The AI hyperscalers who develop frontier “closed source” AI are spending hundreds of billions of dollars on massive data centers. But will this astronomical investment pay off in end-user profits? (Not counting the circular AI-ecosystem profits which support the high stock valuations of Nvidia and others.)

Or will end-users turn away from expensive frontier AI to buy much cheaper “distilled AI” - smaller dedicated software models - from “open source” AI vendors?

nytimes.com - Open source AI anthropic openai


Corporate America Is Getting Hooked on Open-Source A.I.

Companies like AT&T are increasingly using cheap, freely available artificial intelligence models over expensive ones from Anthropic and OpenAI.
By Eli Tan, The New York Times,
Sept. 4, 2026

...

Open-source artificial intelligence has become all the rage in corporate America. Like AT&T, companies such as Airbnb and Deloitte are also turning to open A.I. models that are easy to customize and cheaper to use. Last month, open models accounted for 58 percent of A.I. use, up from 10 percent a year ago, according to U.S. user data from OpenRouter, a platform that lets people choose different A.I. models to complete tasks...

Open models come in two flavors. One is an open-source model, which makes its underlying code public. The other is an open-weights model, which makes its “weights” — the numerical calculations that determine how the model reasons — public.

Many of the most popular open A.I. models are made by Chinese companies like Moonshot AI, DeepSeek and Alibaba. Rather than spending millions in fees to use a closed model, developers can download one of the Chinese systems and build their products on top of it, paying mainly for servers. OpenAI and Anthropic charge for subscriptions and other fees, depending on the job.

Some Chinese open models are now 80 percent to 90 percent as powerful as those from OpenAI and Anthropic, while costing as little as 20 percent of the price...

Many open models can now be powered by a phone or laptop...Leading closed models are getting more complicated and requiring more computing power.

Most U.S. companies still use a combination of open and closed models. Closed models remain the best for heavy duty tasks like coding and image and video generation, while open models often excel at simple, specialized tasks... [end quote]

If I was a corporate CFO, I would provide cheap, distilled AI to my sales force and customer service, which would probably be 95% of the users. They could run it on their laptops or even cell phones. When I was in technical sales (1981-1988) there was no such thing as a cell phone. Sales reps had to find a pay phone to call the office. Now, I could picture sales reps with cell phones equipped with distilled AI to provide them with customized recommendations and pricing right in a customer’s office. Increased productivity, actually cheaper than maintaining an office staff large enough to help the outside sales force.

This strikes at the root of the valuation of AI hyperscalers who are going into debt to build huge frontier data centers which may only be used by the small fraction of end-users (such as research).

Which strikes at the root of the S&P500 bubble that has been inflated by AI mania.

Wendy