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Achieving critical-point preservation in vector-field compression at GPU speeds up to 640 times faster than traditional CPU methods could revolutionize data handling in scientific simulations.
Kimi K3's innovative architecture achieves a 2.5x scaling efficiency improvement, enabling robust performance across diverse long-horizon tasks.
Achieving state-of-the-art performance with just 8 billion parameters, Embodied-R1.5 redefines the capabilities of embodied models in complex physical tasks.
Lossy compression that preserves data topology is now 200x faster, thanks to an algorithm that directly enforces topological consistency rather than reconstructing it.
Achieve orders-of-magnitude speedups in topology-aware lossy compression for scientific data with TopoSZp, without sacrificing compression ratios or introducing false positives in critical point detection.
