it's neat, but it's kinda slow (25x slower than native when I tested it)

In a JupyterLyte notebook:

    import numpy as np
    a = np.random.randn(128,128)
    b = np.random.randn(128,128)
    %timeit a @ b
    1.5 ms ± 3.3 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

On my command line:

    $ python3 -m timeit --setup 'import numpy as np; a = np.random.randn(128,128); b = np.random.randn(128,128)' 'a @ b'
    5000 loops, best of 5: 59.4 usec per loop