down slowly and clearly. We aren't going to just
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dump a spreadsheet on you. No, that wouldn't
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be helpful. We want to evaluate this baseline
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exactly as Reed Multiplex lays it out, because
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this is the foundation of the entire interregnum
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blueprint. So let's start with the hard costs.
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Yeah, you want to buy one of these autonomous
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robots. What's the damage? Let's look at the
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baseline assumptions, and they are starting incredibly
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conservatively here. The initial cost of the
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vehicle itself is projected at approximately
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$30 ,000. Which, just to pause right there, is
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wild. It is. The average cost of a new car in
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America today is hovering around $48 ,000. So
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we are starting with an asset that is significantly
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cheaper than a standard new SUV. Correct. But
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the physical vehicle is only half the equation.
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Right. You also need the brain to operate it
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autonomously. The model includes a $199 per month
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subscription for the full self -driving software.
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Okay, so $30 ,000 up front, or financed, plus
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$200 a month for the AI driver. Now, how does
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it actually make money? It plugs into a ride
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-hailing network. But the network operator, the
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platform that manages the app, routes the rides,
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and handles the customer interface, takes a cut.
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Makes sense. In this base case, the assumption
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is that the network takes a 35 % cut of the gross
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ride revenues. 35%. That feels high, but I guess
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it's roughly in line with what Uber or Lyft might
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take from a human driver today. Maybe a bit more
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to cover the autonomous infrastructure. That's
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a fair comparison. And what are we charting the
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passengers in this model? Again, the estimates
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here are very conservative. They assume a $1
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base rate just to get in the car, plus $1 for
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every mile driven. Okay. They assume average
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trips are about five miles, traveling at an average
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speed of 25 miles per hour in a standard urban
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or suburban environment. And fuel. The cost to
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fuel the robot, the electricity, is estimated
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at 16 cents per kilowatt hour for charging. Okay,
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so a passenger requests a ride. The car picks
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them up, drives five miles at 25 miles an hour
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and charges them roughly six bucks. Right. The
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network takes 35 percent of that and you keep
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the rest to cover your electricity and other
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costs. Exactly. But here is the most important
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variable in this entire equation. The one thing
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that dictates whether you make money or lose
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your shirt. Yes. The utilization rate. Let's
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define that. This is the crucial metric. It's
00:10:19.809 --> 00:10:21.690
defined as the percentage of time the vehicle
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is actively in service, generating revenue over
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a 24 -hour period. Let's walk through the base
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case scenario. The author assumes a 30 % utilization
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rate. That accords to the vehicle actively working
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and carrying paying passengers for 7 .2 hours
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a day, covering roughly 157 miles daily. Under
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this 30 % utilization scenario, after the network
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operator takes their 35 % share off the top,
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the vehicle generates approximately $32 ,000
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in annual revenue for the owner. Okay, $32 ,000
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a year. That sounds fantastic for doing absolutely
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nothing but owning the car. It does. But revenue
00:11:02.399 --> 00:11:05.000
is vanity, profit is sanity. We need to look
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at the expenses. Because those 157 miles a day
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poured wear and tear on the asset. Absolutely.
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Let's break down the deductions exactly as they're
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mapped out because I want you to see how tight
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the margins are at this foundational level. It
00:11:17.629 --> 00:11:19.889
is a capital -intensive business at the unit
00:11:19.889 --> 00:11:22.610
level. First, you have the financing of the vehicle
00:11:22.610 --> 00:11:26.149
itself. Assuming a 6 % interest rate, the model
00:11:26.149 --> 00:11:30.110
calculates a $1 ,500 monthly payment over a standard
00:11:30.110 --> 00:11:33.470
five -year loan term. So that's $18 ,000 a year
00:11:33.470 --> 00:11:35.799
right there just to pay off the robot. Then you
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have commercial insurance, which is estimated
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at $1 ,200 annually. Got it. Next, we have to
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calculate the variable per mile costs. The more
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it drives, the more these add up. Maintenance
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is pegged at 5 cents per mile. Okay. Tires, which
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electric vehicles tend to wear through slightly
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faster due to their weight and torque, are calculated
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at 2 cents per mile. And we can't forget the
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human element. The robot drives itself, but it
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can't scrub the back seat if a passenger spills
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their coffee. True. Cleaning. is factored in
00:12:05.789 --> 00:12:08.830
at one cent per mile. Finally, the model applies
00:12:08.830 --> 00:12:12.350
a standard 20 % tax rate on the operating profits.
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Okay, let's do the math on all of that. Yeah.
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You start with the $32 ,000 in revenue. You subtract
00:12:17.610 --> 00:12:21.090
the $18 ,000 for financing, the $1 ,200 for insurance,
00:12:21.429 --> 00:12:23.990
and the thousands of dollars for the variable
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per mile costs of maintenance, tires, and cleaning.
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Right. That leaves you with a gross profit of
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roughly $14 ,000 per year. Then the government
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takes their 20 % cut for taxes. Your bottom line
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take -home debt income in this 30 % utilization
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base case is approximately $8 ,000 per year.
00:12:44.330 --> 00:12:46.950
And this is where we need to pause and contextualize.
00:12:47.029 --> 00:12:49.750
If we connect this to the bigger picture, analyzing
00:12:49.750 --> 00:12:53.740
that $8 ,000 net income... is vital. I'll be
00:12:53.740 --> 00:12:55.899
honest my initial reaction to $8 ,000 a year
00:12:55.899 --> 00:12:58.700
is it's fine. It's modest. Yeah it pays for groceries
00:12:58.700 --> 00:13:01.340
maybe a nice family vacation. Right. But it doesn't
00:13:01.340 --> 00:13:04.559
exactly scream financial independence or multiple
00:13:04.559 --> 00:13:07.500
business owner. Right. It feels like a very modest
00:13:07.500 --> 00:13:10.539
side hustle. The margins are incredibly tight.
00:13:10.889 --> 00:13:12.889
Between the loan, the wear and tear, and the
00:13:12.889 --> 00:13:15.929
operator's 35 % cut, a massive chunk of that
00:13:15.929 --> 00:13:17.909
revenue is eaten up before it ever hits my bank
00:13:17.909 --> 00:13:20.269
account. Why is this considered such a massive
00:13:20.269 --> 00:13:23.110
paradigm shift if it's only netting me $8 ,000?
00:13:23.169 --> 00:13:26.750
It is a fair reaction. On the surface, $8 ,000
00:13:26.750 --> 00:13:29.250
doesn't sound like a staggering sum of wealth.
00:13:29.549 --> 00:13:31.710
But you have to look at the nature of the income,
00:13:31.889 --> 00:13:34.669
not just the gross amount. What you are fundamentally
00:13:34.669 --> 00:13:38.809
purchasing here is an untiring asset. This is
00:13:38.809 --> 00:13:42.549
a machine generating $8 ,000 of pure passive
00:13:42.549 --> 00:13:46.190
after -tax net income per year without requiring
00:13:46.190 --> 00:13:48.769
your physical labor. Right. I'm not the one driving
00:13:48.769 --> 00:13:51.429
the 157 miles a day. I'm not sitting in traffic.
00:13:51.629 --> 00:13:54.730
Exactly. The true value lies not in the immediate
00:13:54.730 --> 00:13:57.370
cash windfall of a single unit operating at a
00:13:57.370 --> 00:14:00.549
relatively low utilization rate, but in the structural
00:14:00.549 --> 00:14:03.549
nature of that income. It's detached. It is entirely
00:14:03.549 --> 00:14:05.529
detached from your personal time constraints.
