While OpenAI is missing revenue targets and struggling to justify its spending, a former Google DeepMind researcher just raised $1.1 billion in seed funding to chase "superintelligence."

That's not a typo. A seed round. Over a billion dollars. For a company that doesn't have a product yet.

According to CNBC, the funding round was led by major names including Nvidia and Google themselves. The company is pursuing artificial general intelligence, which is Silicon Valley speak for "we're building something that doesn't exist yet and may never exist, but it sounds impressive."

Here's the thing that should make you pause: one AI company just admitted it can't hit its revenue targets despite having the most popular AI product on the planet. Another AI company just raised a billion dollars without having any revenue at all.

That's not a healthy market. That's a speculative mania.

The AGI Winner-Take-All Myth

The AI investment thesis right now is built on the assumption that whoever gets to AGI first wins everything. Maybe that's true. But it's also possible that AI turns out to be more like cloud computing: incredibly valuable, but commoditized enough that no single company captures all the gains.

Think about it: Amazon Web Services pioneered cloud computing and still leads the market, but they didn't capture 100% of the value. Microsoft Azure and Google Cloud are massive businesses too. The cloud revolution created trillions in value, but it got distributed across multiple winners.

Why would AI be different? Right now, we have OpenAI, Anthropic, Google, Meta, and now a parade of startups all building frontier models. If they all succeed in creating useful AI, the value gets divided. If they all fail to monetize despite massive spending, investors lose.

Neither scenario justifies writing billion-dollar checks to companies with zero revenue.

When the Music Stops

Now, to be fair, the researcher probably has legitimate credentials, and there's real science happening in AI labs. Superintelligence might happen someday. But when investors are writing billion-dollar checks for "someday maybe," while established players are burning cash faster than they can monetize, that's usually a sign we're near a top.

I saw this movie in the late 1990s with dot-com companies. I saw it again in 2021 with SPACs and meme stocks. The pattern is always the same: capital flows to the most speculative, least proven ideas at exactly the moment when the smart money is quietly rotating toward profitability.

For everyday investors, the lesson here is simple: when you see this kind of frothy capital deployment, it's time to get pickier about which AI companies you're betting on. The ones with actual revenue, actual customers, and actual paths to profitability are going to look a lot better when the music stops than the ones burning through billions chasing science fiction.

If they can't explain how they'll make money, they're probably hiding the fact that they don't know.