ARC Raiders hit like absolute crack for the first 3 months.
Then followed it up with some of the most mediocre post launch support I’ve ever seen.
They had the gaming world by the balls and just…didn’t do anything with it.
People called $TAO dead in April because one founder sold.
Sam Altman raised $40B this year. OpenAI is chasing a $1T valuation. They have one product and one point of failure.
TAO has 128 subnets, each one a separate bet, each one able to survive independently. Intel co-authored a paper with one of them. PwC signed a distribution deal with another. Grayscale filed for a spot ETF.
$3B market cap against a $1T addressable AI economy is not a valuation. It is a pricing error.
The people who recognised this in May 2026 will not need to explain themselves later.
Like, if you see what I see here.
Politicians are paid actors.
Government is written theater.
You have no representation and no democracy.
The sooner you realize this, the sooner we can actually move forward.
🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months. American AI software prices have jumped 20% to 37%, and GitHub (owned by Microsoft) is dropping flat-rate plans for usage-based billing across its products.
My Take
The AI subsidy era is ending in real time. The same company that put $13 billion into OpenAI and built the Azure infrastructure powering most of Anthropic's compute just looked at the bill from a competitor's coding tool and decided it was not worth paying. That is not a productivity failure on Anthropic's end. Token-based pricing is forcing every enterprise customer to confront the actual cost of running these models at scale, and the number turns out to be far higher than the flat-rate experiments suggested.
This ties directly to my Gemini Flash post yesterday. Anthropic, OpenAI, and Google all raised effective prices in the last six months. Enterprises that built workflows assuming AI costs would keep falling are now watching annual budgets evaporate in months. Two outcomes look likely from here. Either enterprises scale back AI usage to fit budgets, which slows the revenue ramp the labs need to justify their valuations ahead of IPOs, or the labs cut prices and absorb the losses, which makes the unit economics worse at exactly the wrong moment. Both paths land in the same place, the numbers stop working, and somebody has to take the writedown.
Hedgie🤗
please do not fall for this hantavirus nonsense before those pedo clowns apologize for lying and force feeding you experimental vaccine mandates.
#turnyourbrainson