Latest / Elon Musk Podcast / SpaceX Targets Two Trillion Dollar Orbital IPO

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SpaceX Targets Two Trillion Dollar Orbital IPO · Elon Musk Podcast

• 0:00
  Elon Musk's SpaceX has secured an option to acquire the
• 0:03
  artificial intelligence coding startup Cursor for $60 billion,
• 0:08
  or alternatively pay a $10 billion fee entirely for their
• 0:13
  joint development work. I mean, the dollar amounts
• 0:15
  attached to that agreement are just staggering.
• 0:17
  Yeah, it's a huge number. We are looking at a deal that
• 0:20
  combines the world's most valuable private aerospace
• 0:23
  company with a heavily used enterprise software tool and the
• 0:27
  specific software arrangement it operates as the linchpin in a
• 0:30
  much larger strategy. We're talking about an upcoming
• 0:33
  initial public offering, the complete absorption of the ACC
• 0:37
  AI platform, and the deployment of server farms in low Earth
• 0:41
  orbit. OK, so how does acquiring a
• 0:43
  desktop coding application justify a multi trillion dollar
• 0:47
  aerospace valuation and lead to launching data centers into
• 0:50
  space? Well, the $60 billion cursor
• 0:53
  option exists entirely to bolster the financial narrative
• 0:56
  of the company's upcoming initial public offering.
• 0:59
  They are targeting a 1.75 trillion to $2 trillion
• 1:04
  valuation in this public offering, and they're actively
• 1:08
  seeking to raise up to $75 billion in new capital.
• 1:12
  Wow. I put those numbers into
• 1:14
  perspective for you. Raising $75 billion would easily
• 1:18
  surpass the Saudi Aramco listing.
• 1:20
  Making it the largest effort. Exactly the largest public
• 1:24
  offering in the history of the global capital markets.
• 1:26
  But the revenue multiple required to reach that specific
• 1:30
  target is just astonishing. I mean, if you look at the
• 1:32
  private valuation of the aerospace company just prior to
• 1:35
  these new financial maneuvers, it's sat at roughly $800
• 1:39
  billion. Right, which is already huge.
• 1:41
  Exactly. But jumping from 800 billion to
• 1:43
  a public target of 2 trillion means they are asking public
• 1:46
  markets to price the stock at a 100 to 125 times revenue
• 1:51
  multiple. That's a huge leap.
• 1:53
  It is for an investor to see any mathematical return on a
• 1:56
  multiple that high. The company would require
• 1:59
  roughly 40% annualized revenue growth for an entire decade just
• 2:03
  to break even on the initial pricing.
• 2:06
  And you just do not typically see those kinds of multiples
• 2:09
  applied to companies that manufacture heavy industrial
• 2:12
  hardware. No, definitely not.
• 2:14
  Because manufacturing rockets requires massive capital
• 2:17
  expenditure, you have to build factories, procure raw materials
• 2:21
  like stainless steel and titanium, employ thousands of
• 2:23
  aerospace engineers, and, you know, deal with the physical
• 2:27
  reality of building machines that routinely explode during
• 2:30
  testing. Right.
• 2:31
  Rockets blow up, software doesn't.
• 2:33
  Exactly. Industrial hardware companies
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  traditionally trade at a fraction of that multiple, which
• 2:38
  is exactly why the financial foundation of the company has
• 2:41
  fundamentally shifted toward connectivity.
• 2:43
  The Internet side of things. Right.
• 2:45
  The underlying financials of the Starlink satellite Internet
• 2:48
  division generate the bulk of current revenue.
• 2:51
  The network has expanded to 9.2 million subscribers spread
• 2:56
  across 150 countries. That's a lot of dishes.
• 2:59
  It is. Those subscriptions generate
• 3:01
  roughly $16 billion in annual revenue, and the company reports
• 3:05
  an $8 billion profit from those specific operations.
• 3:09
  OK. But those profit margins require
• 3:11
  incredibly close scrutiny, you know.
• 3:14
  Oh absolutely. The global top line numbers look
• 3:16
  phenomenal On a slide deck, 50% profit margins sound like a
• 3:20
  software company, which is the exact narrative they want to
• 3:23
  push, of course. But when you examine specific
• 3:25
  regional filings, the picture changes dramatically.
