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BG2 Pod

The SpaceX IPO, Fable 5, AI Capex Update & Market Check w/ Gavin Baker

1h 20m · Transcribed via assemblyai · Watch on YouTube

Brad Gerstner hosts Gavin Baker (Atreides), Andrew Fox and Altimeter partner Clark Tang two days before SpaceX's record IPO ($135/share, **$1.77 trillion valuation**, banks modelling ~$160bn revenue by 2028). The frame: don't pump it, decompose it from first principles. The bull case rests on three terrestrial legs that all 'pencil' before you need the moonshot. (1) **Launch + Starlink** — rapid Starship reusability drives cost per kg from ~$1,500 on Falcon toward sub-$250, and Starlink direct-to-cell can plausibly 5x connectivity revenue from ~$10bn to ~$50bn (still only 0.3% of the global telecom market). (2) **AI compute ("Elon Web Services")** — the surprise of the last six weeks: SpaceX struck huge compute resale deals with Anthropic and Google and **went from non-hyperscaler to #4 in 30 days, passing Oracle**, monetising at $22-23bn/GW (Anthropic) and ~$50bn/GW (Google) vs an implied $14bn/GW in the model. (3) **The model itself — the panel's highest-conviction overlooked upside:** the Cursor acquisition (~700-800 people, ~$10bn run-rate) injects proprietary coding data into Grok 4.3 training; Composer 2.5 was Pareto-dominant on coding 12 days ago. Orbital compute is a call option, not a requirement: Fox lays out **~$5bn/GW capex to put compute in space vs ~$20-25bn/GW terrestrially** — a 5x cut on half the bill of materials, assuming satellite reliability holds. On the broader capex debate, Gerstner flags Morgan Stanley lifting 2027 capex to $1.1tn (he thinks ~$1.5tn incl. SpaceX/CoreWeave) against ~$300bn inference revenue; the panel argues the math 'maths' because inference gross margins are 50-70%+ and revenue is being underestimated (>$200bn this year). On models: Fable 5 / Mythos and ChatGPT 5.5 mark a new class defined by long-running tasks — Noam Brown's point that benchmarks should be measured in time/tokens, not snapshots, made Baker 'a lot more bullish' on compute. The open-source debate resolves to 'two things can be true': **frontier captures ~90% of economic value while open source is ~80% of tokens** — bearish for frontier-lab margins but bullish for compute. Market check: Gerstner trims from 'large' to 'medium-small' into a seasonally weak, inflation-pressured summer (CPI ~4.2%), but stays structurally long.

Key points

Notable quotes

In 30 days we went from not being an AI hyperscaler to being number four and we passed a lot of companies, including Oracle.

B · 18:36

The implied monetization rate on that number is something like $14 billion per gigawatt per year for the AI business.

D · 24:04

But the math you get to is it's about $5 billion per gigawatt of capex to put these in space.

D · 26:52

And then it is a little funny to me that it was 100 times trailing TTM revenue.

B · 39:23

And so I think for most institutional investors, it's a must buy, A must own is, set it and forget it, right?

A · 36:39

Because nobody has run Mythos for a year continuously.

B · 44:22

90% That has been decisively wrong, probably more than 90% and it may continue to be decisive.

B · 53:32

So the better open source does, the better it is for compute providers.

B · 54:04

And especially as long as we are in a Watt constrained world, if you can get more tokens per watt, which is literally revenue with Nvidia, then a lot of alternatives, just if you build your factory with another chip, you may save some money, but you're going to have less revenue and the margins may be lower.

B · 1:01:48

Less than 0.2% of people on Earth are actually using AI in an agentic way.

D · 1:07:55

Themes

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