Mojo is a programming language developed by Modular Inc., initially released internally in September 2022. It was created to address the complexities of programming across the entire stack in the field of machine learning and artificial intelligence (AI). The language offers innovative and scalable features, including powerful compile-time metaprogramming, adaptive compilation techniques, and caching throughout the compilation flow. Mojo aims to target accelerators and heterogeneous systems commonly used in AI, making it uniquely suited for this field.
Mojo was developed by Modular Inc., a company founded by Chris Lattner, the original architect of the Swift programming language, and Tim Davis, an ML thought leader at Google. The founders' expertise and vision have contributed to Mojo's development.
An initial build of Mojo was introduced by Modular Inc. in September 2022. Since then, it has undergone further development to become a viable and innovative programming language.
Mojo leverages the Multi-Level Intermediate Representation (MLIR) compiler framework to power its advanced compilation features. MLIR, initially started at Google and continued at Modular, has been widely adopted in the machine learning accelerator community for its ability to build domain-specific compilers.
Mojo's history is rooted in the challenges of AI and machine learning programming. The founders of Modular Inc. recognized the need for a new programming language as they encountered complexities while unifying AI infrastructure. They found existing languages lacking in support for modern chip architectures and accelerators. This realization led to the development of Mojo, with a focus on providing a powerful and unified solution for AI workloads.
Mojo offers several advantages over Python, a dominant language in the AI and machine learning fields. It provides compatibility with the Python ecosystem while introducing features for high-performance and low-level programming. Its hybrid type system allows developers to choose between static and dynamic typing for optimal control and predictability. Additionally, Mojo incorporates concepts like the borrow checker from Rust, enhancing memory safety.
Mojo's syntax and features are exemplified through the use of keywords like "fn" for creating typed, compiled functions and "struct" for memory-optimized alternatives to classes. The language's compatibility with Project Jupyter and its ability to call existing Python code demonstrate its versatility and ease of adoption within the Python ecosystem. Mojo's development progress is evident in its accessibility. It became accessible through browsers in May 2023 and is available locally on Linux systems since September 2023. These milestones reflect the language's evolution and readiness for use.
Modular Inc. has ambitious goals for Mojo's future. These include achieving full compatibility with the Python ecosystem and further enhancing its systems programming capabilities. Mojo is positioned to simplify the complexities of AI and machine learning programming while maintaining compatibility with existing Python code, ensuring a smooth transition for developers.
For those interested in learning Mojo, its compatibility with Project Jupyter provides a familiar environment for experimentation and development. Developers can gradually migrate code from Python to Mojo while benefiting from Mojo's performance and low-level control. Mojo aims to offer a unified language that builds upon Python's strengths while addressing its limitations, creating a more robust and efficient programming experience for AI and systems-level development. Check out the Mojo programming manual