• 3:28
  Like there is a specific filing from their European subsidiary
• 3:32
  operating in the Netherlands that shows a Net margin of less
• 3:36
  than 3%. Less than than 3%.
• 3:37
  Less than 3% and the gap between a 3% regional margin and a 50%
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  global margin comes down to a very specific accounting
• 3:45
  mechanism. It's a $4 billion internal
• 3:49
  launch subsidy. Yeah, the mechanics of that
• 3:51
  subsidy are fascinating. The company generates 80% of its
• 3:55
  total launch revenue by paying itself to launch its own
• 3:58
  Starlink satellites. So they're their own biggest
• 4:01
  customer. It operates as a completely
• 4:03
  enclosed economic loop. When a Falcon 9 rocket launches
• 4:06
  a batch of satellites, the Internet division pays the
• 4:09
  launch division. They are booking revenue for
• 4:12
  launches that serve to build their own Internet
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  infrastructure. Moving money from the left
• 4:16
  pocket to the right pocket. Exactly.
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  By moving the money around like that, they can present a highly
• 4:22
  profitable launch cadence while absorbing the actual costs
• 4:26
  within the broader corporate structure.
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  Which fundamentally changes how public markets must evaluate
• 4:32
  aerospace economics. By bundling the hardware
• 4:35
  manufacturing business, the launch services and the high
• 4:38
  margin Internet subscription business together into one
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  single entity, they successfully shift the focus away from the
• 4:45
  low margin realities of building physical rockets.
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  Because nobody wants to invest in low margin hardware.
• 4:51
  Right. So public market investors are
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  being asked to evaluate the entire conglomerate using
• 4:56
  software and connectivity multiples, effectively ignoring
• 4:59
  the traditional metrics used for industrial hardware evaluations.
• 5:03
  But to justify that astronomical valuation jumped to $2 trillion,
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  the company could not just rely on rockets or even the enclosed
• 5:10
  economics of satellite Internet. They needed more.
• 5:13
  They had to alter the fundamental identity of the
• 5:15
  organization by completely absorbing an artificial
• 5:18
  intelligence firm. Okay, the X AI deal, yes.
• 5:21
  They executed an all stock transaction that merged XAI
• 5:25
  directly into the aerospace company.
• 5:28
  That specific merger valued the combined entity at $1.25
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  trillion, and it specifically valued the artificial
• 5:38
  intelligence firm XAI at $250 billion.
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  And the mechanics of an all stock transaction are critical
• 5:45
  to understand here for anyone looking at this deal.
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  No actual cash changed hands to facilitate this.
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  Merger right, No wire transfers. Instead, they essentially
• 5:53
  printed new shares of the combined company and used those
• 5:56
  to absorb the artificial intelligence division.
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  This maneuver allows them to assign these massive private
• 6:01
  valuations without needing to secure hundreds of billions of
• 6:04
  dollars in liquid capital from banks.
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  And this execution relies on a financial concept known as the
• 6:09
  valuation matriyevska. The nesting dolls.
• 6:12
  Exactly. If you picture those Russian
• 6:14
  nesting dolls where one fits perfectly inside the other, that
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  is exactly what they have built with these corporate structures.
• 6:22
  It operates as a sequence of nesting corporate entities.
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  How so? Well, first, the social media
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  platform X was acquired by X AI at a significantly reduced
• 6:33
  valuation. In that step, X cease to be an
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  independent social media business evaluated on its
• 6:39
  ability to generate advertising revenue.
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  Right, the ads don't matter as much anymore.
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  Right. Instead, it became a dedicated
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  data source used specifically for artificial intelligence
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  training. Then the next all was stacked.
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  The newly combined entity of X and XAI was absorbed by the
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  aerospace company. Yeah, hold on, Wait.
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  Back up. I want to make sure you catch
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  this because the structure is dizzying.
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  It really is. So an unprofitable social media
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  platform is inside an AI startup, which is now inside a
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  rocket company. That is the exact structural
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  reality of the organization, and the ownership web extends even
• 7:11
  further than that. Oh yeah, Tesla shareholders,
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  following a previous $2 billion investment in XAI, now owned
• 7:18
  preferred stock in an entity controlled entirely by an
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  aerospace company. That is incredibly messy.
