Generative AI has begun to reach into biology, where it can propose genetic blueprints for microscopic viruses. In 2025, Stanford University PhD student Samuel King used a generative AI model for that purpose. The work did not create AI-generated life, but it offers a starting point for asking what AI might be able to design in the future.
What King’s work set out to do
King’s project produced proposed genetic blueprints for microscopic viruses. A blueprint is a design proposal, not evidence that a living organism has been created. The distinction matters: the work points to a possible role for generative AI in biological design, while stopping short of demonstrating that AI can generate life.
The source describes the result as preliminary. That framing keeps the achievement in perspective: it is an early answer to the question of whether AI can design new life forms, rather than a final demonstration that it can. The possibility that AI-generated life could come next is presented as an open question.
Why the distinction between design and life matters
A computer model can propose a genetic sequence without that proposal becoming a living virus. King’s work, as described, concerns blueprints for microscopic viruses; it does not establish that the model produced functioning organisms or that new life was created.
This gap helps explain why the research is significant without overstating it. AI-generated biological designs could change how scientists think about the building blocks of life, but the source gives no account of a completed transition from digital proposal to living form. For now, the work is an example of AI contributing a design idea in biology.
That leaves several questions open. What would it take for a proposed blueprint to become a real biological entity? What would count as AI having designed new life? The article presents these as part of a conversation about future possibilities, not as outcomes already reached.
AI may offer new ways to see biology
The discussion around King’s work is also about how artificial intelligence could change the way people observe and interpret biology. Generative models offer one way to propose designs, and those proposals may give researchers different ways to think about biological systems. The source describes this broader topic as “new ways of seeing biology.”
That idea reaches beyond a single set of viral blueprints. If AI can suggest patterns or designs that people would not otherwise consider, it may become a tool for exploring biological questions. But a proposal from a model still needs to be understood for what it is: an output that can prompt investigation, not proof that life has been made.
King’s project therefore sits at the intersection of two questions: what generative AI can design, and what those designs might mean for biology. The work invites discussion about where the field could go next while its current result remains carefully bounded.
A conversation about what comes next
MIT Technology Review announced a subscriber-only conversation in which senior AI reporter James O'Donnell would interview King. The discussion was set to cover King’s work, his being named one of MIT Technology Review's Innovators Under 35 and new ways of seeing biology.
The event listing gives the live time as October 16th at 18:30 BST / 1:30pm EDT / 10:30am PDT. It identifies O'Donnell as an AI reporter and King as a Bioengineering PhD Candidate at Stanford University/Arc Institute.
The planned conversation reflects the significance of an early result: not that AI has already generated life, but that models are being used to propose biological designs and that those proposals raise questions worth examining. King’s work supplies a preliminary case for discussing what AI-designed viruses could mean, while leaving the larger question of AI-generated life unanswered.