00:14:05.710 --> 00:14:07.690
If you wanted to make an extra... eight thousand
00:14:07.690 --> 00:14:10.029
dollars driving for uber today you would have
00:14:10.029 --> 00:14:12.690
to physically sit in the driver's seat for hundreds
00:14:12.690 --> 00:14:15.649
of hours yeah you'd be exhausted this asset divorces
00:14:15.649 --> 00:14:18.029
your earning potential from the biological limits
00:14:18.029 --> 00:14:20.889
of your own wakefulness and stamina okay that
00:14:20.889 --> 00:14:22.950
makes sense it's the difference between active
00:14:22.950 --> 00:14:25.809
labor and capital ownership exactly but still
00:14:25.809 --> 00:14:28.370
eight grand is eight grand here is where it gets
00:14:28.370 --> 00:14:31.159
really interesting though Because you aren't
00:14:31.159 --> 00:14:33.799
the one driving, you aren't limited by federal
00:14:33.799 --> 00:14:36.360
regulations on how many hours a driver can operate.
00:14:36.539 --> 00:14:38.740
Right. You don't get tired. The robot doesn't
00:14:38.740 --> 00:14:41.419
need to sleep. Let's look at how tweaking that
00:14:41.419 --> 00:14:44.360
utilization rate radically changes the math.
00:14:44.679 --> 00:14:46.799
Let's turn the dial up and see what happens when
00:14:46.799 --> 00:14:48.879
this robot really gets to work. This is where
00:14:48.879 --> 00:14:52.200
the leverage inherent in autonomous assets becomes
00:14:52.200 --> 00:14:55.919
clear. Let's scale it up to a 65 % utilization
00:14:55.919 --> 00:14:59.279
rate. So instead of working 7 .2 hours a day,
00:14:59.639 --> 00:15:02.659
The car is out there hustling for 15 .6 hours
00:15:02.659 --> 00:15:05.039
a day. Yes. It's doing the morning commute rush,
00:15:05.259 --> 00:15:08.019
the lunchtime runs, the evening dinner crowd,
00:15:08.179 --> 00:15:10.860
and the late night bar pickups. Precisely. Under
00:15:10.860 --> 00:15:14.860
a 65 % utilization scenario, the revenues after
00:15:14.860 --> 00:15:17.740
the operator takes their 35 % cut jump dramatically
00:15:17.740 --> 00:15:21.919
from $32 ,000 to $70 ,000 annually. And because
00:15:21.919 --> 00:15:25.779
your fixed costs like the $1 ,500 monthly financing
00:15:25.779 --> 00:15:28.480
payment and the insurance, remain exactly the
00:15:28.480 --> 00:15:31.480
same, your margins expand beautifully. Right,
00:15:31.539 --> 00:15:33.620
you're only paying more for the variable per
00:15:33.620 --> 00:15:36.159
mile costs, like tires and electricity. Using
00:15:36.159 --> 00:15:38.700
the exact same expense structure we just talked
00:15:38.700 --> 00:15:43.000
about, your gross profits exceed $40 ,000. And
00:15:43.000 --> 00:15:45.399
your after -tax net income hits approximately
00:15:45.399 --> 00:15:50.000
$26 ,000 per year for one car. This raises an
00:15:50.000 --> 00:15:51.960
important question for anyone evaluating this
00:15:51.960 --> 00:15:55.450
model. How do you achieve and maintain that operational
00:15:55.450 --> 00:15:58.389
efficiency? Yeah, going from 8 to 26 is huge.
00:15:58.649 --> 00:16:02.370
The leap from 8 ,000 to 26 ,000 in net income
00:16:02.370 --> 00:16:04.990
demonstrates how sensitive this equation is.
00:16:05.149 --> 00:16:07.669
And Reed Multiplex further refines this by noting
00:16:07.669 --> 00:16:10.070
that altering other micro variables can elevate
00:16:10.070 --> 00:16:12.450
outcomes even more. Right. The environment matters
00:16:12.450 --> 00:16:14.909
just as much as the hours. Exactly. For instance,
00:16:15.049 --> 00:16:17.509
what if you operate in a dense urban core where
00:16:17.509 --> 00:16:19.990
the average speed drops to 15 miles per hour
00:16:19.990 --> 00:16:22.269
due to traffic, but the trips shorten to 30?
00:16:22.250 --> 00:16:24.710
miles and demand allows the base fare to increase
00:16:24.710 --> 00:16:28.429
slightly to $1 .50 or $2 per mile. It changes
00:16:28.429 --> 00:16:30.809
everything. In those adjusted models, the annual
00:16:30.809 --> 00:16:34.090
net profits per vehicle can fluctuate wildly,
00:16:34.289 --> 00:16:38.809
ranging anywhere from 8 ,500 up to 39 ,000. Wow.
00:16:39.029 --> 00:16:42.769
It is a highly dynamic system where small adjustments
00:16:42.769 --> 00:16:46.070
in utilization, local traffic patterns, or surge
00:16:46.070 --> 00:16:49.210
pricing yield disproportionate increases in net
00:16:49.210 --> 00:16:51.669
profit. And we have to talk about the absolute
00:16:51.669 --> 00:16:53.909
best case scenario presented in the analysis
00:16:53.909 --> 00:16:56.769
because it really highlights the ceiling of this
00:16:56.769 --> 00:16:58.950
technology in high demand areas. Let's look at
00:16:58.950 --> 00:17:01.509
it. Imagine you have your cyber cab deployed
00:17:01.509 --> 00:17:04.470
in a bustling tourist city, let's say Las Vegas
00:17:04.470 --> 00:17:07.789
or Miami. The author outlines an 80 % utilization.
00:17:07.880 --> 00:17:10.240
rate. That means the vehicle is operating almost
00:17:10.240 --> 00:17:13.420
19 hours a day. Almost constantly. It's practically
00:17:13.420 --> 00:17:15.839
in constant motion, only pausing to recharge
00:17:15.839 --> 00:17:18.519
and undergo basic cleaning. Fares in this high
00:17:18.519 --> 00:17:21.259
demand scenario are modeled at $2 per mile and
00:17:21.259 --> 00:17:23.720
trips average seven miles. In this scenario,
00:17:23.940 --> 00:17:26.380
the math goes stratospheric. The revenue rockets
00:17:26.380 --> 00:17:30.240
to $110 ,000 annually. After deducting the fixed
00:17:30.240 --> 00:17:33.079
loan costs, the significantly higher variable
00:17:33.079 --> 00:17:36.339
costs from all those miles, and taxes, the gross
00:17:36.339 --> 00:17:39.559
profits hit $65 ,000, pushing the net income
00:17:39.559 --> 00:17:44.500
to $45 ,000 per vehicle. $45 ,000 of passive
00:17:44.500 --> 00:17:48.880
income from a single $30 ,000 vehicle. It's incredible.
00:17:49.400 --> 00:17:51.500
And it's noted that if you get creative as an
00:17:51.500 --> 00:17:54.400
owner, say you integrate solar charging at your
00:17:54.400 --> 00:17:57.200
house, to effectively drop your electricity cost
00:17:57.200 --> 00:18:00.259
to zero, Or if you secure lower interest rates
00:18:00.259 --> 00:18:02.940
on the initial financing, that net profit could
00:18:02.940 --> 00:18:05.759
comfortably push past $50 ,000 a year. However,
00:18:05.940 --> 00:18:08.420
we must examine the edge cases critically. Yeah,
00:18:08.440 --> 00:18:10.660
we have to. The source material is comprehensive
00:18:10.660 --> 00:18:13.059
and does not shy away from the downside risks.
00:18:13.299 --> 00:18:16.099
You cannot just assume you'll hit 80 % utilization
00:18:16.099 --> 00:18:18.480
because you bought the car. What happens when
00:18:18.480 --> 00:18:20.259
things go wrong? Right. We definitely don't want
00:18:20.259 --> 00:18:22.359
to sugarcoat those risks. Let's look at the worst
00:18:22.359 --> 00:18:25.049
case scenario. The analysis outlines a situation
00:18:25.049 --> 00:18:28.650
where utilization drops to just 10%. Which means
00:18:28.650 --> 00:18:32.369
the car is only in service for 2 .4 hours a day.
00:18:32.529 --> 00:18:34.529
It's basically just sitting in a parking lot
00:18:34.529 --> 00:18:37.490
having an existential crisis for 21 hours a day.
