MIT Technology Review hosts a session with Samuel King, the Stanford PhD student who in 2025 used a generative AI model to propose genetic blueprints for tiny viruses. The work is not yet AI-generated life, but the discussion asks whether that could come next.
Google Research presents work on grounding AI agents in real biology. The post is framed as building blocks toward autonomous wet labs.
Vinci4D sells simulation software for semiconductor designers that relies on pretrained physics models instead of conventional methods such as finite element analysis. The goal is to make simulations of how chips behave physically much faster.
Google researchers have open-sourced EnvHarness, a framework that adjusts agent-training environments to an agent's weak spots without changing the agent, the environment or the evaluation setup. The researchers say it can make learning both more effective and more efficient.
US startup Colossal Biosciences announced GenoMorph on October 14, an AI platform designed to identify the genetic edits needed for its 'de-extinction' projects. The company wants to use it to bring back the flightless dodo.
Amulya Vishwanath, who led product marketing for Nvidia's robotics platforms for seven years, says robotics is in its 'Lego era', with actuators, robotic hands, software and safety standards still being rebuilt. Her view runs counter to the idea that a general foundation model is about to transform robotics.