[smohare]

2016 already puts one far into the AI explosion. The current hype cycle, with LLMs as a service at the forefront, arguably makes python less relevant than in it was in the mid 2010’s. The current crop of “AI Engineers” can use whatever languages they want for the most part. In 2016 most practitioners were leveraging a lot more of the standard scientific computing frameworks afforded by python.

[tptacek]

Python was the lingua franca of data science by 2016, but AI and data science was clearly not the reason startups were building in Django and Flask --- the data science teams were always a morass of Jupyter notebooks and pickle blobs.