Snapshot · The Prof G Pod with Scott Galloway
The US is projected to spend at least $750 billion on data center infrastructure in 2026, roughly twice China's stated target of approximately $375 billion by 2030.
Where this was said
At 1:09:17 · chapter starts 1:08:10
Alice Han challenges the common narrative that the US is comfortably ahead of China on AI infrastructure investment. US data center CapEx is projected at $750 billion in 2026 alone, while China's announced target is roughly half that by 2030 — numbers that seem to show a clear US lead. But Alice argues this comparison is deeply misleading because infrastructure and energy buildout costs per gigawatt are dramatically lower in China, meaning the actual capacity gap is far smaller than headline spending figures imply. Ed Elson extends the point to the model layer, noting that Deepseek's AI models are reportedly 96% cheaper than OpenAI equivalents — and that as US enterprises face spending caps on AI, cheaper Chinese alternatives become increasingly attractive. Alice delivers a striking anecdote: major US tech companies she encountered at a Hollywood conference are actively using the Chinese open-source model Qwen because it's cheaper, faster, and easier to fine-tune than OpenAI or Claude. The great AI decoupling, it turns out, is not happening at the enterprise level.
The US-China AI decoupling narrative has a problem: it isn't happening at the enterprise level. Alice Han reports that major US tech companies she encountered are actively using Chinese open-source models like Qwen because they're dramatically cheaper than OpenAI or Claude. Deepseek's models are reportedly 96% cheaper than OpenAI's equivalent.
Deepseek's AI models are reportedly 96% cheaper than comparable OpenAI models, driving growing interest in Chinese AI alternatives among cost-conscious enterprises.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
PropGPT averaged 20 downloads per day right after launching on the App Store through influencer marketing.
Eyal and Yali shut down all marketing and spent 4 months completely rebuilding PropGPT from scratch.
PropGPT has accumulated over 40,000 total downloads since launch.
PropGPT's large language model (AI) operating costs are just $20 per month, and the cost is continually falling.
Ad-based monetization works well for game apps where users spend extended time in-session, as seen with Grid and Wordle.
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