Borrowing constraints could slow spending if AI revenues lag
it would be really sweet if the intersection was the peak of the bubble
The end of the self-funded AI buildout?
Hyperscaler cash capex is growing much faster than cash inflows. On current trends, they will be unable to fully fund the AI infrastructure buildout with cash from operations by the end of this year.
Positive users see further AI scaling, debt financing or margin gains sustaining hyperscalers' infrastructure buildout, while negative users call the capex surge outpacing cash flows an unsustainable risky bet.
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There's still headroom for hyperscalers to take out debt. They're less levered than typical large companies (except Oracle). But this does suggest that the age of speculative compute scaling will soon draw to a close. From here it will increasingly depend on AI-specific revenues.
The end of the self-funded AI buildout?
Hyperscaler cash capex is growing much faster than cash inflows. On current trends, they will be unable to fully fund the AI infrastructure buildout with cash from operations by the end of this year.
like you could have seen the top coming years in advance
it would be really sweet if the intersection was the peak of the bubble
While these companies continue to be profitable, and all but Oracle still have substantial cash reserves, most have already turned to external financing to fund their growing investments in AI infrastructure, e.g., Alphabet's recent $85 billion equity raise.
Read more: https://epoch.ai/data-insights/hyperscaler-capex-vs-cash-flow
@scaling01 Nah, debt financing keeps it going
@scaling01 that's the beginning, not the end
it would be really sweet if the intersection was the peak of the bubble
@EpochAIResearch Fair… but they’re all (ex-oracle) <0.5x levered… folks act like they’re at 6x+ with inability to service debt
@Jsevillamol why only up to a multiple?
@Jsevillamol I think this will be the first real driver of real rates movement, depending on how aggressive they will be. After that we’ll see an explosion in the rates only once macro data starts showing signs of job displacement/growth.
@huskies20001 @EpochAIResearch agree that they can fund plenty more buildout with debt, just noting a regime change from when they didn't need to use debt at all
@Jsevillamol The clear triggers will be lab revenues (and resulting hyperscaler/supply chain revenues) which is largely a function of capabilities - each levelling up unlocking a new set of tasks that can be automated (and revenues with it)
@Jsevillamol It’ll be slow at first with no clear narrative attachment to AI, and then violent, during which there’ll be large dispersion trades to do where long duration stocks that aren’t seeing the requisite revenue growth are hammered and others explode on revenue projections.
@EpochAIResearch Hyperscalers have been issuing both equity and debt to fund CapEx for a while now, especially debt.
@scaling01 can you explain your reasoning? you seem to believe AIs will keep getting better, but somehow this means labs/faang are overspending, and this is a bubble, and it will burst soon?
@scaling01 Looks like hyperscalers will need to start cutting human headcount to save costs.
Google alone spends $70 billion annually on human compensation.
@scaling01 they say it every cycle lol. this time feels different right up until it doesnt
@scaling01 Please be quiet love
Am listening for trouble
@Jsevillamol Curious what you see as the equilibrium (fully diffused) revenues of Fable level models if we see no improvement from here, taking into account expected efficiency gains/commoditisation etc
@EpochAIResearch What’s exciting is seeing AI evolve beyond answering questions toward handling complex, multi-step workflows more effectively.
@EpochAIResearch time to spend the extra $$ on how to scale down to scale up