Are Investors Losing Faith in AI?

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Are People Losing Faith in AI?

Over the past few weeks, fear has taken hold, with most indices worldwide declining. Naturally, the blame has been put on AI. And the truth is, they have a very good reason for it.

But why?

Today, we are going to reveal what is going on and why the nervousness of American investors is highly contagious to global indices (which are much more exposed to AI than you may realize), revealing some very concerning metrics on particular large public companies where investors are literally betting they’ll default in the near future.

At the end, we’ll cover a series of recommendations for investors to gauge better how real AI's alleged progress is; a way to know for certain if incumbents are full of shit or not.

Let’s dive in.

The US Concerns

There are several reasons why US investors are growing nervous. The primary reason is debt, but general suspicions about OpenAI’s buildout and the perception that China has caught up aren’t particularly helping the optimistic case for US AI stocks.

Let’s cover the latter two first, because there’s much more to be said on the first one.

China, China, China

China is becoming a real threat to US AI supremacy. Besides the surprising growing allergy toward American chips (more on that later), they are “waging war” on American companies in two ways: by releasing research on the hardware and software efficiency frontier.

In other words, they are sending two “horrific” thoughts to US investors:

Is the US overcommitting to the compute buildout?

Is the US in the lead at all?

This is primarily based on two numbers: 82% and $4.6 million.

The first one refers to Alibaba’s Aegaeon token-level scheduler, which we recently covered, that has enabled Alibaba to reduce GPU inference usage by 82% compared to previously considered frontier inference strategies.

Put simply, for the same inference workload to be served, the system managed to service that load with 213 GPUs instead of the previous number of 1,192.

This immediately raises the question: how many of these efficiency breakthroughs are US Hyperscalers simply not factoring into their spending projections?

The fears are understandable. It’s clear that efficiency is taking a backseat in US buildouts and research, and money is being spent without regard for efficiency breakthroughs. Instead, companies are literally spending every single dollar they can on this.

It’s less of “this is what I believe would be necessary“ and more of “let’s build as much as we can, and we’ll later see how that supply is met, if ever.“

This is a very risky bet for such an “unprofessional” way of spending money, as:

These buildouts are based on fast-depreciating assets

Require equally impressive energy buildouts

They are notoriously unpopular in the US, with a greater share of Americans being more worried than excited about the technology, while also incurring higher energy prices for homes.

And the business is just objectively worse than their main businesses (much lower…

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