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GigaBrain-0.7 achieves unprecedented task adaptability and completion rates, outperforming previous models in both home and industrial settings.
EvoHIL achieves unprecedented improvements in robotic manipulation by dynamically adapting reward models and ensuring action coherence, setting a new standard for human-in-the-loop learning.
WAM-TTT allows robot models to adapt to new tasks using only raw human videos, eliminating the need for additional demonstrations or fine-tuning.
Imagine training robots to manipulate objects in the real world, but entirely within a high-fidelity, diffusion-based dream.
