The model and research behind Muse
A post thanking MSL’s research team calls Muse’s model its “most underrated part,” praising the work behind a product the author describes as simple and useful.
TLDR
A thank-you post credits MSL researchers with bringing original ideas and new methods to difficult problems while building Muse’s model. It also praises teams working on tool and computer use, memory, personalization, alignment, safety and multimodal understanding, alongside data, evaluations and infrastructure. The author describes the payoff as a product people can use without understanding the technical complexity underneath.
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