buffer(values) — load a 1D array into a buffer
randn(shape, seed?) — random tensor, shape=[rows,cols] or [n]
matmul(W, x) — matrix × vector → vector
relu(x) / sigmoid(x) / tanh(x) — element-wise activations
add(a, b) — element-wise sum
scale(a, c) — multiply each element by scalar c
stencil(grid, rule, steps?) — run CA (rule: 'conway','rule30','rule110','seeds','brian_brain')
log(...args) — print to output log