本·阿弗莱克谈 VFX 中的机器学习与 Python
Simon Willison 博客引用本·阿弗莱克的一段话：他从小对计算机感兴趣，胶片转向数字后更关注视觉特效，而特效工作流程多年来一直包含机器学习。他提到卷积神经网络——transformer 的前身——用于处理张量（画面帧、红绿蓝像素值的数值化表示），通过边缘检测和特征提取识别窗台等物体的位置，从而更方便地抠掉绿幕、替换背景。他自嘲能写“相当糟糕的 Python 脚本”。
为什么重要：这只是一段从业者视角的闲谈，没有新的模型、数据或产品信息，对 AI 从业者的日常判断几乎没有影响。
7th October 2026
I've always been kind of into computers since I was young. And then when film started to move from analog film to digital, I became more interested in that aspect of it. And the visual effects workflow for many years has included machine learning.
So I can write like pretty shitty Python scripts and stuff like that because with convolutional neural networks, which were the sort of precursors to what the transformer can do, which is just much more computation simultaneously, you would do things like look at what's called a tensor, which is just the numerical translation of a visual image in numbers — like the batch number, the frame number, the red, green, and blue values of each pixel in each frame.
And a tensor, you use a convolutional neural network to identify patterns in that that would reveal what's called edge detection or feature extraction, which is just identifying patterns enough to know like this is where the window ledge is, so we can more easily take the green screen image out and replace it with something.
— Ben Affleck, Pythonista