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  And it gets better. The Artificial Intelligence
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  division is carrying high double digit interest rate debt which
• 7:31
  is secured by physical graphics processing units as collateral.
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  The chips themselves. Yes, they pledge their computer
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  chips to secure the loans required to keep the systems
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  running. Wow, securing high interest debt
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  with depreciating computer hardware is incredibly
• 7:47
  aggressive. Very.
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  I mean graphics processing units or GPU's lose value quickly as
• 7:52
  faster, more efficient chips hit the market.
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  If you default on a loan secured by real estate, the bank takes
• 7:58
  the building, which likely holds its value.
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  Land is land. But if you default on a loan
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  secured by a 2 year old computer chip, the bank takes a piece of
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  hardware that might be functional obsolete.
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  But you know, this massive corporate structure limits the
• 8:13
  ability of outside investors to scrutinize the individual cash
• 8:17
  burn or profitability of the social media platform or the
• 8:21
  artificial intelligence division.
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  Because it's all buried. Because they are now shielded
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  completely within the broader aerospace revenue, you cannot
• 8:28
  easily parse out how much money the large language models are
• 8:31
  losing. No, you can't.
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  From a corporate finance perspective, I actually view
• 8:35
  this as a brilliant shielding maneuver.
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  Really. Yeah, they have taken extreme
• 8:40
  cash burn technologies, social media platforms and large
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  language model training and hidden them safely inside a
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  highly profitable government subsidized launch business.
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  It protects the incredibly fragile AI valuation from direct
• 8:55
  public market scrutiny. OK, I view this entirely
• 8:57
  differently. Yeah, you might see a brilliant
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  shielding maneuver, but this operates as a severe governance
• 9:03
  nightmare. How?
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  You mean consolidating these massive, highly distinct
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  businesses without any independent fairness?
• 9:09
  Opinions creates a complete fiduciary stress test.
• 9:12
  Right, the boards overlap. Exactly.
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  When you have overlapping boards of directors and preferred
• 9:18
  shareholders from an automotive company suddenly holding equity
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  in a rocket manufacturer just because the founder decided to
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  merge the entities, it creates A chaotic environment for any
• 9:28
  institutional investor trying to properly assess risk.
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  That's a fairpoint. The blending of high interest
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  debt secured by rapidly depreciating computer chips with
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  revenue generated by launching critical federal satellites
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  creates a highly unstable corporate architecture.
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  So with the artificial intelligence division
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  successfully absorbed into that architecture, the newly combined
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  entity immediately utilized its massive computing power to court
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  CURSOR, which sits as the fastest growing tool in the
• 9:56
  entire enterprise software sector.
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  Right. The mechanics of the Cursor deal
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  present a strict binary choice. The agreement grants an option
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  for an outright acquisition of the startup for $50 billion, or,
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  alternatively, a $10 billion payment specifically allocated
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  for joint development work. And to understand why those
• 10:14
  dollar amounts are so large for a software application, we have
• 10:17
  to look closely at the current AI coding tool ecosystem.
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  It's crowded right now. Very crowded.
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  There are three main approaches dominating the market right now.
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  First, you have GitHub Copilot, which is an accessible $10 a
• 10:32
  month extension that functions essentially as highly advanced
• 10:36
  auto complete. Right, you type it finishes the
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  thought. Exactly.
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  A developer starts typing a line of code and copilot suggests the
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  rest of the line based on the context.
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  Then you have Quad code which takes a completely different
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  approach. It is a terminal native
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  autonomous agent and it features a 1,000,000 token context
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  window. And we should probably define
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  what a token context window actually means for you.
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  Yeah, that's a good idea. In artificial intelligence, a
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  token is roughly equivalent to a word or a piece of a word.
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  The context window is the model short term memory.
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  It's how much information it can hold in its head at one exact
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  moment. So 1,000,000 words.
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  Basically a 1,000,000 token context window means the AI can
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  read and process an enormous amount of an applications code
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  base simultaneously. It scores 80.8% on the SWE bench
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  for complex multi file refactoring.
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  Which is high. Very high.
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  The SWE Bench is a rigorous testing framework that evaluates
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  an AI's ability to solve real world software engineering
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  issues found on platforms like GitHub.
