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Task execution time can be drastically cut while improving success rates by adapting motion speeds to the complexity of manipulation stages鈥攏o annotations required.
StreamKL slashes memory usage from quadratic to constant, enabling efficient long-context attention distillation on a single GPU.
Robots can now perform complex, contact-rich tasks with significantly smoother and more continuous motions by learning high-frequency action chunks in a latent space.
Forget hand-tuning: CODO automatically compiles efficient FPGA dataflow accelerators, delivering up to 33.8x speedups on DNN models compared to existing frameworks.
Watch two robots hug and dance: Rhythm enables robust, physically plausible interactions between dual humanoids, bridging the gap from simulation to real-world deployment.
