Initially (before Mojo's release), I assumed the syntax choice was for better interoperability. Since Mojo is a superset of Python, I thought it could directly call any Python code. But after reviewing some interoperability examples—both Mojo calling Python and vice versa—it doesn’t seem all that seamless or straightforward.
For example, calling Python code from Mojo requires going through a proxy to the Python interpreter, which feels no better than what pyo3 already offers. Plus, Mojo has plenty of compatibility issues when running regular Python code.
So if better interoperability isn't the main reason for sticking with Python-like syntax, the only other explanation I can think of is to attract existing Python programmers. But is syntax really the reason people shy away from GPU programming? There are far more intimidating aspects to it—C++ syntax is probably the least of anyone’s concerns.
https://www.modular.com/blog/modular-platform-25-3-450k-line...
That's been the foundation for a lot of the performance work we've demonstrated publicly, most recently with our AMD partnership announcement.
https://www.modular.com/blog/modular-x-amd-unleashing-ai-per...
We're pretty committed to doing this work in the open, and we've taken a bunch of direct feedback and contributions from the community that have improved the standard library (also open source) and core language.
We're also putting in a lot of work to make Mojo more accessible for users. For example, our GPU Puzzles series is turning into a cornerstone of demonstrating how Mojo is meant to improve the GPU programming experience (that's work my team is directly responsible for, and I'm really proud of the experience people have had with it).
https://builds.modular.com/puzzles/introduction.html
For production workloads, I can say that we're using it in production, but as you said yourself, adoption takes time. I believe we're on the path to get there, and hopefully the work we're doing in public speaks for itself. It's really important to me that we back up our claims with evidence and real-world use cases.
