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AI Models Boost Transparency in Robot Plan Execution

Multiple AI models help robots execute complex plans more transparently

MIT's HiP system helps robots complete long-horizon goals using three foundation models: a large language model, a video diffusion model, and an egocentric action model. Iterative refinement improves the plan at each step for household and manufacturing tasks.

What does the future hold for generative AI?

MIT faculty members, including keynote speaker Rodney Brooks, discussed the power and potential pitfalls of generative AI tools like ChatGPT at the “Generative AI: Shaping the Future” Symposium, the kickoff event of the Institute’s Generative AI Week.

"Building Machines That Learn and Think Like People", 7 years later

In the post about GPT-4V, I mentioned the paper “Building Machines That Learn and Think Like People” (https://arxiv.org/abs/1604.00289) by Brenden Lake, Tomer Ullman, Joshua Tenenbaum, and Samuel Gershman. In that seminal paper the authors suggested that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it.

Multi-AI collaboration helps reasoning and factual accuracy in large language models