00:18:37.630 --> 00:18:40.150
Essentially, yes. Why would that happen? A variety
00:18:40.150 --> 00:18:43.819
of factors. It could be regulatory delays. Perhaps
00:18:43.819 --> 00:18:46.220
the municipality places a cap on the number of
00:18:46.220 --> 00:18:48.440
autonomous vehicles allowed in a specific zone.
00:18:48.599 --> 00:18:50.619
That makes sense. It could be extremely high
00:18:50.619 --> 00:18:53.019
competition in a saturated market where there
00:18:53.019 --> 00:18:56.160
are simply more robo taxes than passengers. Or
00:18:56.160 --> 00:18:58.660
it could be unexpected, prolonged maintenance
00:18:58.660 --> 00:19:01.720
issues like a sensor suite failing that takes
00:19:01.720 --> 00:19:04.140
weeks to replace. At 10 percent utilization,
00:19:04.500 --> 00:19:07.980
covering a mere 36 miles a day at 15 miles per
00:19:07.980 --> 00:19:11.150
hour. Revenues plunge to just $9 ,500 annually
00:19:11.150 --> 00:19:13.289
after the operator takes their cut. And here
00:19:13.289 --> 00:19:15.410
is the trap. Yeah. You still have to pay the
00:19:15.410 --> 00:19:17.490
bank. You still have that $18 ,000 a year in
00:19:17.490 --> 00:19:20.369
financing. You still have insurance. Those fixed
00:19:20.369 --> 00:19:23.410
expenses consume absolutely everything. The math
00:19:23.410 --> 00:19:26.069
becomes unforgiving. The calculation shows that
00:19:26.069 --> 00:19:28.930
this 10 % scenario results in a net loss of $2
00:19:28.930 --> 00:19:32.730
,000 to $5 ,000 per year. It is a stark reminder
00:19:32.730 --> 00:19:36.450
that this isn't magic. It is a business. Market
00:19:36.450 --> 00:19:39.009
selection, regulatory awareness, and operational
00:19:39.009 --> 00:19:42.230
efficiency are going to be paramount when mitigating
00:19:42.230 --> 00:19:44.430
those downside risks. It's the reality check
00:19:44.430 --> 00:19:46.809
we need. You are running a logistics business.
00:19:47.049 --> 00:19:49.970
Exactly. But let's zoom out a bit and look at
00:19:49.970 --> 00:19:52.829
the ecosystem as a whole, because you aren't
00:19:52.829 --> 00:19:55.970
the only one making money here. The network operator
00:19:56.680 --> 00:19:59.160
The company running the app and routing the cars
00:19:59.160 --> 00:20:02.319
is doing incredibly well. Precisely. The ecosystem
00:20:02.319 --> 00:20:04.640
is designed to be mutually beneficial, though
00:20:04.640 --> 00:20:07.160
arguably weighted heavily toward the platform
00:20:07.160 --> 00:20:10.240
in terms of capital efficiency. From the perspective
00:20:10.240 --> 00:20:13.319
of the network operator taking that 35 % cut,
00:20:13.599 --> 00:20:16.559
they are making margins of $20 ,000 to $40 ,000
00:20:16.559 --> 00:20:19.440
per vehicle annually without bearing the cost
00:20:19.440 --> 00:20:21.539
of the vehicle loan, the physical maintenance,
00:20:21.720 --> 00:20:23.680
or the insurance risk. Which is brilliant on
00:20:23.680 --> 00:20:26.609
their part. It is the ultimate asset -light model
00:20:26.609 --> 00:20:30.009
for the network. But that structure is what provides
00:20:30.009 --> 00:20:32.670
the capital necessary to support the ongoing
00:20:32.670 --> 00:20:35.690
massive technological development of the centralized
00:20:35.690 --> 00:20:39.089
AI and the server infrastructure required to
00:20:39.089 --> 00:20:42.190
run millions of autonomous nodes safely. And
00:20:42.190 --> 00:20:44.539
is it the rideshare math wasn't enough? We haven't
00:20:44.539 --> 00:20:46.740
even touched on the hidden margins. The alternative
00:20:46.740 --> 00:20:49.660
streams. Right. The analysis points out that
00:20:49.660 --> 00:20:52.559
these rideshare calculations completely exclude
00:20:52.559 --> 00:20:55.319
entirely different alternative income streams
00:20:55.319 --> 00:20:57.980
that could change the math even further. Yes.
00:20:58.039 --> 00:21:00.799
The vehicle's utility extends far beyond simply
00:21:00.799 --> 00:21:03.519
moving a human from point A to point B. The alternative
00:21:03.519 --> 00:21:06.539
streams are wild. First, it discusses in -cabin
00:21:06.539 --> 00:21:08.849
advertising. Right. Imagine getting into your
00:21:08.849 --> 00:21:11.029
cyber cab and the screens are playing targeted
00:21:11.029 --> 00:21:13.450
ads or sponsored content for local businesses
00:21:13.450 --> 00:21:16.230
based on where the car is routing you. Or subscription
00:21:16.230 --> 00:21:18.589
-based entertainment. Passengers paying a premium
00:21:18.589 --> 00:21:20.869
to access high -end gaming or streaming movies
00:21:20.869 --> 00:21:23.269
during a long commute. But my absolute favorite
00:21:23.269 --> 00:21:25.250
part, the one that really highlights how futuristic
00:21:25.250 --> 00:21:28.269
this is, is the concept of using the car's idle
00:21:28.269 --> 00:21:31.240
processing power. This is a vital point regarding
00:21:31.240 --> 00:21:33.859
resource allocation in the interregnum. Let me
00:21:33.859 --> 00:21:35.359
break this down for the listener because it's
00:21:35.359 --> 00:21:38.740
a bit technical, but so cool. These cars need
00:21:38.740 --> 00:21:41.619
massive supercomputers in their trunks to process
00:21:41.619 --> 00:21:44.420
all the camera and sensor data required to drive
00:21:44.420 --> 00:21:47.319
autonomously. Yes. But when the car is parked,
00:21:47.460 --> 00:21:50.759
charging, or waiting for a ride, that supercomputer
00:21:50.759 --> 00:21:53.160
is just sitting there doing nothing. Just idle
00:21:53.160 --> 00:21:56.059
logic. Exactly. The concept here is that you
00:21:56.059 --> 00:21:59.329
can use that idle processing power. for distributed
00:21:59.329 --> 00:22:02.809
computing tasks. Specifically, artificial intelligence
00:22:02.809 --> 00:22:05.849
inference. To put it simply, AI inference is
00:22:05.849 --> 00:22:08.029
the process where a trained machine learning
00:22:08.029 --> 00:22:10.670
model is used to make predictions or solve problems
00:22:10.670 --> 00:22:13.670
based on new data. It requires immense computational
00:22:13.670 --> 00:22:16.329
power. Think of it like renting out your spare
00:22:16.329 --> 00:22:19.309
bedroom on Airbnb. But instead of a bedroom,
00:22:19.819 --> 00:22:21.440
You are renting out the massive supercomputer
00:22:21.440 --> 00:22:24.880
sitting idle in your cyber cab's trunk so an
00:22:24.880 --> 00:22:27.619
AI company can use it to process data while your
00:22:27.619 --> 00:22:29.960
car is parked in your garage overnight. It's
00:22:29.960 --> 00:22:33.000
a brilliant use of dormant capital. You are literally
00:22:33.000 --> 00:22:35.200
renting out the car's brainpower while it sleeps.
00:22:35.440 --> 00:22:37.819
That specific detail highlights the paradigm
00:22:37.819 --> 00:22:41.079
shift perfectly. The vehicle is no longer just
00:22:41.079 --> 00:22:44.140
a transport mechanism. It is a mobile computing
00:22:44.140 --> 00:22:47.319
center, a node on a distributed energy network.
00:22:47.920 --> 00:22:51.000
And a digital billboard all at once. It's so
00:22:51.000 --> 00:22:53.299
multidimensional. It is a multidimensional asset.
00:22:53.579 --> 00:22:55.740
Okay. We've covered the base math, the scaling,
00:22:55.880 --> 00:22:57.880
the edge cases, and the alternative revenue.
