The vast majority of real world ML code today is written in languages like Python and C++. Relatively few people outside of academia and online forums are functional language enthusiasts. The industry is also looking like most actual coding is going to be done by LLMs going forward, so it makes little sense to design new languages with a niche potential user base since LLMs need a ton of training data. I’m think that was a factor in deciding to base mojo on Python along with the other reasons they state.
agree with all of this. Though i'd say: since the language is mostly read by humans rather than written, in my opinion, it makes even more sense to have a language syntax that actually matches intent. In the case of Machine Learning, it's mostly connecting functions together and acting on them, which matches functional syntax. LLMs are also already very effective at writing ML-inspired syntax (like ocaml or f#) as they have plenty of data to train on, making llms effective from day one if a similar syntax was chosen.