
AI Blueprints
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For much of the history of AI research and applications, working with images was particularly difficult. In the early days, machines could barely hold images in their small memories, let alone process them. Computer vision as a subfield of AI and ML made significant strides throughout the 1990s and 2000s with the proliferation of cheap hardware, webcams and new and improved processing-intensive algorithms such as feature detection and optical flow, dimensionality reduction, and 3D reconstruction from stereo images. Through this entire time, extracting good features from images required a bit of cleverness and luck. A face recognition algorithm, for example, could not do its job if the image features provided to the algorithm were insufficiently distinctive. Computer vision techniques for feature extraction included convolutions (such as blurring, dilation, edge detection, and so on); principal component analysis...