00:22:58.240 --> 00:23:01.299
But the true power of this model. the emotional
00:23:01.299 --> 00:23:04.339
and practical core of this entire deep dive emerges
00:23:04.339 --> 00:23:07.039
when we look at the compounding growth example.
00:23:07.240 --> 00:23:09.720
Yes. This is where the numbers transition from
00:23:09.720 --> 00:23:13.000
an interesting little side income to a transformative
00:23:13.000 --> 00:23:16.220
generational wealth generation strategy. This
00:23:16.220 --> 00:23:17.920
is where the mechanics of capital acceleration
00:23:17.920 --> 00:23:20.859
take over. Pay close attention to this part.
00:23:20.940 --> 00:23:22.480
We're going to break down the compounding growth
00:23:22.480 --> 00:23:25.720
step by step exactly as the source material maps
00:23:25.720 --> 00:23:27.519
it out. Let's go back to that hook I gave you
00:23:27.519 --> 00:23:29.900
at the very beginning of the show. The $6 ,000
00:23:29.900 --> 00:23:33.119
down payment. Assuming a standard 20 % down payment
00:23:33.119 --> 00:23:36.319
on a $30 ,000 asset. Exactly. You start with
00:23:36.319 --> 00:23:39.259
just $6 ,000 in cash to acquire your first cyber
00:23:39.259 --> 00:23:42.400
cab. You finance the rest. Now, let's assume
00:23:42.400 --> 00:23:44.839
you're operating at that modest base case we
00:23:44.839 --> 00:23:47.339
talked about earlier, a 30 % utilization rate.
00:23:48.319 --> 00:23:51.099
You aren't in a super busy city, just a standard
00:23:51.099 --> 00:23:54.339
suburb. Okay. The owner decides to aggressively
00:23:54.339 --> 00:23:58.480
reinvest all pre -tax cash flow. The model estimates
00:23:58.480 --> 00:24:01.759
that at 30 % utilization, you are generating
00:24:01.759 --> 00:24:06.710
about $943 a month in positive cash flow. Crucially,
00:24:06.809 --> 00:24:10.390
you are not treating this $943 as disposable
00:24:10.390 --> 00:24:13.369
income. No vacations. You are not buying on your
00:24:13.369 --> 00:24:15.829
TV or going out to dinner. You are rolling it
00:24:15.829 --> 00:24:17.829
over, keeping it within the business entity to
00:24:17.829 --> 00:24:19.849
acquire more capital. Right. You're letting the
00:24:19.849 --> 00:24:22.640
robot build your empire. By month five, that
00:24:22.640 --> 00:24:25.839
first car has generated roughly $4 ,700 in cash.
00:24:26.079 --> 00:24:28.759
Yes. Combined with a little extra, you have enough
00:24:28.759 --> 00:24:31.440
funds generated solely from the first car to
00:24:31.440 --> 00:24:34.440
secure the $6 ,000 down payment for a second
00:24:34.440 --> 00:24:36.579
vehicle. Let's pause and really analyze what
00:24:36.579 --> 00:24:38.799
that means. It's crazy. In less than half a year,
00:24:38.920 --> 00:24:41.799
a single physical asset has financed the acquisition
00:24:41.799 --> 00:24:45.140
of a duplicate asset entirely under its own power.
00:24:45.660 --> 00:24:48.339
Without requiring any additional external capital
00:24:48.339 --> 00:24:51.619
injections from the owner's W -2 job or savings.
00:24:51.799 --> 00:24:54.599
It's the holy grail of business. And the acquisitions
00:24:54.599 --> 00:24:56.400
accelerate from there because now you have two
00:24:56.400 --> 00:24:59.279
robots working for you. Compounding. According
00:24:59.279 --> 00:25:01.420
to the detailed timeline, by the end of year
00:25:01.420 --> 00:25:05.009
one, your fleet grows to five vehicles. At this
00:25:05.009 --> 00:25:07.309
point, those five vehicles are generating $4
00:25:07.309 --> 00:25:12.490
,713 in monthly cash flow. Within 12 months,
00:25:12.710 --> 00:25:15.890
starting from a single $6 ,000 initial investment,
00:25:16.109 --> 00:25:19.349
you have effectively birthed a small transport
00:25:19.349 --> 00:25:22.250
logistics company. It's astonishing. But the
00:25:22.250 --> 00:25:24.410
snowball just keeps getting bigger faster because
00:25:24.410 --> 00:25:26.369
now you have five cars throwing off cash every
00:25:26.369 --> 00:25:28.789
month. Right. By year two... Sticking to this
00:25:28.789 --> 00:25:31.309
strict reinvestment strategy, your fleet expands
00:25:31.309 --> 00:25:35.069
to 38 vehicles. Those 38 vehicles are yielding
00:25:35.069 --> 00:25:38.369
$35 ,800 in monthly cash flow. And by year three.
00:25:38.450 --> 00:25:40.829
This is where the math sounds almost unbelievable,
00:25:41.009 --> 00:25:44.150
but it's just the cold, hard mechanics of compounding
00:25:44.150 --> 00:25:47.299
interest applied to physical assets. By year
00:25:47.299 --> 00:25:49.759
three, you have over 300 vehicles. Incredible.
00:25:49.839 --> 00:25:52.200
And those 300 vehicles are generating an astonishing
00:25:52.200 --> 00:25:56.539
$285 ,600 in monthly cash flow. The mathematics
00:25:56.539 --> 00:25:59.420
of compounding are notoriously difficult for
00:25:59.420 --> 00:26:02.480
the human brain to intuitively grasp. Oh, totally.
00:26:02.640 --> 00:26:05.119
Our brains are wired to think linearly. One,
00:26:05.279 --> 00:26:07.680
two, three, four. Compounding is exponential.
00:26:07.880 --> 00:26:11.259
One, two, four, eight, 16. Which is why seeing
00:26:11.259 --> 00:26:14.019
it modeled out physically with tangible assets
00:26:14.019 --> 00:26:17.140
like vehicles is so impactful. Okay, wait, stop
00:26:17.140 --> 00:26:18.680
right there. I have to play devil's advocate
00:26:18.680 --> 00:26:20.500
here. Yeah. Because if I'm listening to this,
00:26:20.539 --> 00:26:23.000
my alarm bells are ringing. Naturally. You're
00:26:23.000 --> 00:26:27.859
telling me a $6 ,000 down payment snowballs into
00:26:27.859 --> 00:26:30.140
over a quarter of a million dollars a month in
00:26:30.140 --> 00:26:32.359
just three years? That sounds like a late night
00:26:32.359 --> 00:26:34.720
crypto scam. I understand that reaction. I mean,
00:26:34.740 --> 00:26:36.759
how is that physically possible? I'm calling
00:26:36.759 --> 00:26:40.000
BS on this happening in a vacuum without the
00:26:40.000 --> 00:26:42.319
market completely saturating or the logistics
00:26:42.319 --> 00:26:45.779
breaking down. It is a completely fair and necessary
00:26:45.779 --> 00:26:50.220
reaction. And to be clear, the author anticipates
00:26:50.220 --> 00:26:52.779
that exact skepticism. Okay. The spreadsheet
00:26:52.779 --> 00:26:55.920
outlines the mathematical possibility, but we
00:26:55.920 --> 00:26:58.359
must discuss the physical and operational constraints.
00:26:58.640 --> 00:27:01.019
This does not happen in a vacuum. Right. You
00:27:01.019 --> 00:27:03.759
can't just spawn 300 cars out of thin air. Exactly.
00:27:04.490 --> 00:27:07.369
We are talking about physical machines, not just
00:27:07.369 --> 00:27:09.609
software code that can be duplicated infinitely
00:27:09.609 --> 00:27:13.970
at zero cost. The first massive hurdle is manufacturing
00:27:13.970 --> 00:27:16.990
capacity. Tesla have to build them. Tesla, or
00:27:16.990 --> 00:27:19.569
whoever the manufacturer is, simply has to be
00:27:19.569 --> 00:27:21.730
able to physically build these vehicles fast
00:27:21.730 --> 00:27:24.329
enough to meet this kind of compounding demand
00:27:24.329 --> 00:27:27.109
from tens of thousands of fleet operators trying
00:27:27.109 --> 00:27:29.390
to do the exact same thing. Supply chain realities.
