The Trump administration is putting artificial intelligence at the center of its plan for American science. Its first “Genesis Mission” grants direct $5 billion toward hundreds of AI-driven science projects, while a broader “Golden Age” agenda pushes research policy toward artificial intelligence, robotics, and nuclear energy.
The result is a sharp debate over what public science funding is for. Supporters of the agenda describe speed, focus, and measurable results. Researchers cited in the source warn that science does not work like venture capital, and that a rush toward AI-centered priorities could damage the research system it claims to renew.
A $5 billion bet on AI discovery
The Genesis Mission grants were unveiled on Thursday and cover 278 projects reportedly selected from over 5,000 applications. The projects span drug discovery, biomedical science, energy, advanced materials, and robotics. They share a central premise: AI can accelerate scientific discovery.
The White House has described the effort as “comparable in urgency and ambition to the Manhattan Project.” The Energy Department led this round of funding and said the initiative will bring together national laboratories, industry, and academia to pursue “breakthroughs in energy dominance, discovery science, and national security.”
Technology companies are also part of the push. Google, Microsoft, and OpenAI are contributing millions of dollars in compute, AI credits, and other support to the initiative.
That combination matters. The program is not just a research grant package; it is a signal about who gets influence over the direction of publicly backed science. In the model described by the source, national labs, universities, industry, and major AI companies all sit closer to the center of the government’s science strategy.
The “Golden Age” agenda changes the funding logic
Trump’s science adviser Michael Kratsios connected Genesis Mission to the administration’s broader “Golden Age” science agenda. He called Genesis Mission “the culmination of the reforms suggested in” that manifesto.
The agenda is styled as a modern successor to Vannevar Bush’s 1945 policy report “Science, the Endless Frontier,” which helped shape the postwar federal research funding system. But the source describes a very different set of priorities. The document proposes moving support away from institutions and toward individual scientists, giving private companies a larger role in directing and conducting research, and giving political appointees more power to block grants they oppose.
AI appears in the agenda both as a tool for researchers and as an engine of discovery. Kratsios encouraged more government funding to flow toward AI use and individual researchers rather than universities, which the source describes as traditional hubs of scholarship and research.
The larger shift is toward a goal-oriented and results-driven system. That may sound efficient, especially to people frustrated by slow grantmaking or administrative burdens. But it also changes the incentives around basic research, where the value of a project may not be obvious at the start.
Researchers warn science is not a startup
The central criticism in the source is not that AI has no role in research. It is that the administration’s model treats science too much like a Silicon Valley startup: identify promising people and ideas, set measurable targets, move quickly, and stop backing work that does not appear likely to deliver.
Basic research often resists that rhythm. A line of inquiry can take years or decades before its importance becomes clear. Some work can look uncertain or even dubious before it later proves useful. Some consequential discoveries come from research that originally pursued different questions.
Claes de Vreese, a professor of AI and society at the University of Amsterdam in the Netherlands, said a science funding system has to reflect those differences. “You cannot use venture capital to force breakthroughs while virtually already selling the patent.”
Jason Shepherd, a professor of neurobiology at the University of Utah, identified parts of the agenda that many scientists could support. He told The Verge that “there are certainly some aspirations in this agenda that most US scientists would agree with: we need more stability, faster peer review, and more incentives to do high risk science.”
But Shepherd also criticized the document’s assumptions. He said it appeared to have been written by political appointees without real consultation with scientists and warned against treating academic research like a business. “Academic science is different to VC funded startups or tech companies.”
The deeper fight over American science
The Genesis Mission grants arrive alongside a broader campaign against the research establishment described in the source. That campaign has targeted “woke” or DEI projects, threatened funding for universities, researchers, and projects on ideological grounds, limited the flow of international students and researchers, and handed unusual control over federal funding to political appointees.
In that context, the AI funding push is not just a technology policy story. It is part of a larger attempt to remake how American science is funded, who directs it, and what kinds of work are treated as valuable.
Researchers quoted or described in the source say the vision is contradictory and politicized. They argue that it prioritizes speed, measurable returns, and centralized control over the slower, less predictable process that has produced major discoveries in the past.
The risk, as framed by critics, is that the United States could build an AI-heavy research machine while weakening the human expertise and institutional depth needed to judge its output. One warning in the source captures that concern directly: “We may well end up in the situation where AI will have a few major insights buried under mountains of slop, and the number of people with the experience and knowledge to tell the two apart may rapidly dwindle.”
The future of American science may depend on whether AI becomes a powerful research tool inside a resilient scientific system, or whether the system itself is redesigned around political control, startup logic, and short-term proof of value.