陈旧扩散：使用老派方法生成超写实5D电影
Stale Diffusion: Hyper-realistic 5D Movie Generation Using Old-school Methods
AI总结：
本文提出Stale Diffusion方法，将Stable Diffusion固化在最大熵状态，利用自然累积的错误生成超写实5D视频，并以“慢科学运动”自居回应AI暂停呼吁。
摘要：
两年前，Stable Diffusion在生成具有超人数量手指的图像方面实现了超人级性能。随着其技术新颖性的持续衰退，我们提出Stale Diffusion，一种将Stable Diffusion固化并僵化在最大熵状态的方法。Stable Diffusion的工作原理类似于一个谷仓（Stable），无限的马匹已从中逃逸（Diffusion）。由于马匹早已离开谷仓，我们的提议可能被视为过时且无关紧要。尽管如此，我们通过自认是“慢科学运动”的早期采纳者来极力捍卫我们的新颖性主张，该运动将在未来产生极其重要的智慧结晶。我们的贡献速度也可被视为对近期呼吁暂停AI实验的准静态落实，对此我们全心支持。通过对18个月前的Git提交历史进行细致的考古考察，我们发现自然累积的错误产生了一种新颖的熵最大化Stale Diffusion方法，该方法能够生成令人昏昏欲睡的超写实5D视频，其效果与人的想象力一样好。
英文摘要：
Two years ago, Stable Diffusion achieved super-human performance at generating images with super-human numbers of fingers. Following the steady decline of its technical novelty, we propose Stale Diffusion, a method that solidifies and ossifies Stable Diffusion in a maximum-entropy state. Stable Diffusion works analogously to a barn (the Stable) from which an infinite set of horses have escaped (the Diffusion). As the horses have long left the barn, our proposal may be seen as antiquated and irrelevant. Nevertheless, we vigorously defend our claim of novelty by identifying as early adopters of the Slow Science Movement, which will produce extremely important pearls of wisdom in the future. Our speed of contributions can also be seen as a quasi-static implementation of the recent call to pause AI experiments, which we wholeheartedly support. As a result of a careful archaeological expedition to 18-months-old Git commit histories, we found that naturally-accumulating errors have produced a novel entropy-maximising Stale Diffusion method, that can produce sleep-inducing hyper-realistic 5D video that is as good as one's imagination.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
