Neural nets taught to run short programs — and they get really good
Computers that learn from examples were taught to read tiny program text and give the right output. Using a kind of memory model called LSTM, researchers showed these machines can learn to turn characters into answers for small tasks. It wasnt magic; training needed a smart path where problems get harder step by step. That training path, a new version of curriculum learning, was the key — normal training failed, but this way helped across many tests. The result surprised many: the models handled simple program rules and even big math steps, one task reaching 99% accuracy when adding long numbers. This does not mean machines now understand code like people do, but it shows they can pick up patterns…
Neural nets taught to run short programs — and they get really good
Computers that learn from examples were taught to read tiny program text and give the right output. Using a kind of memory model called LSTM, researchers showed these machines can learn to turn characters into answers for small tasks. It wasnt magic; training needed a smart path where problems get harder step by step. That training path, a new version of curriculum learning, was the key — normal training failed, but this way helped across many tests. The result surprised many: the models handled simple program rules and even big math steps, one task reaching 99% accuracy when adding long numbers. This does not mean machines now understand code like people do, but it shows they can pick up patterns in text that look like rules. It’s a hint that with the right lessons, simple networks can do more than we thought, and maybe soon they will help make tools that check or run tiny scripts, faster, and safer.
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