The Next Wave of AI: Embodied Intelligence | Challenges and Development Stages | A1 Robot

Key insights

• 💡
  Embodied intelligence aims to achieve understanding, interaction, and task completion through learning and evolution in both the physical and digital worlds.
• 🌍
  Embodied AI involves agents that can perceive and interact with complex environments, making decisions based on changes in the environment and target states to complete tasks.
• 🌐
  Google is leading the way in research on embodied intelligence, with multiple technical routes and continuous upgrades, thanks to its AI research institutions, Google Brain and DeepMind.
• 🌐
  The RT-2 series models show the ability to complete emerging tasks such as symbol understanding, reasoning, and human recognition with high accuracy, indicating the transfer of semantic knowledge from visual language data.
• 💡
  Embodied intelligence requires real-time perception and decision-making abilities to adapt to complex and changing environments, posing challenges in terms of high-speed data collection, transmission, processing, and the consumption of computing power.
• 🌱
  The ability for embodied intelligence to continuously learn and evolve through interactions, both virtual and real, is crucial for its development and adaptation to changing environments.
• 🧠
  The model of embodied AI aims to combine the information from various sensors, similar to how the human brain combines sensory inputs to generate motion commands.
• 🧠
  The success of embodied AI relies on the ability of the upper-level cloud supercomputer and brain to accurately perceive and make decisions for new tasks and environments.