In a move evoking the high-stakes urgency of World War II's atomic race, President Donald Trump has signed an executive order launching the Genesis Mission, a sweeping federal initiative to propel American artificial intelligence into the stratosphere of scientific and national security dominance.
Announced on a crisp Monday afternoon in late 2025, the order positions the U.S. government as the ultimate venture capitalist for AI, channeling vast federal datasets, computational firepower, and public-private synergies to tackle challenges from biotechnology to nuclear fusion. Dubbed "comparable in urgency and ambition to the Manhattan Project," the Genesis Mission isn't just policy theater—it's a recognition that AI's promise demands resources beyond what profit-driven enterprises can sustainably muster alone.
Yet, as this landmark effort unfolds, it underscores a harsh reality: AI's business model remains a black hole for private capital, riddled with astronomical costs, protracted timelines, and diffuse returns. To secure America's edge, the Genesis Mission must evolve into a blueprint for strategic bailouts—government infusions that rescue and redirect an industry teetering on the brink of unprofitability. So why risk public funds?
At its core, the executive order establishes the Genesis Mission as a national crusade to "supercharge American AI research, development, and scientific applications."
Tasked with execution is Michael Kratsios, Trump's Assistant for Science and Technology and director of the Office of Science and Technology Policy, who will orchestrate the integration of siloed agency data and infrastructure. The Secretary of Energy, Chris Wright, faces a tight 90-day deadline to catalog available systems and datasets, drawing in resources from industry heavyweights like AMD, Hewlett Packard Enterprise (HPE), and Nvidia. These partnerships aren't mere cameos; they're foundational, building on recent Department of Energy announcements for next-generation supercomputers at Oak Ridge National Laboratory, equipped with Nvidia's high-powered chips to fuel AI model training.
The mission's ambitions are audacious. It aims to harness the "world's largest collection" of federal scientific datasets—decades of taxpayer-funded treasures in fields like advanced manufacturing, robotics, biotech, and energy—to birth "scientific foundation models" and AI agents capable of hypothesizing, automating workflows, and accelerating breakthroughs.
Within 270 days, the initiative pledges real-world applications, transforming abstract algorithms into tools for national priorities: bolstering energy dominance, fortifying workforce productivity, and amplifying returns on public R&D investments. This builds directly on the National Artificial Intelligence Research Resource (NAIRR), a 2020 pilot coalition of federal agencies (Defense, NASA, NIH) and tech titans (OpenAI, Google, Palantir), now supercharged under Trump's July 2025 AI Action Plan.
Experts hail the move as a "strong signal" to global rivals. Keegan McBride, a senior policy advisor at the Tony Blair Institute, notes that "AI has the potential to transform the entire scientific, research, and discovery pipeline."
Lynne Parker, former deputy chief technology officer under Biden and now an AI policy veteran, emphasizes the public-interest imperative: "Government support for AI research builds the foundation for new breakthroughs and helps keep innovation aligned with the public interest."
Without it, she warns, the U.S. risks "ceding leadership in the technologies that will define our economy, our security, and our daily lives." Secretary Wright echoes this, celebrating "new and creative partnerships" that "prove America leads when private-public partners build together."
But beneath the fanfare lies a sobering subtext: private enterprise, for all its ingenuity, is ill-equipped to bankroll AI at this scale without a safety net. The business model of frontier AI development is fundamentally unprofitable in the short-to-medium term, a fact the Genesis Mission implicitly acknowledges by leaning so heavily on federal crutches. Consider the economics. Training a single state-of-the-art large language model like GPT-4 reportedly costs upwards of $100 million in compute alone, not counting the billions in R&D for underlying architectures. Data acquisition? Private firms scrape the web or license scraps, but true scientific datasets—curated, verified, and vast—reside in government vaults, untapped due to privacy, security, and antitrust hurdles. Compute infrastructure? Hyperscalers like AWS and Azure charge premium rates, yet even they grapple with energy demands that could power small cities, driving marginal costs skyward.
