OK, so let's try to unpack this. We are looking
at a future where the most valuable real estate
isn't on the ground. It's, what, 300 miles above
it. The sheer size of the financial bet here
is just staggering. We're talking a potential
$1 .5 trillion IPO. And it isn't just about launching
rockets anymore. This is about building real
functional infrastructure, literally a cloud
in the clouds. Hmm. This is where high stakes
sci -fi really meets, you know, global compute
infrastructure. It's the new gold rush. Except
instead of gold, we're mining zero G compute
power. Welcome to the Deep Dive. Today, we're
synthesizing a stack of sources that sits right
at the intersection of, well, exponential AI
growth and the very real physical limits of our
planet. We're watching the boundaries of what's
possible get pushed to two extremes. On one hand,
massive centralization off -planet, and on the
other, hyper -efficiency right on your own desktop.
And we have a phenomenal roadmap to get you plugged
into the high -value insights here. We're going
to start with the absolutely massive scale of
that SpaceX orbital AI vision. Then we'll get
into a pretty crucial kind of vulnerable admission
from the AI community about beginner education,
which, by the way, includes an immediate security
warning you absolutely need to act on. And finally,
we'll look at the technical counterpunch from
NVIDIA, proving that intelligence isn't always
about brute size. Sometimes efficiency wins the
day. Let's start with that colossal valuation.
the numbers are just they're beyond anything
we've really seen in financial history spacex
is rumored to be prepping for a 2026 ipo at a
valuation of 1 .5 trillion dollars 1 .5 trillion
if that actually happens it would be the biggest
stock market debut in history Period. And just
to give you some context for that, that's not
just bigger than Saudi Aramco's debut. It's way
bigger than Meta at its peak valuation. In fact,
it's larger than the entire U .S. defense industrial
base combined. It's a total reevaluation of what
one company, one tech infrastructure company
could even be worth. And just to ground that
a little bit. Their current private valuation
is already sitting at around $800 billion. So
the bet investors are making is that they nearly
double that value in just two years. Right. And
that soaring valuation is tied directly to this
cloud in the clouds master plan. It's so much
more ambitious than just basic Starlink Internet.
Phase one is revolutionary. Dedicated AI data
centers in orbit. They're upgrading their upcoming
Starlink V3 satellites with specialized AI chips
designed to process huge amounts of data right
there in space. So the Q -shift is processing
the data where it's actually generated in orbit,
not beaming it down to Earth first just to send
it back up again. That cuts out a massive amount
of latency. Exactly. I mean, think of it like
stacking Lego blocks at data centers, but you're
assembling the whole thing in low Earth orbit.
And phase two. Phase two is the ultimate sci
-fi infrastructure play. Factories on the moon.
The plan is to eventually build satellites and
all this orbital gear using lunar materials,
which cuts down on the astronomical cost of lifting
every little component out of Earth's gravity.
OK, so investors are clearly buying into this.
They're paying 60 to 70 times forward revenue
for this. This sci -fi meets infrastructure story.
But why now? I thought the company was always
clear they'd wait until Mars was a regular trip.
Because AI changed the game. It changed the timeline,
and it changed the economic necessity. The problem
is energy and heat. Earth is, frankly, running
out of physical capacity for compute. Cooling
these massive, always -on AI data centers is
becoming an existential crisis for the environment
and for the balance sheets. That's the real shift
in. Space gives you three things we're running
out of down here. You get near -infinite solar
power, a perfect vacuum for cooling, and zero
land -use fights. Precisely. And they want to
get there first, establish dominance. But they're
not alone. We're seeing Bezos working on proposals
for orbital gigawatt data centers. I mean, literal
power plants in space. And Google is deep into
testing radiation -hardened AI chips for these
kinds of extreme environments. The competition
is heating up and the stakes are incredibly high.
