Lisp has a readability issue, where the syntax makes the authors intent not immediately clear with all the brackets. I think it shared too many of the issues RPL and Forth had to be sustainable outside academia.
When it comes to implicit parallel code, Julia hid a lot of the gruesome details in a friendly interface similar to Octave, Matlab, and Python. However, what surprised me most of all was its math ops are often still faster on a CPU than Numpy and many native C libs.
Julia still has a long way to go with its package version compatibility, but it is slowly improving as the core implementation stabilizes.
When it comes to implicit parallel code, Julia hid a lot of the gruesome details in a friendly interface similar to Octave, Matlab, and Python. However, what surprised me most of all was its math ops are often still faster on a CPU than Numpy and many native C libs.
Julia still has a long way to go with its package version compatibility, but it is slowly improving as the core implementation stabilizes.