00:27:29.690 --> 00:27:32.730
Yes. Secondly, there are local regulatory hurdles.
00:27:33.869 --> 00:27:36.490
might welcome 10 robo taxes, but if you suddenly
00:27:36.490 --> 00:27:39.309
try to dump 300 autonomous vehicles onto the
00:27:39.309 --> 00:27:41.529
streets of a mid -sized town, the local government
00:27:41.529 --> 00:27:43.049
is going to intervene. Yeah, the mayor is going
00:27:43.049 --> 00:27:45.589
to step in. They will cap fleet sizes to manage
00:27:45.589 --> 00:27:48.309
traffic congestion. And what about the actual
00:27:48.309 --> 00:27:51.549
day -to -day logistics? Where do 300 cars park
00:27:51.549 --> 00:27:54.529
when demand is low? That is the most significant
00:27:54.529 --> 00:27:56.950
constraint for the individual operator, the immense
00:27:56.950 --> 00:28:00.069
complexity of fleet management. Managing 300
00:28:00.069 --> 00:28:03.339
physical vehicles, even autonomous ones, requires
00:28:03.339 --> 00:28:06.920
sophisticated logistics. Real estate alone. You
00:28:06.920 --> 00:28:09.500
need physical real estate to park them. You need
00:28:09.500 --> 00:28:12.119
dedicated high voltage charging infrastructure.
00:28:12.740 --> 00:28:16.279
You need a centralized system for cleaning. Are
00:28:16.279 --> 00:28:18.680
you hiring a crew of teenagers to wipe down back
00:28:18.680 --> 00:28:20.720
seats at a depot every night? You probably are.
00:28:20.859 --> 00:28:23.160
You need localized maintenance hubs for tire
00:28:23.160 --> 00:28:25.759
rotations and sensor calibrations. It's a massive
00:28:25.759 --> 00:28:27.920
operational undertaking. It's not just a spreadsheet
00:28:27.920 --> 00:28:31.279
anymore. You are running a major local utility.
00:28:31.680 --> 00:28:34.500
Precisely. The model illustrates the cybercabs
00:28:34.500 --> 00:28:37.500
role as a hyperscalable asset class, mimicking
00:28:37.500 --> 00:28:39.700
the kind of exponential wealth accumulation we
00:28:39.700 --> 00:28:41.880
previously only saw in early digital enterprises.
00:28:42.200 --> 00:28:44.359
Like software companies. Exactly. Software companies
00:28:44.359 --> 00:28:47.039
with near zero marginal costs. But executing
00:28:47.039 --> 00:28:49.680
it to that 300 car degree in the physical world
00:28:49.680 --> 00:28:52.140
requires transitioning from a passive investor
00:28:52.140 --> 00:28:55.859
into an active logistics CEO. OK, that grounds
00:28:55.859 --> 00:28:59.339
it a bit. It's possible, but it requires serious
00:28:59.339 --> 00:29:01.859
operational infrastructure as you scale. But
00:29:01.859 --> 00:29:04.700
just to indulge the absolute ceiling of this
00:29:04.700 --> 00:29:08.519
compounding idea, the analysis provides an extreme
00:29:08.519 --> 00:29:11.519
edge case. The absolute pick. If you have the
00:29:11.519 --> 00:29:14.180
operational chops to manage the fleet, and the
00:29:14.180 --> 00:29:16.420
local demand allows the base fare to be raised
00:29:16.420 --> 00:29:20.680
slightly to $3 .25 per mile, the monthly cash
00:29:20.680 --> 00:29:25.650
per vehicle hits $1 ,757. Wow. Under that highly
00:29:25.650 --> 00:29:28.849
specific, optimized set of conditions, the model
00:29:28.849 --> 00:29:31.529
projects the fleet could expand to over 500 vehicles
00:29:31.529 --> 00:29:35.089
by year three. That represents $46 million in
00:29:35.089 --> 00:29:38.250
annual cash flow. $46 million. From a six grand
00:29:38.250 --> 00:29:41.049
down payment. Even with the logistical nightmares
00:29:41.049 --> 00:29:44.029
of parking 500 cars, that math fundamentally
00:29:44.029 --> 00:29:46.029
breaks how we think about starting a traditional
00:29:46.029 --> 00:29:48.309
small business. It does. You aren't opening a
00:29:48.309 --> 00:29:50.190
bakery and hoping to break even in five years.
00:29:50.369 --> 00:29:52.470
You are deploying self -replicating capital.
00:29:52.690 --> 00:29:55.710
But as we noted. The urban market, where you
00:29:55.710 --> 00:29:58.789
might reach a 500 car cap, will become fiercely
00:29:58.789 --> 00:30:01.569
competitive. Which is why one of the most compelling
00:30:01.569 --> 00:30:04.250
insights from the Reed Multiplex analysis is
00:30:04.250 --> 00:30:06.829
the strategic pivot away from the obvious urban
00:30:06.829 --> 00:30:09.950
taxi model. Yes. Let's get out of this city.
00:30:10.200 --> 00:30:12.200
Because honestly, the most surprising part of
00:30:12.200 --> 00:30:15.420
this entire blueprint is how the cybercab's value
00:30:15.420 --> 00:30:18.400
proposition explodes when you look at specialized
00:30:18.400 --> 00:30:21.359
use cases in rural areas. Absolutely. If you
00:30:21.359 --> 00:30:23.099
live in a rural area, you might be listening
00:30:23.099 --> 00:30:25.019
to this and thinking, this is just a city thing.
00:30:25.200 --> 00:30:27.980
Yeah. No one is taking a robotaxi to the grocery
00:30:27.980 --> 00:30:30.660
store in my farm town. It's a common misconception.
00:30:31.079 --> 00:30:33.380
But the analysis explores applications that go
00:30:33.380 --> 00:30:35.619
way beyond shuttling people around downtown.
00:30:35.859 --> 00:30:38.819
The diversification of utility is key to mitigating
00:30:38.819 --> 00:30:41.079
the utilization risks and market saturation we
00:30:41.079 --> 00:30:44.319
just discussed. For example, logistics, autonomous
00:30:44.319 --> 00:30:47.559
last mile delivery. Instead of passengers, the
00:30:47.559 --> 00:30:49.940
cyber cab collaborates with e -commerce platforms
00:30:49.940 --> 00:30:53.240
or local grocery stores to move parcels and groceries
00:30:53.240 --> 00:30:55.759
to remote homes. It solves a massive supply chain
00:30:55.759 --> 00:30:58.319
issue. The analysis even mentions the incredible
00:30:58.319 --> 00:31:00.660
potential for integration with drone technology
00:31:00.660 --> 00:31:04.700
for combined aerial and ground transport. A cyber
00:31:04.700 --> 00:31:07.799
cab drives to a neighborhood and a drone launches
00:31:07.799 --> 00:31:11.480
from its roof to drop a package on a porch. It
00:31:11.480 --> 00:31:14.359
fundamentally reshapes supply chains. Furthermore,
00:31:14.539 --> 00:31:17.480
the analysis details profound healthcare applications.
00:31:17.700 --> 00:31:20.279
Oh, this was brilliant. Imagine cybercabs stripped
00:31:20.279 --> 00:31:22.619
of their passenger seats and outfitted with diagnostic
00:31:22.619 --> 00:31:26.210
equipment. mobile clinics exactly they could
00:31:26.210 --> 00:31:29.190
autonomously transport vulnerable or elderly
00:31:29.190 --> 00:31:32.230
patients to centralized medical facilities or
00:31:32.230 --> 00:31:34.410
they could deliver vital medications directly
00:31:34.410 --> 00:31:37.210
to homes the access that provides the analysis
00:31:37.210 --> 00:31:39.650
notes they could even incorporate secure digital
00:31:39.650 --> 00:31:42.589
interfaces for virtual consultations with doctors
00:31:42.589 --> 00:31:45.710
during the transit itself the time spent traveling
00:31:45.710 --> 00:31:48.309
becomes productive health care time and in education
00:31:48.309 --> 00:31:50.569
there are applications for these vehicles to
00:31:50.569 --> 00:31:52.730
serve as mobile learning environments providing
00:31:53.069 --> 00:31:54.950
students with access to high -speed internet
00:31:54.950 --> 00:31:58.329
resources or facilitating immersive virtual experiences
00:31:58.329 --> 00:32:01.009
while commuting long distances to regional schools.
