Snapshot · The Prof G Pod with Scott Galloway
Tens of billions of dollars worth of data centers were blocked in the US in 2025 due to political pushback, with 19 states considering restrictions on data center construction.
Where this was said
At 1:06:15 · chapter starts 1:06:00
Ed Elson delivers the episode's sharpest analytical observation: proactive AI regulation isn't just good ethics, it may be good strategy. If workers trust the government to protect them, they'll embrace the technology. A KPMG and University of Melbourne survey quantifies the gap starkly: 90% of Chinese respondents are excited about AI versus less than 40% of Americans. Ed connects this to the data center opposition story — tens of billions blocked in 2025, 19 states considering restrictions — arguing that America's regulatory vacuum is generating a public backlash that is materially slowing infrastructure buildout. China's approach, by contrast, creates public buy-in. He acknowledges this doesn't require glorifying the CCP, but argues that the White House's libertarian reflex is creating an own-goal that could hand China a structural advantage in the AI buildout over the long term.
Tens of billions in US data center projects were blocked in 2025 due to public opposition, with 19 states considering construction restrictions or outright bans. Ed Elson argues this is a direct result of Washington's failure to regulate AI proactively — and it may end up handing China a structural advantage.
A KPMG/University of Melbourne survey found nearly 90% of Chinese respondents were excited about AI, compared to under 40% of Americans.
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.
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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