Intel is talking about their own Python distribution getting released as a product. Early access has been available for a while and the suite, compatible with the popular Anaconda environment, is now being released in full.
The prevailing challenge in Python programming is to use all the benefits of a modern CPU such as vectors, cores, etc. This is also a reason why TIK teaches these topics in dedicated courses: notably High Performance Python, Python and Parallelism, Python for Science and Engineering or Python for Finance. Now, Intel is hoping to put more compute power in the hands of high-level language programmers.
Concretely, the Intel distribution contains optimized versions of numerical packages. Under the hood, Intel used technologies such as its Math Kernel Library, Threading Building Blocks or the Intel Compiler to maximize computational performance. Intel says that with these improvements, their numerical Python code runs close to native performance. While it is an important stepping stone, we are probably all hoping for a situation where many applications other than linear algebra can run fast coded in high level languages such as Python. Intel recognizes this need in packages such as numpy, scipy and scikit-learn.
Intel’s Python packages can be obtained directly from the Anaconda Cloud.
See also: the press release by Continuum Analytics, Anaconda’s creators.