AI 资本开支陷阱：为何超大规模云服务商支出激增却反遭市场惩罚

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Not for long time. Just one hint of capex reduction and boom...

Yes it's like a moon race in cold war times which no one wanted to loose. No one wants to show themselves weak and building infrastructure recklessly, time will tell if they can generate solid revenue model out of it.

But the revenue from all this infrastructure is "sometime later" — and the market doesn't know how to price "sometime later"

I disagree. the market doesn't know how to price "yo we spent billions on something that.. can kind of code right now.. in the hands of a coder. And if you give us way more money, we hope it can do other things eventually but right now it's just great at generating text. "

Ever tried to extract and organize data using an LLM or an agent? build a financial model? Seems quite simple, but I do this for a living now. It's a fucking nightmare. I think it will eventually get solved. There's very little that a trillion dollars can't fix.

AI monetization might actually never happen. That's what's difficult to price. But the hyperscalers have a long leash. They've proven great capabilities/profitability in the past, are made up of a lot of smart people, so they get the benefit of the doubt that they're not just burning money in a furnace right now.

Each mega company represents a sector of the digital world. MSFT is corporate, META is socials, AMAZON is retail, and Google is a combination of search, mobile, video platform, and hardware.

I think given Google's diversification, it's the most likely to succeed, it's vertically integrated with access to unlimited data, second is amazon due to its logistics network, as for MSFT and META I don't know. They've had a history of not doing well outside their core business.

That's the risk that's been priced in right now. Maybe someone with expert knowledge of each industry from corporations to socials can give more insight?

Good work claude

Why post AI?

Great write-up. Of the four, Meta is the most compelling to me.

First, it’s the cheapest on an objective basis. You’re paying a below-market multiple for one of the fastest-growing and highest-margin advertising businesses in the world.

Second, I don’t see Meta’s core business being nearly as vulnerable to AI disruption as I do the cloud providers. AI may change how people consume content, but advertisers will still pay to reach attention. Search and cloud computing, on the other hand, face a greater risk of being reshaped or partially disintermediated by AI-native architectures.

The most interesting distinction, though, is capital allocation. Microsoft, Google, and AWS have cloud platforms they need to defend. Even if returns on AI infrastructure disappoint, they may have little choice but to keep investing to protect market share.

Meta doesn’t have that same obligation. If Zuckerberg concludes the incremental ROI on AI infrastructure isn’t there, he can slow capex, take the write-down, and investors are still left owning an exceptional advertising business. In other words, with Meta you’re buying a proven cash-generating business with an AI call option, rather than a company whose core platform increasingly depends on winning the AI infrastructure race.

Ultimately, you’re betting that Zuckerberg remains rational about capital allocation. Given how quickly he pivoted during the “Year of Efficiency” after the market rejected the metaverse spending, I think he’s earned more credibility on that front than many people give him credit for.

OK bot

You'd be surprised. I know old people who are always sending me videos from Facebook shilling supplements and other stuff and asking me what I think. I keep telling them not to take health advice from people who are clearly being paid to shill stuff but they don't listen.

I guess young people are just as bad with Tiktok but there's more chance of them changing and adopting AI, whilst the elderly users of Facebook die off.

Thanks for your perspective that's interesting and cool. I was previously a financial analyst and am currently working at an AI company attempting to automate financial workflows. It's kind of a nightmare. But I'm glad that some fields are killing it.

it's about the broader sector flows. When one area catches a bid, it's usually not random

Ya fair. It's not random. It's mechanical. MU has made my year. I picked this up in Jan after running local models and realizing that memory was a binding constraint in inference. As we can see, the market is digesting these hardware costs in a rational way: memory producers go up, memory utilizers (eg apple) go down. One company's revenue is another company's cost.

On a much larger scale, basically the same thing happening with hyperscalers vs data center (AMD, VRT, NVDA etc). And this is rational as well. It would be strange as hell and very concerning, if we saw google et al being rewarded for spending capital with no clear return prospect/timeline.

Re timeframe: Frankly, we don't know when the hyperscalers will get rewarded, but at the very least, one of them will have to create something that has visibility to profit.

On that front though META seems to have the strongest track record of converting data center spend into profit. They've done it in the past, using better models/more compute to increase time spent watching reels, tailor/target ads, which translates to revenue in a shorter time frame.

On companies promising that their models will soon be able to do most office work.. that's a long ways away. I actually used to be an investment analyst and now work with an AI company trying to solve this problem. But I'll give you the truth: the latest and greatest model had a 38.4% workflow pass rate across 172 real and basic finance/accounting workflows. Frankly, if it was 99% that would still be too atrocious to trust with real work.

But as TechTuna mentioned, a field like design, where there are fewer opportunities to label something objectively incorrect, might flourish.