00:32:01.329 --> 00:32:04.910
Which brings us to a core economic concept. The
00:32:04.910 --> 00:32:07.609
author identifies the rural advantage. Let's
00:32:07.609 --> 00:32:10.990
explore this. Why would rural areas be better
00:32:10.990 --> 00:32:13.900
than cities for this? In an urban environment,
00:32:13.980 --> 00:32:15.940
you have millions of people. You have density.
00:32:16.119 --> 00:32:18.420
You have density, yes, but you also have intense
00:32:18.420 --> 00:32:21.779
competition. Right. In a city, your cyber cab
00:32:21.779 --> 00:32:24.420
is competing against public transit, subways,
00:32:24.599 --> 00:32:27.619
buses, walkable neighborhoods, human -driven
00:32:27.619 --> 00:32:30.099
Ubers, and dozens of other autonomous fleets.
00:32:30.440 --> 00:32:33.740
The dependency on any single vehicle is low.
00:32:33.920 --> 00:32:36.220
Okay, that makes sense. But in rural areas, the
00:32:36.220 --> 00:32:38.700
dynamic completely shifts. In places like the
00:32:38.700 --> 00:32:41.500
American Midwest, the Canadian prairies, or the
00:32:41.500 --> 00:32:43.960
Australian... lane interior, essential infrastructure
00:32:43.960 --> 00:32:46.400
like grocery stores, specialized medical centers,
00:32:46.480 --> 00:32:48.559
and high schools can be 50 miles away or more.
00:32:48.700 --> 00:32:50.740
Yeah, massive distances. Reliable transportation
00:32:50.740 --> 00:32:53.539
is absolutely indispensable for survival, but
00:32:53.539 --> 00:32:56.500
public transit simply does not exist. The geographic
00:32:56.500 --> 00:32:59.099
distances exacerbate the challenges of accessing
00:32:59.099 --> 00:33:01.819
basic services. So in a rural area, your cyber
00:33:01.819 --> 00:33:04.380
cab isn't just a convenience, it's a lifeline.
00:33:04.519 --> 00:33:07.599
The analysis posits that a single cyber cab could
00:33:07.599 --> 00:33:10.880
operate extended, highly predictable routes in
00:33:10.880 --> 00:33:13.240
these areas. Offering on demand services for
00:33:13.240 --> 00:33:15.680
weekly shopping, transporting specialized agricultural
00:33:15.680 --> 00:33:19.019
supplies or facilitating medical visits. Yes.
00:33:19.160 --> 00:33:22.240
And because there is no alternative, the exclusivity
00:33:22.240 --> 00:33:25.200
beats the urban density. The author provides
00:33:25.200 --> 00:33:28.099
a highly specific, fascinating scenario detailing
00:33:28.099 --> 00:33:30.839
a Midwestern farming cooperative to illustrate
00:33:30.839 --> 00:33:33.480
the economics of this exclusivity. I love this
00:33:33.480 --> 00:33:35.740
example. It perfectly illustrates the power of
00:33:35.740 --> 00:33:38.799
pooling resources in a community. The scenario
00:33:38.799 --> 00:33:41.460
describes a hypothetical situation where local
00:33:41.460 --> 00:33:44.299
rural residents, maybe a dozen families, spread
00:33:44.299 --> 00:33:46.819
out over a county pool their money to invest
00:33:46.819 --> 00:33:49.539
in a fleet of five cybercaps. Shared asset model.
00:33:49.779 --> 00:33:51.319
These aren't for one person. They're community
00:33:51.319 --> 00:33:54.279
assets. These vehicles alternate between passenger
00:33:54.279 --> 00:33:56.980
transport, linking isolated farmhomes to larger
00:33:56.980 --> 00:33:59.099
towns that might be an hour's drive away, and
00:33:59.099 --> 00:34:01.410
heavy cargo duties. They could literally transport
00:34:01.410 --> 00:34:04.049
smaller yields of harvested crops to regional
00:34:04.049 --> 00:34:06.250
processing facilities that are 60 miles away,
00:34:06.410 --> 00:34:09.210
running continuously back and forth. And because
00:34:09.210 --> 00:34:12.610
there are literally zero alternatives out there,
00:34:12.730 --> 00:34:17.170
no buses, no trains, no Ubers, they can command
00:34:17.170 --> 00:34:21.449
premium pricing. The model uses $1 .50 base fare
00:34:21.449 --> 00:34:25.190
plus $1 .20 per mile. And critically, because
00:34:25.190 --> 00:34:27.969
of those much longer average trips estimated
00:34:27.969 --> 00:34:31.050
at 10 to 15 miles minimum and the lack of alternatives,
00:34:31.469 --> 00:34:33.989
the utilization rate could comfortably stabilize
00:34:33.989 --> 00:34:37.329
at 50%. Doing the math on that, the scenario
00:34:37.329 --> 00:34:40.369
calculates that this rural co -op model generates
00:34:40.369 --> 00:34:43.730
$45 ,000 in annual net profit per vehicle. Which
00:34:43.730 --> 00:34:45.510
is excellent. But what's really interesting is
00:34:45.510 --> 00:34:47.530
how the expense columns shift in this environment.
00:34:47.880 --> 00:34:50.219
Yes, the operational reality of rural driving.
00:34:50.360 --> 00:34:52.219
The analysis points out that you would experience
00:34:52.219 --> 00:34:54.619
significantly lower commercial insurance rates
00:34:54.619 --> 00:34:57.460
in low traffic rural areas because the risk of
00:34:57.460 --> 00:34:59.260
collisions with other vehicles or pedestrians
00:34:59.260 --> 00:35:01.800
is drastically reduced compared to a dense city
00:35:01.800 --> 00:35:03.659
center. But on the flip side, you are driving
00:35:03.659 --> 00:35:06.500
on dirt roads, gravel and poorly maintained country
00:35:06.500 --> 00:35:08.840
highways. Exactly. So the savings on insurance
00:35:08.840 --> 00:35:11.139
are needed to offset the higher maintenance and
00:35:11.139 --> 00:35:13.969
tire costs associated with rougher terrain. It
00:35:13.969 --> 00:35:16.710
requires a different operational calculus. And
00:35:16.710 --> 00:35:18.489
we also have to account for the seasonal swings,
00:35:18.710 --> 00:35:22.070
which the analysis models brilliantly. In a farming
00:35:22.070 --> 00:35:25.030
community, demand isn't flat year -round. Not
00:35:25.030 --> 00:35:27.289
at all. During the harvest periods in late summer
00:35:27.289 --> 00:35:30.409
and fall, utilization would spike massively,
00:35:30.570 --> 00:35:33.969
maybe up to 70%, as the vehicles are constantly
00:35:33.969 --> 00:35:37.389
moving labor, supplies, and crops. That could
00:35:37.389 --> 00:35:40.789
boost profits to a run rate of $60 ,000 per vehicle.
