I'm familiar with the concept of broadcasting in Numpy, but I don't understand what it means in this context. Can someone explain?

__s basically covers it but my initial switch from pure python to NumPy just involved changing my vector 'class' (just a tuple in reality) into NumPy arrays. Whilst the basic vector multiplications and additions became way faster the overhead of creating hundreds of tiny NumPy arrays was a killer.

So, just like in the original article instead of creating a single 1x3 array I created a Mx3 array where M represented as many rays as I could fit into memory at once (I have quite a weedy machine).

Due to how NumPy broadcasting exactly the same code for, say, subtracting the origin from a ray vector works to subtract that single origin vector for a multidimensional array of ray vectors.

I see now, thanks.

Basically map https://docs.scipy.org/doc/numpy/user/basics.broadcasting.ht...

So OP would've converted from indexing numpy arrays in Python space