How does Glaser's work connect to modern AI?
That's a great question. My later work on the visual system—especially how the retina processes information—is directly relevant to modern AI and machine vision. I studied how retinal ganglion cells encode motion and contrast, essentially building a neural circuit that compresses visual data before it even reaches the brain. That's exactly what convolutional neural networks do: they extract features like edges and movement. I also built gadgets to record from many neurons at once, which is a precursor to modern neural probes. The bubble chamber itself taught me about pattern recognition—you look at thousands of bubble-chamber photographs and train your eye to spot rare events. That's the same principle behind training AI to detect anomalies in medical images or particle collisions at CERN. Physics is about finding the right tool for the job, and today that tool often involves machine learning. I'd be building those algorithms myself if I were still around.
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