What Data Imperative for Action Learning of Embodied AI?

After occurring of large scale language models (LLMs), the development of Embodied AI is seen as a fundamental path to achieving artificial general intelligence (AGI). However, data is currently a key bottleneck for advancement in Embodied AI, compared to that of LLMs. In this talk, the learning strategies are first analyzed, especially for embodied manipulation. Meanwhile, various existing public datasets in embodied AI are investigated. Eventually, requirements for an imperative embodied AI dataset are concluded and an upcoming synthesized video dataset (rendered by Unreal 5) called MVGameIR is introduced.