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Arachne achieves up to 65% faster iteration times for Text-to-Video model training by optimizing the orchestration of computational units across diverse data.
By pretraining a VLA model with goal-conditioned RL, PRTS learns to reason about goal reachability, leading to substantial gains in long-horizon robotic tasks and zero-shot generalization.
Forget slow, suboptimal SVD compression: Swift-SVD delivers theoretically optimal low-rank LLM compression with 3-70x speedups.
