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字节跳动近日宣布推出全新的InfinityStar框架，该框架显著提升了视频生成效率，将生成一段5秒720p视频所需的时间缩短至仅58秒。这一创新不仅提高了生成速度，还通过统一的架构支持各种视觉生成任务，包括图像生成、文本到视频生成以及视频延续等。

微信AI联合清华大学发布了连续自回归语言模型（CALM），这一创新性技术引发了业界广泛关注。 传统的大型语言模型（LLM）依赖于预测下一个token（词元），虽然保证了连贯性，但也带来了高昂的计算成本和响应延迟。CALM的出现，旨在解决LLM效率瓶颈，为构建更高效的语言模型提供了新的思路。 CALM的核心理念：从离散到连续 CALM的核心在于将语言建模从预测离散的token，转向预测连续的向量。

众所周知，大型语言模型（LLM）的根本运作方式是预测下一个 token（词元），能够保证生成的连贯性和逻辑性，但这既是 LLM 强大能力的「灵魂」所在，也是其枷锁，将导致高昂的计算成本和响应延迟。可以说，业界「苦」LLM ...