What happens when AI stops merely *reading* DNA and starts learning how to *write* it? Eric Nguyen, CEO and co-founder of Radical Numerics and a key figure behind Evo, joins us to explain the leap from early genome language models to Omni—a system that can outperform specialized models on disease-variant prediction, reason across biological sequences, and even begin to “show its work” when designing better molecules. The surprising part is *where those capabilities seem to be coming from*: in several cases, the model learns useful biological structure it was never explicitly taught.

But the same capability creates a much harder question: what happens when models can design sequences that preserve biological function while looking different enough to evade today’s defenses? Eric walks us through why current biosecurity systems may be solving the wrong problem, what an AI-native defense could look like, and why the teams pushing biological design forward may also need to build the systems that defend against it. The YouTube version is especially worth watching—we put Radical Numerics’ benchmark results and model visualizations on screen as Eric walks through what they actually show.