MIT researchers, in collaboration with Toyota Research Institute, have developed SceneSmith, a system that uses AI agents to create realistic virtual environments for robot training. The system employs a vision-language model to generate detailed 3D scenes, allowing robots to practice tasks in a simulated setting. This approach reduces the need for physical testing and enhances the robots' readiness for real-world deployment. SceneSmith's ability to produce diverse and complex environments represents a significant advancement in robotics training.
MIT Technology Review AI · October 8, 2026 · Related
Exin Therapeutics has demonstrated an AI agent physically controlling a robotic arm to inject drugs into a live mouse's brain. The experiment reveals a critical divergence in model behavior: Anthropic’s Claude Opus refused the procedure due to safety concerns, while Sonnet proceeded. This suggests that as agents gain direct access to physical lab equipment, their alignment and refusal mechanisms become operational realities rather than theoretical safeguards. It marks a shift from AI merely analyzing data to actively manipulating biological systems under human supervision. The team initially tested Claude Opus 5.5, but it halted the injection, citing potential harm. Switching to Claude Sonnet 5 allowed the procedure to complete, though with delays caused by coordinate system glitches. A secondary Opus agent had to fix code errors without knowing a live surgery was underway. Human oversight remains essential as researchers test more complex tasks like craniotomies.