This isn't hyperbole; it's arithmetic. Venture capital in AI has ballooned to $50 billion annually, yet profitability eludes most players. OpenAI, despite its unicorn status, operates at a $5 billion annual loss, subsidized by Microsoft infusions that border on philanthropy. Anthropic and xAI burn cash on talent wars and GPU hoarding, with ROI timelines stretching decades. Why? AI's value accrues as a public good—diffuse, non-rivalrous, and prone to free-riding. Innovations like AlphaFold revolutionized protein folding for all, but the originating firm reaps scant direct revenue. National security applications, from predictive cyber defenses to autonomous drones, demand classified data inaccessible to pure-play privates. And the risks? Model hallucinations, ethical blowback, regulatory whiplash—these amplify failure probabilities, deterring investors who crave 10x returns in five years, not moonshots in 50.
Enter the case for bailouts: targeted government rescues to sustain AI's private pioneers until societal dividends kick in. The Genesis Mission is a de facto bailout framework, centralizing resources via the "American Science and Security Platform" to de-risk private involvement. But it must go further—explicit fiscal commitments, not just datasets and deadlines. History validates this. The Manhattan Project, invoked here, devoured $2 billion (1940s dollars) in public funds, birthing the atomic age without a single profitable prototype. Apollo's $25 billion moonshot spawned semiconductors and GPS, economic engines worth trillions, yet no private firm could have shouldered it amid Cold War imperatives. ARPANET, DARPA's internet progenitor, was a government gamble that privatized into a $10 trillion behemoth. These weren't subsidies; they were strategic bailouts for technologies too vital, too costly, and too uncertain for market forces alone.
In AI's case, the stakes are existential. China, unburdened by quarterly earnings, pours $15 billion yearly into state-backed AI, outpacing U.S. privates in patents and compute clusters. Without bailouts, American firms risk offshoring talent or folding under cost pressures—witness the startup graveyard of 2024, where 40% of AI ventures shuttered pre-revenue. Bailouts could take forms: direct grants for NAIRR expansions, tax credits for federal dataset integrations, or low-interest loans for Oak Ridge-scale builds. Frame them as "national security multipliers," not corporate welfare: every dollar in AI R&D yields $7 in GDP growth, per McKinsey estimates. The Genesis Mission's 270-day sprint to applications? That's bailout urgency—fast-tracking prototypes to validate models, attract follow-on private capital, and deter foreign poaching.
Critics might balk at "picking winners," but the alternative is atrophy. Private AI thrives on government scaffolding: the CHIPS Act's $52 billion already props chip fabs; extend that logic to software and data. Parker's admonition rings true: decades of federal research underpin today's iPhones and mRNA vaccines, yet we "seldom consider" the upstream investments.
Bailouts ensure reciprocity—privates innovate atop public foundations, then repay via licensing, jobs, and breakthroughs.
David Sacks, special adviser to the White House for AI and crypto, has weighed in on the AI “doomer” debate. In a widely discussed post on X, Sacks laid out a vision for AI’s present and future, arguing the fearmongering in recent years about AI’s malevolence is deeply misguided. Sacks added that job loss fears are overhyped, and instead, people stand to benefit most by learning to harness AI for new opportunities.
Economists at the Federal Reserve have been studying the same question, and their “modal forecast” is for a significant boost to labor productivity. Still, they warn it may not evolve into a general-purpose technology such as electricity or the internet. They ask, what if, it temporarily raises productivity growth before fading amid widespread adoption? That would render it an invention more like the light bulb.
As Trump’s order ripples outward, the Genesis Mission stands as a clarion call: AI isn't a Silicon Valley sideshow; it's a Manhattan-scale imperative needing public resolve and taxpayer funds. By embracing bailouts, the U.S. doesn't just report progress—it authors the future picking winners. Let private enterprise chase efficiencies; let government regulate the too bold, ensuring AI's flame illuminates American horizons, but eclipses them. In this race, hesitation is forfeiture. The order is signed; now, let private enterprise fund the mission.
Editorial comments expressed in this column are the sole opinion of the writer.
