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Washington's equation to settle the tech race puts priority on beating China over calls for a slowdown in Silicon Valley

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Washington's equation to settle the tech race puts priority on beating China over calls for a slowdown in Silicon Valley

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The US administration settled its stance on the escalating debate over AI brakes with a clear declaration that places geopolitical superiority above calls for technical caution, after President Donald Trump downplayed the usefulness of imposing governmental restrictions that would slow development. The stance, announced by Trump to journalists in Ireland on September 13, 2026, after following the golf tournament at his resort in Donegal, was based on a direct equation: fear of losing leadership to China, confirming that whoever wins the AI race will secure global primacy.

The presidential response effectively stalled the efforts of leaders of major advanced-model firms, as Dario Amodei, CEO of "Anthropic", had published an article urging the AI sector to slow the pace of capability improvements to allow sufficient time to build safety barriers. Amodei's call received explicit endorsement from Sam Altman, CEO of "OpenAI", who said that the idea of a pause had been the focus of his company's internal discussions in recent weeks, and Elon Musk also voiced public support for Amodei's proposal.

The race imposes a dilemma on legislators, while rising computing costs and concerns about systems getting out of control move to the forefront of the electoral battle.These tussles follow the resignation of Jacob Coxon, a former researcher at Anthropic and OpenAI, in protest against the possibility that models could exceed human control, a move that sparked broad reverberations in Washington and prompted lawmakers from both parties, such as Democrat Josh Gottheimer and Republican Mike Lucker, to introduce a bipartisan House bill requiring human oversight of AI deployment.

Although Trump acknowledged a theoretical need for some regulatory controls, he described those calling for a pause as a negative force that raises concerns about things that will not happen. This stance coincided with criticism from David Sacks, former White House AI adviser and co-chair of the Presidential Council of Advisors on Science and Technology, who confronted Silicon Valley leaders by insisting that the industry determines the pace of development and can slow itself, considering a regulatory framework as an alternative to action to be extortion of the political system and the public.

The confrontation moved beyond software into an infrastructure battle, as computing farms and data centers became a central issue in the U.S. election season, amid growing protests in several cities over scarce water consumption and rising electricity bills. Nevertheless, Trump maintained his absolute support for building these massive facilities to ensure the needed computing power, disregarding their declining local popularity in favor of external competitive superiority.

This U.S. shift carries direct strategic implications for businesses and tech leaders in the Gulf, Egypt, and the Arab Levant. Washington's exclusion of binding legal brakes means the rollout pace of advanced models and autonomous agents will accelerate rather than pause, removing the regional bet on ready-made Western regulations sufficient to manage risks. Banking institutions and government agencies that integrate these models locally will find themselves required to build internal governance layers and bespoke verification filters to protect their data and operations, without waiting for U.S. federal frameworks to restrict producers.

The absence of official brakes shifts the responsibility for discipline from model developers to field engineering and implementation teams.Accordingly, purchase and hiring priorities for regional tech teams are changing, so that focus is no longer limited to the cost-per-token race, but to verification engineering skills and building continuous human-in-the-loop systems within software to ensure autonomous agents do not drift in sensitive production environments.

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