Can a small network learn new digits without forgetting old ones?
A user says they had Claude do automated research on a toy continual-learning problem, teaching a small network handwritten digits two at a time.
TLDR
A user describes a Claude-assisted Split MNIST experiment: a small neural network learns handwritten digits in orderβ0/1, 2/3, 4/5, 6/7, then 8/9. Each stage uses only that pairβs real training images, with testing on all ten digits after the final stage. The user says the setup starts with two training passes per task and reports results averaged across three random seeds.
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