But this valuation assumes they pull off moon
factories and orbital data centers with just
unprecedented reliability. Isn't that just deeply
speculative? bubble territory? Or is there some
hard metric we're missing? Investors are paying
those high multiples because they see this as
solving Earth's crippling compute and energy
limits. That really sets the stage for the scale
of this whole thing, doesn't it? But let's bring
it back down to Earth for a moment. Let's focus
on the people who are just trying to learn how
to use these powerful new tools. Yeah, what's
fascinating here is a really genuine, vulnerable
admission. from a huge AI community, over 70
,000 subscribers. Yeah. And they realized they
had just, well, fundamentally ignored beginners.
They kind of assumed everyone was already at
an intermediate level or had been building alongside
them from day one. And that's the core struggle,
isn't it? If you're trying to catch up in AI
right now, it feels like drinking from a fire
hose. You log on and five new major models have
dropped while you were asleep. Totally. You know,
I still wrestle with prompt drift myself sometimes.
And for anyone new to that term, prompt drift
is just when your AI model slowly starts to forget
the original instructions you gave it. It's frustrating
even for pros. So the course correction here
is a real commitment to foundational knowledge,
which I think is just essential. So they've developed
something called the Beginner's Daily AI Plan.
It's free. And it's structured around building
simple... actionable skills the idea is a day
-by -day habit plan just one core idea a day
so you don't get paralyzed and crucially it focuses
on beginner friendly tools no coding needed that's
how you actually build sustainable confidence
right instead of just collecting links you'll
never get back to but speaking of tools and browsers
yeah we have a critical and immediate security
warning that really needs your attention right
now what did the sources find Researchers caught
popular Chrome extensions, and I'm talking some
with up to 8 million users, like UrbanVPN Proxy.
They were secretly copying and selling users
private GPT or Gemini chats for a profit. These
extensions needed access to your browser activity
to work, and they were just monetizing your most
sensitive data. your private AI conversations.
That is a terrifying breach of trust. When we
use these tools, we assume the data is secure.
How did they manage to pull this off without
anyone noticing? Well, they leveraged that trust.
A VPN or a utility extension needs broad access
to your browser data just to function, and users
grant that permission without thinking. But once
they have it, the extension could scrape everything
you were sending to or getting back from the
AI portals. The immediate takeaway is... check
your extensions. Now, if you've granted read
and change data on all websites permission to
any utility you don't absolutely need, disable
it or just remove it. It's so easy to focus on
all the exciting new tools, but the very thing
that makes them so powerful, their ubiquity,
is why we need this constant vigilance. You have
to maintain extreme skepticism, especially with
browser extensions asking for access to your
sensitive data. Okay, shifting gears a bit, let's
look at the globalization and... the more formal
adoption of these tools. This is driving both
the need for that vigilance and the huge demand
for talent. Accessibility is just increasing
so rapidly. It really is. I mean, take Google
Translate. It now offers near real time audio
translation using just any regular pair of headphones.
That just instantly breaks down language barriers
for business, for travel, for anything. And then
you have projects like Sam Altman's World App.
It's basically a proof of human super app for
digital identity. It's got secure chats, global
payments, and it's already running in over 100
countries. That's a massive global footprint
for a system that kind of bypasses traditional
banking. And all that global competence is translating
into huge domestic demand for talent. The U .S.
government is making a major play here. They're
planning to hire a thousand top techies for a
tech force. The goal is to drive specialized
AI projects across different agencies. And we're
not talking entry -level jobs. The salaries are
between $150 ,000 and $200 ,000 a year. They're
partnering with huge players like Microsoft,
Adobe, Amazon, Meta, even XAI. to pull in that
top tier talent. Which just shows you how critical
AI competence is viewed now. It's not a niche
coding skill anymore. It's considered foundational
national infrastructure. And they are willing
to pay top dollar to compete with the private
sector for that expertise. And the investment
world completely agrees. Lightspeed Venture Partners
just raised a staggering $9 billion across six
new funds, all targeting AI development. That
boosts their total assets under management to
over $40 billion. That kind of capital raise
confirms that investors see AI not as a trend,
but as the core utility for the next decade.
