Personally, I'm not a fan of it. But the thesis is real, and it might have delivered on its promise if the world wasn't actually full of scumbags and scammers (each one accidentally contributing to making Big Banks look like the lesser of the evils).

The datacenter deals came after. But now, the man who promised the world an AI system that defends free speech and is “pro-human”, is instead selling to his competitors and lowering the daily app usage limits of his own Grok by an order of magnitude (really).

If you’re dealing with the world’s richest man, you can predict that money will come before other concerns despite other rhetoric. Interesting strategy though!

Edit: To be fair, they did decide that hardware was "the bottleneck" according to an interview I saw last year. But I firmly believe they underestimated the software problem (and their app was/is riddled with them).

> 1.Methodology: The study was carried out in collaboration with IPSOS among 19,000 adults aged 18 to 75 across 18 countries, between 12 January and 16 February 2026.

Survey methods: https://www.ipsos.com/en-uk/survey-methods-ipsos-uk

If the Ipsos stock price is any indicator of surveys still being viable in 2026, then I can only wonder what actually motivates comments like this.

That being said, if the actual study cannot be reproduced, it's not science. So I'm looking forward to seeing the method and not the conclusion scrutinized. There's a lot of cognitive dissonance right now, especially in the US, when it comes to perceptions about mental health.

Sec. 3

Unbiased AI Principles.

It is the policy of the United States to promote the innovation and use of trustworthy AI. To advance that policy, agency heads shall, consistent with applicable law and in consideration

of guidance issued pursuant to section 4 of this order, procure only those LLMs developed in accordance with the following two principles (Unbiased AI Principles):

(a) Truth-seeking. LLMs shall be truthful in responding to user prompts seeking factual information or analysis. LLMs shall prioritize historical accuracy, scientific inquiry, and objectivity, and shall acknowledge uncertainty where reliable information is incomplete or contradictory.

(b) Ideological Neutrality. LLMs shall be neutral, nonpartisan tools that do not manipulate responses in favor of ideological dogmas such as DEI. Developers shall not intentionally encode partisan or ideological judgments into an LLM's outputs unless those judgments are prompted by or otherwise readily accessible to the end user.

Then theres reference checks, less formal but generally still follow some kind of rigor or process and you generally know who they’re going to talk to.

Then there’s the third type of investigation, where they actually don’t tell you they’re doing it, may or may not admit to doing it, and you have no way of knowing whether you were singled out for some reason, assuming you are able to find out it happened in the first place.

And good luck searching for any recourse if ethics or even laws (such as HIPAA) are ignored in that situation, even if it’s for example a b2c healthcare company that is expected to set an example for health privacy standards, rather than calling everyone you knew to probe their memories of how healthy you appeared to be at the time, then using that information to evaluate your performance with different criteria than other employees.

Sure, it’s not a typical scenario, but if it happens to you, you’ll probably never be able to scoff at a comment like this again. You might never get over it.