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In the U.S. midterm elections, the Democratic Party achieved a landslide victory, and newly elected governors in multiple states immediately imposed tough conditions on data centers, announcing a full suspension of new construction permits until new regulations are introduced. This policy shift directly triggered the market, with tech stocks such as Nvidia, Tesla, AMD, and Micron experiencing the largest single-day market value evaporation in history after the election, involving nearly $4 trillion. Chamath Palihapitiya, co-host of the well-known All-In Podcast and a Silicon Valley investor, revealed in the November 8 episode that the real "nuclear-level" variable lies in the computing power supply contract between SpaceX and Anthropic—both parties hold a "90-day mutual exit clause." If market computing power supply suddenly tightens due to state permit freezes, SpaceX could theoretically terminate the contract and reprice at 2 to 3 times the spot price, completely rewriting the power dynamics of the entire AI industry. (Screenshot from the All-In Podcast) Hyperscale cloud providers, holding large existing computing power, remain in the "landlord" position, while new cloud providers (Neoclouds) and frontier model companies that heavily rely on external leasing face a life-or-death situation. Meanwhile, All-In Podcast co-hosts Jason Calacanis, David Sacks, and David Friedberg also warned on the show that if states continue to set approval barriers, gigawatt-scale data center projects worth over $50 billion will be forced to relocate to Canada, Mexico, Malaysia, or even the Middle East. The U.S. will fall from being a "global computing power exporter" to an expensive "Token importer," with strategic impacts on technological competitiveness and employment that cannot be ignored. Permit Freeze: Grassroots Backlash Against the "AI Oligarchs" After the election results were announced, newly elected Texas Governor Gina Ino Hosa publicly stated that all new data center permits would be suspended until special legislation is enacted. According to discussions by All-In Podcast co-hosts, candidates in several newly elected states hold similar positions. This public sentiment did not arise out of nowhere. Chamath cited a widely circulated video on platform X—SpaceX’s team held a briefing in Cochise County, Arizona, for its 6GW data center project, where two SpaceX employees, Riley and Katie, promised on the spot that the project would reduce local electricity costs, consume no water resources, cut property taxes by 20%, and provide funds to repay county bonds. However, the audience responded with continuous noise and confrontation. Chamath pointed out that this sentiment is not based on rational judgment of facts but is a totemic projection of the "economic divide." Community residents strongly resent that tech giants enjoy generous tax breaks from local governments while driving up local electricity prices and water consumption. David Sacks bluntly stated that residents’ core logic is: "AI oligarchs get rich with tax breaks, while we pay higher electricity bills for them." David Sacks further noted that the political momentum for permit freezes is almost rigid: "In the last election, both Democrats and Republicans targeted politicians who approved data centers. Anyone with political ambitions has no reason to approve any projects in the next four years." His baseline judgment is that projects already fully permitted are likely to be completed by 2027, but new projects without approval will face great uncertainty, and by 2028, the entire project pipeline may be basically closed or significantly shrunk. "Landlords" and "Tenants": The Life-or-Death Divide in Computing Power Chamath clearly divides current computing power market participants into two distinct camps and bluntly states that their fates differ greatly under the new situation. Hyperscalers—including Google, Meta, Microsoft, Amazon, and SpaceX—build their own power plants and hold large existing computing power, truly acting as "landlords." The tightening of new data center permits has limited impact on them but brings important strategic opportunities: by directing incremental computing power to their own products, they can effectively suppress the growth speed of external competitors. As Chamath said, Google's recent acquisition of Crusoe data centers directly reflects this logic—"They kicked out the tenants and took the entire asset for themselves." In contrast, emerging cloud service providers (Neoclouds) and frontier model companies (such as Anthropic and OpenAI) heavily rely on externally leased computing power and are the true "tenant class." Once new supply is locked down by state regulations, spot GPU prices will soar, forcing these companies either to accept much higher quotes or gradually fall behind in the fierce model iteration competition due to insufficient computing power. Notably, Anthropic and OpenAI are currently in a rapid model iteration cycle of 60 to 90 days. Once computing power supply tightens, this pace will be forcibly slowed, giving models under hyperscalers like Google Gemini a time window to catch up. SpaceX’s "90-Day Nuclear Button": A Contract That Decides the AI Landscape Among all variables, Chamath believes the most decisive is a little-known contract clause. According to Chamath, the computing power supply agreement between SpaceX and Anthropic contains a "mutual 90-day exit clause"—either party can notify the other 90 days in advance to terminate the contract. This clause seems like a standard commercial arrangement during stable market periods but becomes a "nuclear bomb" ready to detonate when computing power supply suddenly tightens. Chamath’s reasoning is as follows: If state permit freezes cause a sharp reduction in available market computing power, spot computing power prices will skyrocket. SpaceX will have strong economic incentives to terminate existing contracts and reprice at spot market prices—likely 2 to 3 times the original contract price. Anthropic will have no choice but to accept this price or face a life-or-death crisis of computing power supply interruption. The chain reaction of this move goes far beyond that. Chamath points out it will force all hyperscalers to reconsider their computing power allocation strategies—whether to continue renting to external customers at current prices or keep it all for their own models. At the same time, it will force Neoclouds to use all financing reserves to buy up all available computing power at high prices to avoid being completely squeezed out of the market. "I think all game theory is condensed in this deal. If Elon decides to tear up this contract, the consequence will be a complete reshuffle of the AI industry landscape," Chamath concluded. Computing Power Going Overseas: The U.S. Faces Strategic Risk of Changing from "Exporter" to "Importer" On the show, Jason Calacanis and David Sacks both warned about the prospect of data center relocation. The core logic is: data centers do not have to be located within the U.S. Gigawatt-scale, $50 billion-level hyperscale data centers can be built in Canada, Mexico, Malaysia, Singapore, and even the Middle East after the war ends. Google has already deployed large data centers in Malaysia. With existing submarine cables, CDN technology, and the Starlink network, cross-border computing power delivery latency and efficiency are no longer major obstacles. David Sacks clearly stated that if the U.S. does not build these data centers, it will pay a high price for importing "Tokens." Jason Calacanis added a more direct domestic cost: hundreds of thousands of data center construction jobs paying $300,000 to $400,000 annually will be lost, and tax revenues originally belonging to U.S. local governments will flow to places like Malaysia. "These governors will learn a very harsh lesson in globalization," said Jason Calacanis. David Friedberg proposed an even more radical policy risk—some far-left political figures are already discussing not only restricting data center construction but also limiting AI model development, deployment, and even usage itself. He believes the deep logic behind this is the fundamental struggle between state power and AI technology control: whoever controls the strongest AI capabilities holds absolute advantage over citizens and markets.