Cassidy: SpaceX put an $18.4 billion AI bet on the board—and Wall Street’s already asking who pays for the encore.
Cassidy: Quick catch-up: SpaceX has been building an AI compute business alongside its space operations.
Cassidy: It reported 1.4 gigawatts of nameplate compute at the end of the second quarter and is targeting more than 2 gigawatts by year-end.
Cassidy: Longer term, it’s aiming for up to 20 gigawatts of AI power and cooling capacity by late 2027, built on Nvidia Vera Rubin systems.
Bill: This is AI Daily Briefing.
Bill: SpaceX says the payoff comes fast.
Bill: Investors just put a price on that claim.
Bill: Let’s start there. This story isn't over: SpaceX AI compute buildout.
Bill: Follow us wherever you're listening, and the next chapter comes to you.
Cassidy: From Ari Levy, Lora Kolodny at CNBC:
Quote: After SpaceX spent way more on its AI buildout than analysts expected
Quote: executives tried to convince investors on Tuesday that it's all worthwhile
Quote: claiming that the company is making its money back within a year.
Quote: The message didn't resonate, as SpaceX shares sank following the company's first earnings report since its IPO in June.
Cassidy: SpaceX’s first post-IPO earnings report put an $18.4 billion quarterly capex bill in front of skeptical investors.
Cassidy: That’s more than double quarterly sales, with over 80% aimed at AI.
Bill: Wall Street got the one-year-payback pitch, then marked the stock down 7.5% after hours.
Bill: That’s a live stress test: real money voting against the slide deck.
Cassidy: CFO Bret Johnsen pointed to $6.7 billion in newly contracted cloud-services revenue, ramping in October.
Cassidy: Fine—show me that ramp against an $18.4 billion quarter, because those are very different-sized numbers.
Bill: Capex rose more than sixfold year over year.
Bill: Glad they beat revenue estimates, but “efficient” has to survive 3 a.m.
Bill: utilization, power bills, and customers actually consuming the compute—not just signing contracts.
Cassidy: Alex K.T. Martin, writing in The Japan Times:
Quote: The country’s biggest data center operator
Quote: which is owned by government-backed NTT
Quote: intends to add roughly 750 megawatts of capacity over the next seven years to meet soaring demand from companies seeking to catch up in
Quote: artificial intelligence
Quote: people familiar with the matter said.
Cassidy: NTT Data is eyeing a ¥1.5 trillion plan to reach one gigawatt in Japan by 2033—roughly 750 megawatts added over seven years.
Cassidy: Seven years. The build schedule is setting the pace now, not the model-release calendar.
Bill: That ¥2 billion to ¥2.5 billion per megawatt estimate doesn’t include the Nvidia accelerators.
Bill: So the $9.6 billion headline covers building and power before you buy the expensive part that actually runs the workload.
Cassidy: We just heard Wall Street push back on SpaceX’s one-year AI-capex payback.
Cassidy: NTT’s plan at least puts the physical timeline out in the open: that capacity doesn’t arrive until 2033.
Bill: A gigawatt is serious.
Bill: But every enterprise buyer in Japan hoping to catch up on AI should notice the date attached to it: 2033.
Bill: Hardware roadmaps move a little faster than construction permits.
Cassidy: Dan Robinson, writing in The Register:
Quote: Amazon is now upping its forecast for how much capex it will spend this year on expanding its infrastructure
Quote: including that needed for those AI workloads.
Quote: "Earlier this year we said we plan to invest approximately $200 billion in cash capex in 2026
Quote: the majority of which to support AI and AWS," Jassy told analysts on a conference call about its financials.
Bill: Amazon just raised 2026 cash capex from $200 billion to $220 billion, partly because memory costs rose.
Bill: And Jassy says even that won’t cover demand through 2027.
Bill: At some point, “we can’t build fast enough” is a very expensive forecast to get wrong.
Cassidy: The Register puts the aggregate at roughly $595 billion across Amazon, Google, and Microsoft.