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  Right. Scoring over 80% means the AI
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  can look at multiple interconnected files, understand
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  how a change in one affects the others, and successfully rewrite
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  the code without breaking the application.
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  Finally you have cursor which is a $20.00 a month AI native
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  integrated development environment.
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  An IDE. An IDE?
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  Yeah, unlike Copilot which just sits inside an existing program,
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  Cursor is an entirely self-contained workspace.
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  Cursor excels at visual multi file editing and utilizing
• 12:08
  background agents. Meaning the AI does work while
• 12:11
  you're busy doing something else.
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  Exactly. A developer can highlight the
• 12:15
  section of code, ask the background agent to rewrite it
• 12:17
  to be more efficient, and the AI will complete that task while
• 12:21
  the developer continues working on a completely different part
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  of the application and. Cursor has experienced hyper
• 12:26
  growth within that specific ecosystem.
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  They have reached $2 billion in annual recurring revenue.
• 12:32
  That's. Wild for an enterprise software
• 12:34
  company hitting 2 billion in recurring revenue demonstrates
• 12:38
  extreme stickiness with their client base.
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  Their software is currently used by 67% of the Fortune 500.
• 12:46
  Wow. Yeah, they have successfully
• 12:47
  captured the high end enterprise developer market.
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  But the underlying economics of Cursor's business model show
• 12:54
  exactly why they would agree to this arrangement with the
• 12:57
  aerospace company. The API costs.
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  The API Costs Cursor currently pays retail prices to companies
• 13:03
  like Anthropic and Open AI for direct access to their
• 13:07
  underlying language models. Every single time a Cursor user
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  prompts the system to generate a block of code, Cursor pays an
• 13:15
  API fee to the very companies they are competing against in
• 13:18
  the broader AI market. It's.
• 13:19
  Huge disadvantage. They are effectively funding
• 13:22
  their own direct competitors just to keep their software
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  functioning. Which is why the $10 billion
• 13:27
  alternative payment opens up a Compute for equity handshake.
• 13:30
  Cursor gets direct access to the Colossus supercomputer, which
• 13:34
  possesses computing power equivalent to 1,000,000 NVIDIA,
• 13:38
  each 100 chips. That is an unbelievable amount
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  of power. Is this access allows Cursor to
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  train their own proprietary coding models without relying on
• 13:48
  their competitors infrastructure?
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  And what does SpaceX get? In exchange, the aerospace
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  company gains immediate access to a massive stream of
• 13:55
  enterprise software revenue, which creates a highly
• 13:59
  attractive software narrative to bolster the financials of their
• 14:03
  upcoming public offering. The massive volume of compute
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  required to train proprietary models for tools like Cursor,
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  combined with the energy demands of the Colossus supercomputer,
• 14:13
  is rapidly exhausting the physical limits of Earth's power
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  grid. We're just running out of power.
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  We are simply running out of places to plug these machines
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  in. This severe resource exhaustion
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  has led to the most extreme proposal the aerospace company
• 14:27
  has ever produced. They submitted a formal filing
• 14:30
  to the Federal Communications Commission requesting
• 14:32
  authorization for an entirely new non geostationary orbit
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  system. A new satellite constellation.
• 14:38
  Yes, the application details a network of up to 1,000,000
• 14:42
  individual satellites designed specifically to function as
• 14:45
  fully operational orbital data centers.
• 14:47
  The physics and orbital parameters of this plan are
• 14:50
  fascinating to examine. The satellites would operate at
• 14:54
  altitudes between 502,000 kilometers above the Earth,
• 14:58
  specifically utilizing Sun synchronous orbits.
• 15:01
  Which is a very deliberate choice.
• 15:03
  Right. This exact orbit matters
• 15:05
  immensely because the satellite rides the Terminator line.
• 15:09
  The Terminator line is the dividing boundary between day
• 15:12
  and night on Earth. By matching the satellites
• 15:14
  orbital speed with the Earth's rotation around the sun, the
• 15:18
  satellite never falls into the planet's shadow.
• 15:21
  This specific placement allows for near constant solar
• 15:24
  exposure. And because the solar panels are
• 15:27
  operating in the vacuum of space, there is absolutely no
• 15:30
  atmospheric filtering of the sunlight.
• 15:32
  So it's perfectly clear. Yes.
