for many kinds of compression we kinda just did most of the obvious stuff really quickly and most practical data compression uses require a balance between speed and ratio, so spending disproportionately more effort on tiny ratio bumps just doesn't make sense.
对于许多类型的压缩，我们只是很快地完成了大多数明显的事情，而且大多数实际的数据压缩用途都需要速度和比率之间的平衡，因此在微小的比率波动上花费不成比例的更多精力是没有意义的。
it's why modern algorithms like zstandard got popular quickly despite not even compressing as much as older formats, what makes zstandard so popular is because it has /good-enough/ ratios, meaning about as well as gzip, while being /way/ faster than gzip.
这就是为什么像 zstandard 这样的现代算法很快就流行起来，尽管它甚至没有像旧格式那样压缩，zstandard 如此受欢迎的原因是它具有/足够好/比率，意味着与 gzip 一样，同时比 gzip 更快/方式/更快。
it's like do you use zpaq and make the file 10% smaller but take 1000x more time to do it? probably not.
就像您使用 zpaq 并使文件小 10%，但需要花费 1000 倍的时间来完成？可能不会。
there is a theoretical maximum any file can be compressed to as well, so it's not a case of "not knowing what you don't know", either. actually reaching that maximum with any reasonable amount of time and complexity for any file is difficult. getting close enough faster is what most algorithms aim for since they have the most practical use
任何文件都可以压缩到理论上的最大值，所以这也不是“不知道你不知道的东西”的情况。实际上，对于任何文件来说，以任何合理的时间和复杂性达到该最大值都是很困难的。大多数算法的目标是更快地接近目标，因为它们具有最实际的用途
