Difference between revisions of "Embodied AI"
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<b>Embodied AI</b> is an emerging field where AI algorithms and agents learn through interactions with their environments from an egocentric perception similar to humans, rather than learning from datasets of images, videos or text curated primarily from the Internet. This involves working with real-world physical systems, such as robots. The embodiment hypothesis is the idea that “intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity” | <b>Embodied AI</b> is an emerging field where AI algorithms and agents learn through interactions with their environments from an egocentric perception similar to humans, rather than learning from datasets of images, videos or text curated primarily from the Internet. This involves working with real-world physical systems, such as robots. The embodiment hypothesis is the idea that “intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity” | ||
Revision as of 08:00, 20 May 2023
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- ALFRED
- AlfWorld
Embodied AI is an emerging field where AI algorithms and agents learn through interactions with their environments from an egocentric perception similar to humans, rather than learning from datasets of images, videos or text curated primarily from the Internet. This involves working with real-world physical systems, such as robots. The embodiment hypothesis is the idea that “intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity”
