Python has been one of the fastest growing programming languages for years now and with the new wave of A.I., that trend will continue. Though most A.I. models have traditionally been built on C and C++, Python itself is built on both and has some major upsides for machine learning.

Known for being easy to understand and read because of its syntax, Python being succinct lends itself well to A.I. development. In addition, the numerous libraries and frameworks in Python’s ecosystem for model training and data processing are tailor-made for machine learning. Because it has been gaining popularity for some time, the community support for Python has also thrived as a result with collaboration paving the way for innovation.

If this was not enough, Python is very flexible and scalable with a plethora of integrations with other various technologies. According to James Bourne of Developer-Tech News, “use of Python grew 571% in Snowpark,” and Python skills will become increasingly essential as developers journey into higher levels of A.I.. It is not necessary to recompile source code every single time which means being able to see the results of changes is faster, leading to more efficient coding. Coupled with the fact that Python is platform-independent means that it has major advantages when it comes to accessibility and ease of use.