Here's some benefits it might try to offer as differentiators:
1. Easy packaging into one executable. Then, making sure that can be reproducible across versions. Getting code from prior, AI papers to rub can be hard.
2. Predictability vs Python runtime. Think concurrent, low-latency GC's or low/zero-overhead abstractions.
3. Metaprogramming. There have been macro proposals for Python. Mojo could borrow from D or Rust here.
4. Extensibility in a way where extensions don't get too tied into the internal state of Mojo like they do Python. I've considered Python to C++, Rust, or parallelized Python schemes many times. The extension interplay is harder to deal with than either Python or C++ itself.
5. Write once, run anywhere, to effortlessly move code across different accelerators. Several frameworks are doing this.
6. Heterogenous, hot-swappable, vendor-neutral acceleration. That's what I'm calling it when you can use the same code in a cluster with a combination of Nvidia GPU', AMD GPU's, Gaudi3's, NPU's, SIMD chips, etc.
1. Easy packaging into one executable. Then, making sure that can be reproducible across versions. Getting code from prior, AI papers to rub can be hard.
2. Predictability vs Python runtime. Think concurrent, low-latency GC's or low/zero-overhead abstractions.
3. Metaprogramming. There have been macro proposals for Python. Mojo could borrow from D or Rust here.
4. Extensibility in a way where extensions don't get too tied into the internal state of Mojo like they do Python. I've considered Python to C++, Rust, or parallelized Python schemes many times. The extension interplay is harder to deal with than either Python or C++ itself.
5. Write once, run anywhere, to effortlessly move code across different accelerators. Several frameworks are doing this.
6. Heterogenous, hot-swappable, vendor-neutral acceleration. That's what I'm calling it when you can use the same code in a cluster with a combination of Nvidia GPU', AMD GPU's, Gaudi3's, NPU's, SIMD chips, etc.