• 15:34
  On Earth, clouds, dust, and the atmosphere itself scatter the
• 15:38
  light before it ever hits a solar panel.
• 15:40
  In space, the light hits the panels with complete intensity,
• 15:43
  and because they are riding the Terminator line, there are no
• 15:46
  nighttime cycles to interrupt power generation.
• 15:48
  Constant power. A solar panel in this specific
• 15:50
  orbit can generate up to 40 times more usable energy than an
• 15:54
  identical panel placed on the surface of the Earth.
• 15:57
  But the technical infrastructure required to link 1,000,000
• 16:00
  server nodes in space is highly complex.
• 16:03
  The system relies entirely on high bandwidth optical inter
• 16:07
  satellite links. Yeah, they are essentially
• 16:10
  creating a vast laser mesh network in a vacuum to rapidly
• 16:15
  route data traffic between the servers and down to the ground
• 16:18
  stations. Right?
• 16:19
  Furthermore, placing these incredibly heavy compute nodes
• 16:22
  into space relies entirely on the Starship vehicles 200 ton
• 16:26
  payload capacity. A standard communications
• 16:29
  satellite weighs a fraction of what a server rack weighs.
• 16:33
  No other launch vehicle currently in existence possesses
• 16:35
  the raw lift capability required to physically transport this
• 16:39
  much heavy server hardware into orbit.
• 16:41
  Wait, let me just pull back here for a second.
• 16:43
  Because we are talking about launching massive server farms
• 16:45
  into the vacuum of space simply because we literally do not have
• 16:49
  enough electricity available on the ground to power the
• 16:51
  artificial intelligence industry.
• 16:53
  Exactly. We are out of juice down here,
• 16:55
  so we have to go up and the financial equation provided by
• 16:58
  the company in their filings attempts to rationalize the
• 17:01
  physics of doing this. How do they justify the cost?
• 17:03
  They claim that with the launch cost of the Starship vehicle
• 17:07
  dropping below $100 per kilogram, orbital computing
• 17:10
  could actually become 25% cheaper than running ground
• 17:14
  based operations. Really.
• 17:15
  Cheaper. Yes, think about what goes into
• 17:18
  building a terrestrial data center.
• 17:20
  You have the rising cost of commercial real estate.
• 17:23
  You have massive terrestrial grid interconnection delay where
• 17:27
  power companies tell developers they will have to wait years
• 17:30
  just to hook up a new facility. Because the grid can't handle
• 17:32
  it. Right, you also have the immense
• 17:34
  cost of cooling infrastructure. Keeping 1,000,000 running
• 17:37
  computer chips from melting down requires millions of gallons of
• 17:41
  water and massive industrial air conditioning systems.
• 17:45
  By moving the servers to a vacuum that sits near absolute
• 17:48
  0, the cooling problem is functionally solved by the
• 17:52
  environment itself. That's fascinating, and they aim
• 17:55
  to eventually generate 100 gigawatts of compute capacity
• 17:59
  through this orbital network. 100 gigawatts.
• 18:02
  In the regulatory filing, they specifically describe this
• 18:05
  energy capacity as a step toward achieving A Kardashev Tucker
• 18:09
  level civilization. Oh, the Kardashev scale.
• 18:12
  Yeah, the Kardashev scale is a method of measuring a
• 18:15
  civilization's level of technological advancement based
• 18:18
  entirely on the amount of energy it is able to harness.
• 18:20
  OK, remind me how that works. A type of civilization can
• 18:23
  harness all the energy of its its home planet.
• 18:26
  A Type 2 civilization can harness all the energy of its
• 18:29
  home star by moving power generation and computation
• 18:33
  directly into space to capture unfiltered solar energy.
• 18:36
  They are framing this infrastructure project as an
• 18:39
  evolutionary leap in human technology.
• 18:42
  This physically relocates the primary bottleneck of artificial
• 18:45
  intelligence development. The constraint limiting AI
• 18:48
  growth is no longer the physical power grid infrastructure or the
• 18:51
  availability of real estate on Earth.
• 18:54
  The new bottleneck is strictly launch cadence and payload
• 18:57
  capacity in space. If a company wants more
• 19:00
  computing power, they physically have to launch more rockets to
• 19:04
  put more servers into orbit. But relocating critical
• 19:07
  computing infrastructure into orbit using a complex mix of
• 19:10
  international software and hardware components immediately
• 19:14
  triggers intense government scrutiny.
