«Они получили то, что заслужили»Король порно оказался замешан в жестоком убийстве. Как ему удалось избежать наказания?17 августа 2022
发布会的另一个重头戏则是小鹏正式发布了第二代 VLA（Vision-Language-Action，视觉-语言-动作）物理 AI 大模型，并宣布大众汽车将成为小鹏第二代 VLA 的首发客户。
Sansa is wondering why I keep wasting catnip on vacuum testing.，这一点在体育直播中也有详细论述
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Abstract:Autoregressive decoding is bottlenecked by its sequential nature. Speculative decoding has become a standard way to accelerate inference by using a fast draft model to predict upcoming tokens from a slower target model, and then verifying them in parallel with a single target model forward pass. However, speculative decoding itself relies on a sequential dependence between speculation and verification. We introduce speculative speculative decoding (SSD) to parallelize these operations. While a verification is ongoing, the draft model predicts likely verification outcomes and prepares speculations pre-emptively for them. If the actual verification outcome is then in the predicted set, a speculation can be returned immediately, eliminating drafting overhead entirely. We identify three key challenges presented by speculative speculative decoding, and suggest principled methods to solve each. The result is Saguaro, an optimized SSD algorithm. Our implementation is up to 2x faster than optimized speculative decoding baselines and up to 5x faster than autoregressive decoding with open source inference engines.