Cassidy: Grid connections and memory supply don’t bend to a model-launch calendar.
Cassidy: Neither do construction crews.
Bill: AWS pulled in $42.2 billion this quarter, up 36.7 percent, so it’s not spending on vapor.
Bill: But fast-growing revenue and a quick payback on $220 billion are two different spreadsheets.
Bill: SpaceX just got that lesson priced into its stock.
Cassidy: Exactly. A $169 billion annualized AWS run rate is enormous—Fortune 500 scale on its own—but it doesn’t make the denominator go away.
Cassidy: Wall Street is finally asking whether all this physical buildout has a revenue ramp behind it.
Cassidy: Converge Digest, with Jim Carroll:
Quote: CoreWeave announced plans to expand its AI cloud platform into Indonesia
Quote: marking the company’s first data center presence in the Asia-Pacific region.
Quote: The expansion will add three facilities with a combined 360 megawatts of contracted IT power
Quote: with the sites expected to come online in 2028.
Bill: CoreWeave has 360 megawatts of contracted IT power across three Indonesian sites, but the machines don’t arrive until 2028.
Bill: Investors are pricing demand years before any hardware serves a single latency-sensitive workload.
Cassidy: And CoreWeave will own and operate the compute environment itself.
Cassidy: For Southeast Asian customers with data-locality rules
Cassidy: control over the inference stack may matter more than whose logo is on the accelerator.
Bill: Wall Street just flinched at SpaceX’s one-year payoff pitch.
Bill: CoreWeave has until 2028—but 360 megawatts is still an expensive bet on local demand showing up on schedule.
Cassidy: NTT Data has seven years to pursue a gigawatt in Japan; CoreWeave’s first Asia-Pacific footprint comes online in 2028.
Cassidy: Model cycles run in months.
Cassidy: Grid capacity, permits, and local operating teams are setting the calendar.
Cassidy: DataMagz writes:
Quote: Samsung SDS has launched South Korea’s first NPU-as-a-Service (NPUaaS) platform
Quote: providing enterprises with on-demand access to FuriosaAI’s RNGD artificial intelligence inference accelerators through the Samsung Cloud
Quote: Platform. The service enables organisations to run AI inference workloads without deploying dedicated hardware.
Cassidy: Samsung SDS is putting FuriosaAI’s RNGD chips inside Samsung Cloud, with one-, two-, four-, and eight-card instances.
Cassidy: That matters: a Korean enterprise can tune its deployment and run inference without handing the whole operating layer to an American
Cassidy: hyperscaler.
Bill: Furiosa has set a baseline: 512 FP8 teraflops at 180 watts per accelerator.
Bill: Eight cards fit in a roughly 3-kilowatt server.
Bill: Now Samsung SDS has to prove the boring but decisive part—throughput per dollar on an actual customer workload.
Cassidy: After all the hundreds of billions in capex we just ran through, this is more useful than another glossy facility rendering.
Cassidy: NPUs run finished models, and Samsung SDS is selling access to that inference layer as a product.
Bill: Right. “Agentic workloads” sounds lovely until the eighth step fails and somebody gets paged.
Bill: But if RNGD delivers comparable latency for less than the Nvidia cloud bill, Korean teams will switch fast.
Bill: Enterprise procurement is never sentimental.
Cassidy: Want to go deeper on the infrastructure behind AI?
Cassidy: Try The Data Center Daily—a daily briefing on AI compute
Cassidy: hyperscaler capex the power grid
Cassidy: chip supply and energy markets reshaped by intelligence at scale.
Cassidy: Find it wherever you get podcasts.
Cassidy: One thing to watch: SpaceX says its newly contracted $6.7 billion in cloud-services revenue begins ramping in October.
Cassidy: Links to every story are in the show notes.
Cassidy: Check out the ones that caught your attention.
Cassidy: That’s AI Daily Briefing for today.
Cassidy: This is a Lantern Podcast.