A better method for planning complex visual tasks

MIT researchers have developed a generative artificial intelligence-driven approach for planning long-term visual tasks, like robot navigation, that is about twice as effective as some existing techniques. Their method uses a specialized vision-language model to...

Featured video: Coding for underwater robotics

During a summer internship at MIT Lincoln Laboratory, Ivy Mahncke, an undergraduate student of robotics engineering at Olin College of Engineering, took a hands-on approach to testing algorithms for underwater navigation. She first discovered her love for working with...

New method could increase LLM training efficiency

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning. But developing...