Dong Hao, a vice professor at Peking University and chief scientist at Shangwei Qiyuan, proposes a new paradigm for embodied AI development. He argues that current methods relying solely on imitation learning or reinforcement learning have limitations, particularly in handling errors and achieving general intelligence. Hao advocates for a two-dimensional "Scaling Law" that considers both the quantity of data and the number of tasks, aiming for robots that become more efficient and capable with more learning. AI
IMPACT This new 2D Scaling Law could accelerate the development of general-purpose robots by making learning more efficient.
RANK_REASON Academic presentation of a new theoretical framework for AI development. [lever_c_demoted from research: ic=1 ai=1.0]
- AGI
- Baidu Intelligent Cloud
- Beijing Academy of Artificial Intelligence
- Dong Hao
- InternData-A1
- Peking University
- Shanghai Artificial Intelligence Laboratory
- Ursa Minor
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