00:35:41.179 --> 00:35:43.699
But conversely, in the deep winter, when the
00:35:43.699 --> 00:35:46.019
weather is harsh, the roads are snowed in, and
00:35:46.019 --> 00:35:49.380
farming operations halt, utilization might plummet
00:35:49.380 --> 00:35:52.320
to 20%. So what does the co -op do with five
00:35:52.320 --> 00:35:54.869
autonomous vehicles in January? This is where
00:35:54.869 --> 00:35:57.630
adaptability is required. To counter the winter
00:35:57.630 --> 00:35:59.909
lull, the co -op would have to diversify the
00:35:59.909 --> 00:36:02.489
vehicle's uses. They could be contracted to the
00:36:02.489 --> 00:36:04.650
local county for emergency response logistics
00:36:04.650 --> 00:36:07.389
delivering salt or winter supplies. Oh, that's
00:36:07.389 --> 00:36:09.949
smart. Or they could serve as mobile repair units
00:36:09.949 --> 00:36:12.530
carrying tools to isolated homes that lose power
00:36:12.530 --> 00:36:15.409
or heating. It turns the vehicle from a taxi
00:36:15.409 --> 00:36:19.380
into a multi -tool. And the returns on that adaptability
00:36:19.380 --> 00:36:22.019
are incredible, but the implications get even
00:36:22.019 --> 00:36:24.659
bigger. The analysis takes this rural advantage
00:36:24.659 --> 00:36:28.199
concept and extends it globally. Yes, to developing
00:36:28.199 --> 00:36:30.900
regions. Specifically, looking at developing
00:36:30.900 --> 00:36:33.699
regions, such as sub -Saharan Africa. And this
00:36:33.699 --> 00:36:36.119
is where the cybercab transitions from a wealth
00:36:36.119 --> 00:36:39.079
-generating tool into a profound mechanism for
00:36:39.079 --> 00:36:41.659
inclusive global development. In developing regions,
00:36:41.920 --> 00:36:44.139
the technology allows for leapfrogging. Like
00:36:44.139 --> 00:36:47.309
cell phones. Exactly. Just as many parts of the
00:36:47.309 --> 00:36:49.610
world skipped the massive infrastructural cost
00:36:49.610 --> 00:36:52.309
of laying copper landline telephones and went
00:36:52.309 --> 00:36:54.590
straight to mobile cell networks, they can potentially
00:36:54.590 --> 00:36:56.829
skip the massive cost of building intricate,
00:36:57.070 --> 00:36:59.929
heavily subsidized public rail networks and move
00:36:59.929 --> 00:37:02.630
straight to autonomous, decentralized electric
00:37:02.630 --> 00:37:04.929
fleets. The vision outlined here really blew
00:37:04.929 --> 00:37:08.110
my mind. It envisions these vehicles functioning
00:37:08.110 --> 00:37:10.829
as mobile health clinics, traveling autonomously
00:37:10.829 --> 00:37:13.269
between remote villages separated by uncaved,
00:37:13.309 --> 00:37:15.469
difficult roads. Such a powerful image. They
00:37:15.469 --> 00:37:17.670
would be equipped with basic diagnostic tools,
00:37:18.030 --> 00:37:21.070
refrigeration for vaccines, and high -band satellite
00:37:21.070 --> 00:37:24.050
telemedicine links. The economics of this are
00:37:24.050 --> 00:37:26.989
heavily dependent on partnerships. The analysis
00:37:26.989 --> 00:37:28.969
suggests that international government subsidies
00:37:28.969 --> 00:37:32.469
or NGO partnerships could bring the upfront acquisition
00:37:32.469 --> 00:37:35.789
costs down to perhaps $20 ,000 per year. unit
00:37:35.789 --> 00:37:38.070
in these regions, making deployment feasible.
00:37:38.990 --> 00:37:42.590
Operating at a 40 % utilization rate, the revenues
00:37:42.590 --> 00:37:45.489
derived from small patient fees combined with
00:37:45.489 --> 00:37:48.289
international aid subsidies could yield a $30
00:37:48.289 --> 00:37:52.050
,000 net profit annually for the local operators.
00:37:52.369 --> 00:37:54.469
And it discusses the best case outcomes where
00:37:54.469 --> 00:37:57.050
this localized economic engine actually drives
00:37:57.050 --> 00:37:59.889
further development. As the fleets generate capital,
00:38:00.110 --> 00:38:02.909
local governments or co -ops can reinvest that
00:38:02.909 --> 00:38:05.409
money into improving local infrastructure. Caving
00:38:05.409 --> 00:38:08.909
roads. Yes, paving roads or building solar. microgrids
00:38:08.909 --> 00:38:11.110
to charge the vehicles, which in turn potentially
00:38:11.110 --> 00:38:13.650
doubles the utilization and profits of the fleets,
00:38:13.690 --> 00:38:16.250
it creates a virtuous cycle of development. It's
00:38:16.250 --> 00:38:19.190
incredibly hopeful, though the author is impartial
00:38:19.190 --> 00:38:22.170
and notes the very real worst case risks. We
00:38:22.170 --> 00:38:24.349
have to acknowledge them. In some regions, political
00:38:24.349 --> 00:38:27.789
instability, corruption, or conflict could disrupt
00:38:27.789 --> 00:38:30.710
operations entirely, or the vehicles could be
00:38:30.710 --> 00:38:32.710
targeted for theft of their batteries and compute
00:38:32.710 --> 00:38:36.260
hardware. It emphasizes the need for robust contingency
00:38:36.260 --> 00:38:38.320
planning and localized security adaptations.
00:38:38.780 --> 00:38:41.079
But what is essential to draw from these global
00:38:41.079 --> 00:38:44.239
rural applications is that under recognized advantage,
00:38:44.719 --> 00:38:47.679
while urban markets offer density, rural markets
00:38:47.679 --> 00:38:50.860
provide exclusivity and undeniable utility. Right.
00:38:50.980 --> 00:38:53.539
This leads to higher per trip revenues and a
00:38:53.539 --> 00:38:55.900
significantly greater, more tangible societal
00:38:55.900 --> 00:38:58.840
impact. The analysis even notes that these heavy
00:38:58.840 --> 00:39:00.800
duty electric platforms could eventually tow
00:39:00.800 --> 00:39:03.019
agricultural equipment between smallholder farms.
00:39:03.150 --> 00:39:05.449
act as mobile veterinary units for livestock
00:39:05.449 --> 00:39:08.309
herds, or, and this is brilliant, contribute
00:39:08.309 --> 00:39:10.710
to local energy resilience by acting as massive
00:39:10.710 --> 00:39:13.710
mobile batteries sharing their power during local
00:39:13.710 --> 00:39:15.809
grid failures to keep critical village infrastructure
00:39:15.809 --> 00:39:18.409
online. Rural deployment positions the cyber
00:39:18.409 --> 00:39:21.090
cap as a catalyst. It bridges geographical disparities
00:39:21.090 --> 00:39:23.110
in medical and agricultural access that have
00:39:23.110 --> 00:39:25.690
endured across eras, finally bringing the benefits
00:39:25.690 --> 00:39:27.610
of the digital revolution to the physical world
00:39:27.610 --> 00:39:30.469
in remote locations. So what does this all mean?
00:39:30.690 --> 00:39:33.869
We have covered so much ground today. We really
00:39:33.869 --> 00:39:35.650
have. We've talked about the tight margins of
00:39:35.650 --> 00:39:38.610
the base math, the explosive scaling, the hidden
00:39:38.610 --> 00:39:41.570
revenue of AI inference, the compounding logistics
00:39:41.570 --> 00:39:45.769
of a 300 car fleet, and the global impact of
00:39:45.769 --> 00:39:48.309
rural. mobile clinics. How does this all tie
00:39:48.309 --> 00:39:50.610
together into a cohesive worldview? Well, the
00:39:50.610 --> 00:39:53.030
source material ties all these specific data
00:39:53.030 --> 00:39:55.110
points back to that overarching philosophical
00:39:55.110 --> 00:39:58.050
framework we mentioned at the start, the 5 ,000
00:39:58.050 --> 00:40:00.909
days interregnum. Right. Yes. The interregnum
00:40:00.909 --> 00:40:03.610
is the defining concept. To reiterate, it is
00:40:03.610 --> 00:40:06.130
the transitional gap where human effort intersects
00:40:06.130 --> 00:40:08.489
with emerging but not yet fully realized machine
00:40:08.489 --> 00:40:10.989
capability. It is the bridge between the old
00:40:10.989 --> 00:40:13.250
world of physical labor and the new world of
00:40:13.250 --> 00:40:15.389
autonomous abundance. If we connect this to the
00:40:15.389 --> 00:40:18.389
bigger picture. The cybercap perfectly exemplifies
00:40:18.389 --> 00:40:21.090
interregnum economics. It acts as a passive,
00:40:21.230 --> 00:40:24.489
highly expandable resource. It produces real
00:40:24.489 --> 00:40:27.510
physical value in the real world without requiring
00:40:27.510 --> 00:40:29.710
constant human oversight or physical exhaustion.
