Most digital images intended for viewing are generally assumed to be in sRGB colour space, which is gamma-encoded. This means that a linear increase of value in colour space does not correspond to a linear increase in actual physical light intensity, instead following more of a curve. If we want to mathematically operate on colour values in a physically accurate way, we must first convert them to linear space by applying gamma decompression. After processing, gamma compression should be reapplied before display. The following C code demonstrates how to do so following the sRGB standard:
Union and government to restart talks on ending doctor dispute
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大众对已故知名人士的关注也催生了搜索高峰，包括英国摇滚歌手奥兹·奥斯本、美国摔跤手哈尔克·霍根、美国演员米歇尔·特拉克滕伯格与戴安·基顿，这一现象反映出人们希望了解这些有影响力人物的生平背景与人生轨迹。
I have been thinking a lot lately about “diachronic AI” and “vintage LLMs” — language models designed to index a particular slice of historical sources rather than to hoover up all data available. I’ll have more to say about this in a future post, but one thing that came to mind while writing this one is the point made by AI safety researcher Owain Evans about how such models could be trained: