How AI could generate new life-forms | Eric Nguyen

0:06You're listening to TED Talks Daily, where we bring you new ideas to spark your curiosity every day. I'm your host, Elise Hu. When you think about AI literally generating new DNA, does that thrill you or scare you? For bioengineer and genomic AI pioneer, Eric Nguyen, it's a little bit of both. But for him, the possibilities of unlocking new medicines and curing diseases, among other things, makes it worth the risk. In his talk, he shares how looking at DNA as a language, one that AI can learn to read, write, and ultimately build will let us fundamentally change biology and life itself.

0:54I've always found it curious how biologists study life. There's this saying, a biologist will learn how a car works by poking at it, removing one part at a time, and seeing how it affects the rest of the car. On the other hand, an engineer will learn how a car works by taking it completely apart and rebuilding it. Take, for example, the Human Genome Project, one of the biggest breakthroughs of the last century. We spent over a decade mapping out all three billion letters of our genome, the complete set of DNA. We thought that once we could read DNA and apply that same principle, poking and dissecting one letter at a time, that we can start eradicating all human diseases.

1:43But instead, we began to realize just how little we actually understood about the true function of DNA. As a researcher, I work on artificial intelligence and trained as an engineer. I learn by building things and understand by creating. Today, I want to share an idea that can fundamentally change how we study biology and life itself. Instead of just reading and dissecting DNA, we should be generating it. And we can do this by treating DNA as a language, one that AI can learn to read, write, and ultimately build. This idea led myself and a team of researchers at Stanford and the Ark Institute with a sort of moonshot.

2:43Can we generate an entire genome from scratch using AI? Build life from the ground up? Now, I understand the thought of feeding the code of life into a generative AI is both thrilling and perhaps unsettling. But I came to realize that if this was possible, it could unlock some of the most powerful breakthroughs in science and medicine. But I'll be honest, we had no idea if AI could actually generate DNA. In many ways, DNA is like a language. It has grammar, structure, sort of like sentences and paragraphs that group together to form a story. And these stories are passed down through evolution, generation by generation.

3:38For humans, it's been hard to comprehend these stories written in DNA, in large part because of its scale. DNA is extremely long, and yet at the same time sensitive to the smallest mistakes. Imagine trying to write something the length of 30 ,000 books in a foreign language, and that when you're off by a single letter, one of billions, this can mean the difference between a healthy person and a person with a life-threatening disease. And so to tackle these challenges, Together with my colleague, Michael Polley, we developed an AI that could generate extremely long sequences of DNA 500 times longer than previous AI models at high levels of detail.

4:32We assembled a team of scientists and AI experts and gathered the largest collection of DNA used to train AI. 80 ,000 whole genomes fed into a model that we called Evo. And our goal was to create something like a chat GPT for DNA, where you can prompt Evo and describe the DNA you want, and it would generate new sequences, one letter at a time. But there is one key difference. With chatbots, you can just read what it writes, and you can decide if it makes sense to you. With DNA, it's not so simple. It's not an intuitive human language. How do you know if it's any real or good? What does that even mean?

5:19What we needed was a test, a way to verify that what it wrote would actually function. And so we started with a familiar tool in biology called CRISPR. CRISPR is like a pair of molecular scissors that can edit DNA, used for things like gene therapy. We asked Evo to make its own and generate its own version of CRISPR from scratch, which had never been done before. It's got proteins and RNA inside. It's a complex system. And so our biologists would take that generated DNA and analyze it to see how realistic does it look. Does it resemble something in nature? How do its proteins fold? Which all give us a sense of its function.

6:08But ultimately, we have to test their ability to cut DNA by actually building them in the lab. And so that's what we did. Now, waiting for lab results can sometimes be a nerve-wracking experience. Honestly, it's kind of like waiting for the results of a pregnancy test. You're excited, anxious, and hopeful for a positive outcome. And then all of a sudden, these two little lines appear. Just to be crystal, crystal clear, these two lines are a good thing. That's what we want. It means that our CRISPRs cut a single strand of DNA into two, in the exact right spot, just like natural CRISPRs in the lab.

6:57And so that's when we knew. It worked. Evo-generated DNA that not only looked realistic, but that actually functioned. And so next, we decided to go for that moonshot to try and generate a whole genome from scratch. and EVO was able to generate hundreds of synthetic proteins in a genome that resembled those in nature. But ultimately, it was missing a few parts. It wasn't yet complete, more like a rough sketch of the genome. However, this is just the first version. That rough sketch of the genome will become more detailed over time. In fact, within years, we anticipate AI will be able to generate whole functional genomes.

7:44In other words, AI will be able to generate new life. As this technology improves, biology will shift from discovery to design. What might this world look like? Let's look ahead. In this future, we can make truly personalized medicine. Imagine prompting an AI like Evo with your genome finding sources of diseases, predicting your reaction to drugs, and guiding treatment options based on your own DNA. But why even take medicine when you might have a permanent cure? We might choose to alter our DNA outright, and we are beginning to see this today. Recently, the FDA approved the first gene therapy for sickle cell disease, a painful, lifelong condition of the blood.

8:43And it works by just changing a single gene in a person's DNA to permanently cure the patient. And now, there are over 500 DNA-altering treatments awaiting approval. But let's say you're not comfortable with changing your DNA. What if we added new DNA? All of our DNA is organized into 23 pairs of chromosomes. Chapters, if you will, in the book that is our genome. What if evil learned to generate a 24th chapter, a whole new chromosome equipped with all the machinery needed to fight hundreds of diseases on demand? With DNA generation, what is the limit of what's possible? We've all seen Jurassic Park.

9:34We all thought it was science fiction, and it is. Mostly. Researchers are now reconstructing the genomes of extinct species, with one company planning to resurrect the woolly mammoth by as early as 2028. Now, instead of bringing back extinct species, can we create new ones? Researchers are now engineering microbes for colonizing Mars. If we one day wish to be a multi-planetary species, we'd have to figure out how to grow things on Mars, make it more hospitable and possibly terraform. And it is possible we have microbes on Earth that can handle a range of extreme conditions that we call extremophiles.

10:20Now, I understand some of these things might sound scary. One of the biggest concerns is biosecurity, the potential to create bioweapons. Can AI be used to generate more infectious viruses? Yes. but AI can also defend and monitor against these threats as well. And so perhaps you feel like me and that you have to choose between advocating for innovation versus safety. I'd encourage you to embrace both, because stopping progress entirely I don't think is practical. We need to evolve with the technology, monitor its capabilities, and constantly be asking ourselves, what possible futures are we enabling?

11:12As humans, we've always sought to understand the world around us. That is in our nature. But understanding alone has rarely been enough. For centuries, we've studied life by observing and dissecting it. But now, we're no longer just reading life's code. we now have the power to generate it. And with AI, we're at the beginning of unlocking new medicines, science, and even entire new forms of life. Do we make small edits? Do we write entirely new chapters? Or do we one day design life itself? Because to truly understand biology, we must create it. And the future of life is ours to build. Thank you.

12:20That was Eric Nguyen at TED 2025. If you're curious about TED's curation, find out more at ted.com slash curationguidelines. And that's it for today. Today, TED Talks Daily is part of the TED Audio Collective. This talk was fact-checked by the TED Research Team and produced and edited by our team, Martha Estefanos, Oliver Friedman, Brian Green, Lucy Little, and Tonsika Sungmarnivong. This episode was mixed by Christopher Faze-Bogan. Additional support from Emma Taubner and Daniela Balarezo. I'm Elise Hu. I'll be back tomorrow with a fresh idea for your feed. Thanks for listening.

13:03Thank you.