
August 7, 2026
The danger of measuring Artificial Intelligence incorrectly 🤖
The wrong metric can teach an AI to do its job worse.

The wrong metric can teach an AI to do its job worse.

The wrong metric can teach AI to do its job worse.

Can AI learn from its mistakes? Trajectory is betting on turning every interaction into better specialized models and more effective enterprise agents.

An AI agent doesn't become useful just because it has access to a powerful model. It becomes useful when its performance is observed in the real world and its changes are validated before affecting more people. So the future won't necessarily belong to the AI that speaks the most beautifully, but to the one that knows when it didn't solve

Today we're talking about Anthropic, the company behind Claude. According to Reuters, the company has been exploring the possibility of designing its own artificial intelligence chips. The verb matters: exploring. That's not the same as announcing a finished processor, a factory, or a launch date. Exactly

Anthropic is considering designing its own chips for Claude to reduce costs, dependence on Nvidia, and risks in the race for artificial intelligence.

Artificial intelligence investing is entering a new phase: Wall Street no longer rewards just any spending on chips, data centers, and computing capacity.

What if artificial intelligence’s next major limitation isn’t in the chips, but in the power outlet?

OpenAI, visas, and tech hiring: the $3.2 million settlement that reopens the debate over foreign talent, PERM, and fair competition.

The risk isn’t that it’s all hype. The risk is paying today as if every dollar invested were going to produce extraordinary returns quickly and for all participants. That last word is decisive: everyone. AI can generate enormous social and economic value, but concentrate less profit than the market expects in a handful of companies. If models become cheaper, more capable, and easier to integrate, users could keep much of the benefit in the form of lower costs, better products, and greater productivity. That would be fantastic for the economy, but it doesn’t guarantee extraordinary margins for every model, chip, or cloud provider. We may see a paradox. Artificial intelligence can be more useful than many skeptics admit and, even so, certain investments may prove financially disappointing.

And according to the Department of Justice, the problem was not just technical. It was that OpenAI and Statsig allegedly created practical obstacles. Among them: not posting certain PERM job openings on the regular employment portal, requiring paper applications when they accepted electronic applications for other positions, and announcing some

What if a security ban made AI more expensive? The FCC is reportedly preparing a restriction to block the import of new Chinese optical transceivers: components that connect servers with light inside data centers.