• 19:16
  Oh, I'm sure regulators love this.
• 19:18
  Not at all. The regulatory backlash against
• 19:20
  this plan is already servicing rapidly US senators have
• 19:24
  formally demanded probes into the company regarding strict
• 19:27
  foreign ownership control or influence rules.
• 19:29
  Oh, because of the funding. Exactly.
• 19:31
  There are specific detailed reports outlining undisclosed
• 19:35
  funds being routed through various entities in the
• 19:37
  Caribbean and the British Virgin Islands, specifically to
• 19:40
  purchase private shares in the aerospace firm.
• 19:43
  And this intense scrutiny connects directly back to the
• 19:45
  foundational code of the artificial intelligence models
• 19:48
  themselves. There is intense controversy
• 19:50
  currently surrounding Cursor's Composer 2 model.
• 19:53
  Right, the code origin. It was discovered that the
• 19:55
  system was secretly built upon the Chinese artificial
• 19:58
  intelligence model known as Kimi K 2.5.
• 20:01
  And the broader legislative actions responding to these
• 20:04
  discoveries are severe. Very severe.
• 20:07
  There is the No DeepSeek on Government Devices Act moving
• 20:10
  through the Legislature, along with bipartisan bills
• 20:13
  specifically barring federal contractors from utilizing any
• 20:18
  artificial intelligence models affiliated in any way with
• 20:21
  foreign adversaries. But you know, utilizing open
• 20:24
  weight international models like Kimi or DeepSeek is entirely
• 20:28
  standard practice for rapid iteration in the technology
• 20:31
  sector. Sure, in standard tech.
• 20:33
  Right. Developers take the absolute
• 20:35
  best available open source tools, refine them locally, and
• 20:39
  build specialized application layers directly on top of them.
• 20:42
  That is exactly how the software industry continuously achieves
• 20:45
  hyper growth. Yep, punishing a company for
• 20:48
  using the most efficient, effective code available stifles
• 20:51
  global innovation and completely misunderstands how global
• 20:54
  software development actually functions in reality.
• 20:57
  I get that, but a defense contractor cannot have
• 21:00
  undocumented code originating from foreign adversaries
• 21:04
  embedded within its core infrastructure.
• 21:07
  You think it's too risky? It's not simply a matter of
• 21:09
  software efficiency or speed of development.
• 21:11
  It is strictly about data security and the severe
• 21:15
  potential for espionage. OK, fair.
• 21:17
  When an aerospace company is responsible for managing highly
• 21:20
  classified national security payloads and they decide to
• 21:23
  integrate an AI tool built on a foreign adversaries architecture
• 21:27
  into their operational network, the risk of hidden back doors or
• 21:31
  data exfiltration becomes a profound vulnerability.
• 21:34
  The geographic origin of the code strictly dictates the
• 21:37
  operational security of the entire system.
• 21:39
  And this intense regulatory scrutiny is severely limits
• 21:42
  their operational freedom and directly threatens a $24.4
• 21:46
  billion backlog in Department of Defense and National
• 21:49
  Reconnaissance Office contracts. $24 billion on the line.
• 21:53
  Yeah, if the federal government strictly enforces these foreign
• 21:57
  influence roles, it could potentially force the company to
• 22:00
  completely RIP out the foundation of its newly acquired
• 22:04
  artificial intelligence tools, crippling the very software
• 22:07
  narrative they are utilizing to sell the public markets on a $2
• 22:10
  trillion valuation. Which is wild.
• 22:14
  By wrapping rockets, satellite Internet and advanced coding
• 22:18
  software together into a single massive financial package, the
• 22:22
  company is attempting to construct an entirely
• 22:24
  independent off planet computing infrastructure while
• 22:27
  simultaneously commanding the largest public valuation ever
• 22:31
  seen. So will public market investors
• 22:33
  agree to price the sprawling conglomerate based strictly on
• 22:36
  its off planet computing dreams? Or will the intense regulatory
• 22:40
  risks and the staggering cost of launching the hardware drag the
• 22:44
  entire valuation right back to Earth?
• 22:46
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