Bridging Perception and Action in Robotics Multimodal Large Language Models (MLLMs) hold promise for enabling machines, such as robotic arms and legged robots, to perceive their surroundings, interpret scenarios, and take meaningful actions. The integration of such intelligence into physical…
Will the perfect storm of potentially life-changing, artificial intelligence-driven health care and the desire to increase profits through subscription models alienate vulnerable patients? For the third year in a row, MIT’s Envisioning the Future of Computing Prize asked students to describe,…
An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown disturbances inflight presents an enormous challenge for the…
Data should drive every decision a modern business makes. But most businesses have a massive blind spot: They don’t know what’s happening in their visual data. Coactive is working to change that. The company, founded by Cody Coleman ’13, MEng…
Despite the substantial progress in text-to-image (T2I) generation brought about by models such as DALL-E 3, Imagen 3, and Stable Diffusion 3, achieving consistent output quality — both in aesthetic and alignment terms — remains a persistent challenge. While large-scale…
Large reasoning models, often powered by large language models, are increasingly used to solve high-level problems in mathematics, scientific analysis, and code generation. The central idea is to simulate two types of cognition: rapid responses for simpler reasoning and deliberate,…
