🦔Nvidia's VP of applied deep learning told Axios that for his team, the cost of compute is far beyond the cost of employees. An MIT study found AI automation is economically viable in only 23% of roles where vision is a primary part of the work, meaning human labor remains cheaper in the vast majority of cases. Uber's CTO said he's back to the drawing board because his 2026 AI budget is already blown. AI software fees have increased 20% to 37% over the past year. Despite all of this, Big Tech has announced $740 billion in capital expenditures for AI this year, a 69% increase from 2025, while laying off more than 92,000 tech workers. My Take The core contradiction of the AI moment is now being stated openly by people inside the industry. Companies are cutting human workers who are cheaper than the AI replacing them, to fund AI infrastructure that isn't generating measurable productivity returns, financed by investors who are also funding the AI companies selling the tokens at prices those companies cannot sustain without continued subsidy. My honest read is that the workforce decisions being made right now are irreversible on a timeline the technology cannot meet. The entry-level pipeline being dismantled today will take a decade to rebuild. The engineers being cut to fund token budgets that exceed their salaries are the same people who would catch the failures when the AI gets it wrong. Companies are making permanent structural changes based on a cost structure that doesn't exist yet and a productivity case that by their own executives' admission hasn't materialized. At some point the distance between the bet and the reality has to close, and the people who absorbed the cost of being wrong won't be the ones who made the decision. Hedgie🤗