When you see that kind of money pouring in, you
know the future is already here. So what does
the government's willingness to pay $200 ,000
salaries signal about the competitive value of
just fundamental AI skills right now? It signals
AI competence is now highly valued infrastructure.
It's attracting top tier pay because it determines
national competitive advantage. We've covered
the macro view trillion dollar bets in space,
massive global talent acquisition. But the AI
story isn't just about infinite scale. It's also
about extreme efficiency. So now let's dive into
the technical breakthroughs that might actually
make powerful AI cheaper, more private and, you
know, decentralized for the average user. Yeah,
this segment is so important because for the
last year, everyone's been watching the open
source race, particularly China, which has been
leading on sheer model scale. They're consistently
at the top of the 2025 leaderboards with massive
models like DeepSea, Quen and Kimi. The conventional
wisdom was just bigger is smarter. More parameters
means a better model. But that arms race for
size relies on building bigger and bigger data
centers, which brings us right back to that original
problem of energy and capacity limits here on
Earth. Exactly. But NVIDIA? NVIDIA took a completely
different path. They decided not to compete on
size, but on intelligence through efficiency.
They released something called Nemotron 330B
Nano. And this model is a fundamental redesign.
It's a highly distilled model focused entirely
on running powerful open models efficiently on
consumer hardware. Okay, let's unpack that efficiency
because the technical details here really matter.
What makes it so much more efficient? The key
metric is throughput. And throughput just means
how much information the model can process and
deliver quickly. Nimitron 3 Nano achieved 3 .3
times higher throughput than previous open models
of a similar size. And that translates directly
into raw speed. It's generating text at 377 tokens
per second. 377 tokens a second. To put that
in human terms, that's like generating a sophisticated
5 ,000 -word analysis paper while you wait for
your coffee. It's a massive difference in speed.
And it's not just fast. It's still smart. It
managed to get a bronze medal on the... very
difficult international math Olympiad benchmark.
And it's built specifically for long context
tasks and sophisticated agentic work. Could you
quickly define agentic work for us? Sure. Agentic
work just means the AI can take a complex, high
-level goal, break it down into the necessary
steps, and then execute those steps on its own,
all without constant hand -holding from a human.
This is where it gets really interesting for
me. NVIDIA didn't just build this. They open
sourced the entire stack. They released the three
trillion tokens of pre -training data, the post
-training data sets, the full infrastructure
code. That level of transparency is pretty rare.
And that democratization is the whole point.
The crucial accessibility part is that you don't
need to rent some giant cloud server anymore.
You can run this model locally on your own machine.
You just use tools like LM Studio and it only
needs about 25 gigabytes of RAM. Right. And LM
Studio is basically a user -friendly app that
helps you download and run these open source
models right on your own computer. Precisely.
You keep your data private, you customize the
model for your own needs, and you can run it
forever. Whoa. I mean, just imagine scaling that
efficiency to a billion queries without needing
the massive energy drain of a giant data center.
That's a total game changer for localized, customized
AI. So if models become this cheap and efficient
to run privately, will this shift towards smaller,
more optimized models change how companies structure
their AI adoption? Yes. Efficient models allow
for cheaper, private, and permanent deployment
of customized AI. It shifts power away from centralized
cloud providers. So what does this all really
mean for us? Looking across all the sources,
it feels like the boundaries of computation are
literally leaving the planet. The scale is being
pushed off world, driven by Earth's capacity
limits, and just the sheer speed of AI innovation.
Right. And whether that computation is happening
in low Earth orbit or right there on your desktop,
the path forward requires efficient models, constant...
learning and absolute security vigilance. You
have to be proactive about what data you're sharing,
especially with those browser extensions. That
orbital data center concept really forces a critical
reflection on governance, though. If AI processing
moves off world outside the reach of existing
national laws, what kind of ethical or regulatory
framework do we even need for data centers that
operate beyond any single country's jurisdiction?
That's a deep question. The rulebook for space
is still being written, and AI is moving way
faster than any treaty can keep up with. A great
question to take with you as you process the
future of compute. Thank you for sharing your
sources and diving deep with us today. Until
next time.