00:40:30.280 --> 00:40:33.400
And the analysis deliberately contrasts this
00:40:33.400 --> 00:40:36.480
new class of asset with other traditional forms
00:40:36.480 --> 00:40:38.360
of investment that people have relied on for
00:40:38.360 --> 00:40:41.360
generations. Like real estate. Exactly. Consider
00:40:41.360 --> 00:40:44.280
traditional real estate. Demanding rental properties
00:40:44.280 --> 00:40:46.960
require constant maintenance, dealing with tenant
00:40:46.960 --> 00:40:50.619
disputes, fixing leaky roofs at 2 a .m. and managing
00:40:50.619 --> 00:40:54.579
property taxes. Or consider traditional equities.
00:40:54.679 --> 00:40:57.139
Right. The stock market. Fluctuating stock investments
00:40:57.139 --> 00:41:00.500
that are subject to unpredictable. global market
00:41:00.500 --> 00:41:03.599
whims, inflation, and corporate mismanagement.
00:41:03.800 --> 00:41:07.440
The cyber cab, by contrast, gives you the control
00:41:07.440 --> 00:41:10.320
of a small business, but the scalability of software.
00:41:10.579 --> 00:41:13.840
It facilitates compounding returns through immediate
00:41:13.840 --> 00:41:16.980
physical utility during a time of rapid technological
00:41:16.980 --> 00:41:19.840
progress. You own the means of transportation.
00:41:20.360 --> 00:41:22.159
But the most important philosophical takeaway
00:41:22.159 --> 00:41:24.659
from Brian's work is the ultimate purpose of
00:41:24.659 --> 00:41:26.960
this wealth generation. Yeah, why do it at all?
00:41:27.019 --> 00:41:28.739
The ultimate goal of these compounding returns
00:41:28.739 --> 00:41:30.739
isn't just hoarding millions of dollars in a
00:41:30.739 --> 00:41:33.119
bank account or buying a bigger yacht. The analysis
00:41:33.119 --> 00:41:35.480
is very clear on this. It explains that true
00:41:35.480 --> 00:41:38.139
interregnum economics is about securing resources
00:41:38.139 --> 00:41:41.039
to support your higher pursuits. It is about
00:41:41.039 --> 00:41:43.860
buying back your time. Exactly. It's about securing
00:41:43.860 --> 00:41:47.340
the capital necessary to support your intellectual,
00:41:47.679 --> 00:41:50.909
creative, or communal endeavors. If you have
00:41:50.909 --> 00:41:53.530
a robot fleet generating your baseline income,
00:41:53.789 --> 00:41:55.849
you can spend your time writing, researching,
00:41:56.110 --> 00:41:58.309
building community projects, or raising your
00:41:58.309 --> 00:42:00.329
family without the constant pressure of wage
00:42:00.329 --> 00:42:02.800
labor. It is about using these technological
00:42:02.800 --> 00:42:06.539
tools to push society as a whole toward a future
00:42:06.539 --> 00:42:09.059
of greater abundance. It represents a fundamental
00:42:09.059 --> 00:42:11.400
shift toward an economy where individuals can
00:42:11.400 --> 00:42:13.780
actively participate in sustainable, equitable
00:42:13.780 --> 00:42:16.480
growth rather than being squeezed out by corporate
00:42:16.480 --> 00:42:19.420
monopolies. It is an incredibly practical, empowering
00:42:19.420 --> 00:42:22.719
antidote to all the online pessimism. The message
00:42:22.719 --> 00:42:24.659
here is clear. You aren't a victim of the robot
00:42:24.659 --> 00:42:27.139
revolution. You have the blueprint to become
00:42:27.139 --> 00:42:29.579
a fleet commander leveraging intelligent assets
00:42:29.579 --> 00:42:31.690
to free up your own human time and potential.
00:42:31.849 --> 00:42:34.769
Exactly. The analysis concludes by stating that
00:42:34.769 --> 00:42:37.190
this window of opportunity invites participation
00:42:37.190 --> 00:42:40.489
in a broader movement. By deploying capital into
00:42:40.489 --> 00:42:43.090
autonomous networks, you are contributing to
00:42:43.090 --> 00:42:45.309
a legacy of progress that benefits generations
00:42:45.309 --> 00:42:48.409
to come. It requires work though. It requires
00:42:48.409 --> 00:42:51.369
strategic planning, risk tolerance, and immense
00:42:51.369 --> 00:42:54.719
operational adaptability, certainly. But the
00:42:54.719 --> 00:42:57.360
mechanism for true financial independence and
00:42:57.360 --> 00:43:00.579
societal impact is clearly delineated in the
00:43:00.579 --> 00:43:02.960
framework provided. OK, let's bring it all together
00:43:02.960 --> 00:43:06.039
for you. In this deep dive, we have traced the
00:43:06.039 --> 00:43:08.920
incredible century long evolution of the automobile
00:43:08.920 --> 00:43:12.000
from a depreciating labor intensive tool that
00:43:12.000 --> 00:43:15.159
sits idle 95 percent of the time to an autonomous
00:43:15.159 --> 00:43:17.539
networked economic engine that works while you
00:43:17.539 --> 00:43:19.980
sleep. A complete paradigm shift. We have slowly
00:43:19.980 --> 00:43:22.119
crunched the exact numbers of how a six thousand
00:43:22.119 --> 00:43:24.280
dollar starting investment. could theoretically
00:43:24.280 --> 00:43:27.800
snowball into a 300 -car logistics empire generating
00:43:27.800 --> 00:43:30.679
massive monthly cash flow. The compounding math.
00:43:31.000 --> 00:43:33.320
And we've explored how moving beyond the crowded
00:43:33.320 --> 00:43:36.480
city streets could reshape global equity, turning
00:43:36.480 --> 00:43:39.460
these vehicles into rural farming utilities and
00:43:39.460 --> 00:43:42.320
life -saving mobile medical clinics in developing
00:43:42.320 --> 00:43:45.199
nations. We have unpacked a comprehensive vision
00:43:45.199 --> 00:43:48.579
that replaces anxiety about the future with actionable
00:43:48.579 --> 00:43:51.659
mathematical mechanics, showing how the interregnum
00:43:51.659 --> 00:43:54.739
can be navigated thoughtfully and highly profitably.
00:43:54.880 --> 00:43:57.380
Which leaves us with a final lingering thought
00:43:57.380 --> 00:43:59.980
for you to mull over on your own after you finish
00:43:59.980 --> 00:44:02.179
listening. today we've talked all about the machines
00:44:02.179 --> 00:44:04.860
but let's think about the people yes if a six
00:44:04.860 --> 00:44:07.019
thousand dollar investment can theoretically
00:44:07.019 --> 00:44:09.840
build a multi -million dollar fleet of autonomous
00:44:09.840 --> 00:44:12.920
robots in just three years how does that fundamentally
00:44:12.920 --> 00:44:15.400
change the way we teach financial literacy to
00:44:15.400 --> 00:44:17.420
the next generation yeah when the machines are
00:44:17.420 --> 00:44:18.940
the ones out there doing the physical learning
00:44:18.940 --> 00:44:22.039
what becomes the true intrinsic value of human
00:44:22.039 --> 00:44:24.739
time Thank you so much for joining us on this
00:44:24.739 --> 00:44:26.860
deep dive into the Reed Multiflex Interregnum
00:44:26.860 --> 00:44:29.239
series. Keep questioning, keep learning, and
00:44:29.239 --> 00:44:30.260
we will catch you next time.