#现象/趋势

I am shocked, absolutely shocked, that Anthropic ARR has likely gone vertical in October after they cut token prices. Except the exact same thing happened for the entire AI market, which is why GPU rental prices have surged while token prices declined. $100b plus in year-end ARR looks possible again.

Gartner predicts cost pressure will force more than 80% of neocloud providers to cease independent operations by 2030. Hyperscalers face less risk because their large, diversified revenue could plausibly sustain AI investments for years. Gartner also forecasts AI-optimized IaaS spending will grow from $66B in 2027 to $174B in 2030. That growth is too low for most AI compute providers to recover their investments before current AI chips are replaced. AI data center owners would need $8.5T in cumulative revenue through 2030 to cover announced capex, financing costs and a 12% return on invested capital, yet Gartner forecasts attributable AI revenue of no more than $3.6T. On the current trajectory, more than $4T in asset value could be exposed to write-down risk through 2032, and Gartner does not expect the 12% return to be reached before the end of 2032.

@Yuchenj_UW I think we’re going to see a lot of stranded compute in partially complete data centers

It’s a bloodbath in Bay Area. Thousands of layoffs, more to come. Met a founder this morning who mentioned his AI tech is laying off 2000 call center workers. Not sure if society is ready for such upheaval. Gut wrenching

AI-related employment is surging: AI-linked roles have accounted for more than +750,000 new jobs created in the US since 2023, according to LinkedIn estimates. This surge has been led by data annotators, with +282,000 new positions created, followed by data center jobs at +117,000, and AI engineers at +105,000. As a result, these 3 categories have accounted for +504,000 new jobs. AI-related positions also offer significantly higher pay, with a median salary of ~$180,000 on LinkedIn, compared to $80,000 across all jobs. This comes as the rapid expansion of AI infrastructure, particularly the buildout of data centers, is driving stronger demand for labor. The AI boom is reshaping the US job market.

BIS (Bank for International Settlements) just published a report on circular financing among AI companies. > Over half the money flowing into AI companies comes from other AI companies: between 2021 and 2025, peers supplied 55.2% of AI firms' incoming investment value, while AI investors sent 28.7% of their own deal value to AI targets. > Circular deals are rare but big: only 16.1% of AI-to-AI deals involved firms that also buy from or sell to each other, yet they held 46.4% of the money. That figure is partly inflated, because an entire funding round counts as circular if just 1 of its AI investors also trades with the company. > Chip, cloud and infrastructure suppliers are the investor in 73% of circular ties, and in 64% of all such ties the investor also sells to the firm it funds. Data tool and model makers rarely invest this way, since their products are more interchangeable. > AI is unusually suited to these deals: suppliers can track customers' compute use, chips and data centres are custom-built, few firms make critical tools such as photolithography machines, and capital needs are too big for normal lenders. In AI compute and cloud, 15.2% of supplier-customer ties also involve financing, versus just 3.3% with equity stakes in a broad 2006 US study. > Some AI sales are paid for by the sellers themselves, because money a supplier invests in a customer partly returns as the supplier's revenue. Lucent and Nortel did this in the late 1990s, then lost money on the loans and lost the sales when the telecom firms they funded stalled. > A supplier that invests in its customer can lose twice: if the customer struggles, both the stake and the future orders shrink. Because these deals involve a few giant suppliers, 1 shock could spread through sales and finance at the same time. > Much of this risk is hidden: many AI firms are private, deals mix cash with long-term purchase promises, and pledges to cover any fall in the value of chips and data centre equipment stay off the books until a downturn forces payment. Because these firms span many sectors and countries, no single regulator sees the full picture, and the research names no companies or overall dollar total.

@minchoi Colossus 1 is 150k H100, 50k H200 and 30k GB200. Colossus 2 is 110k GB200 and 440k GB300. Another 220k GB300 will be fully operational next week and another 220k in November. If we get lucky, yet another 220k GB300 by late December.