[linguae]

My understanding is that enough time had passed between the AI winter of the late 1980s and the rise of big data and deep neural networks in the 2010s to where a relatively tiny minority of modern machine learning practitioners came from the old-school AI community, which tended to prefer Lisp or Prolog. When machine learning became hot in the past 15 years or so, many new entrants to ML who had no previous AI knowledge used the tools they’re familiar with, which are generally C, C++, Java, JavaScript, and Python. In addition, many in the natural sciences use Fortran and Matlab. Perhaps had the AI winter of the late 1980s not happened (which took out the Lisp machine market) and had Common Lisp not been relegated to certain niches, perhaps there would’ve been more usage of the language, which may have led to Python being less dominant today.

I love Lisp and Smalltalk, but I work as a machine learning researcher as my day job, and I code in Python at work. Admittedly I miss Common Lisp whenever I code in Python, and I think Jupyter notebooks are a poor man’s Smalltalk environment, but when comparing Python to C and C++ (and I used to work primarily in systems programming, so I know my way around C), Python is a major productivity boost.