Said to combine the usability of Python with the performance of C, Mojo is designed to be the programming language of choice for artificial intelligence (AI) development.
A member of the Python family of languages, Mojo is fully compatible with the Python ecosystem and might be considered a subset of Python. Over time, it may become a superset of Python. Mojo bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. The language allows for portable codes that are faster than C, with seamless interoperability with Python.
Mojo is under development with Modular, an AI company founded by former Apple and Google engineers and executives, and based in the San Francisco Bay area. A next-generation AI developer platform, Mojo was conceived as the language of choice for AI. While the company's intent is to open-source Mojo eventually, the language is currently being incubated within Modular.
According to Modular, the company hadn't intended to build a new programming language, but, as its AI development was underway, they realized that programming across the entire stack was too complicated. Seeking an innovative and scalable programming model that could target accelerators and other systems common in the AI field, they needed a programming language with powerful compile-time metaprogramming, integration of adaptive compilation techniques, caching throughout the compilation flow, and other features that weren't found in existing languages, such as high-performance support for a wide variety of accelerators.
Multi-Level Intermediate Representation (MLIR) is a new open-source compiler infrastructure that was first implemented at Google, whose leads moved to Modular. In its quest to build a next-generation AI platform, Modular was already using MLIR for some of its infrastructure but needed a programming language that could unlock the full potential of MLIR, so Mojo is the first major programming language designed expressly for MLIR.
In developing the language, the Mojo team chose to embrace the Python ecosystem since it's so widely used and generally works well with the AI ecosystem. Thus, the goal was to retain full compatibility with the Python ecosystem and to make it easier for Python coders to migrate to Mojo. There were influences from C, C++, Julia, Nim, Rust, Swift, and Zig, as well.
In terms of importing existing Python modules for use in a Mojo program, Mojo is 100% compatible with Python because it used CPython for interoperability. However, in terms of migrating any Python code to Mojo, it is not yet fully compatible. Although Mojo supports many of Python's core features, including async/await, error handling, variadics, and so on, the language is still new and has not yet incorporated some of the other features from Python, such as classes.
Where the goal is to mix Python and Mojo code, the expectation is that Mojo will cooperate directly with the CPython runtime and have similar support for integrating with CPython classes and objects without having to compile the code itself. This allows for plug-in compatibility with a massive ecosystem of existing code.
The intention is full compatibility with Python, although Mojo is an entirely new language with an entirely new compilation and runtime system. There is nothing in the implementation, compilation, or runtime that uses any existing Python technologies.
While compatibility and migratability with Python are important to the success of Mojo, it is a standalone language.
Recommended Resources
GitHub is a developer platform, used to build, scale, and deliver secure software. Although Mojo is under development in-house by Modular AI, the intention is for it to be open-sourced at some time. The repository was opened in order to gather issues and engage in feedback from users who have access to the Mojo Playground, its hosted JupyterHub where coders can experiment with coding with an early version of Mojo. Issues may be reported here, and links to other resources are included.
https://github.com/modularml/mojo
Mastering Mojo Programming Language: An In-Depth Guide for Developers
Code Avail was developed as an online resource for computer science academic help, projects, and assistance with programming languages, including live tutoring and freelance work. Its section on the Mojo programming language discusses its development and characteristics, including its uses in the real world, comparisons between Moho and other programming languages, an evaluation of the language, conclusory comments, and links to related topics on the same site.
https://www.codeavail.com/blog/mojo-programming-language/
The Mojo programming language was developed in-house by Modular, an AI development company seeking a next-generation programming language for artificial intelligence applications. Its AI inference engine, its software stack, and Mojo, designed to provide superior programmability of AI hardware and extensibility of AI models, are discussed here, and illustrated in several ways, including the Mojo programming manual, and information about the Mojo Playground, used for testing codes.
https://www.modular.com/
Hash13 offers training programs on a wide range of technologies for the Indian workforce. If successfully completed, its training course on the Mojo programming language will result in a signed certificate of training that can be added to CVs or resumes, posted on Linkedin, and used to enhance credibility and increase potential opportunities. The mentor for the program is introduced, and a list of what will be learned during the course of the training is included.
https://www.hash13.com/mojo-training/
W3Resource was created in 2008 to be an online web development resource. Its tutorial on the Mojo programming language, a next-generation programming language for artificial intelligence development, includes some of the key points of the language, including its relationship and compatibility with Python, and some of the problems with Python that Mojo is intended to solve. The characteristics of Python are listed, as reasons why Mojo was needed, as well as its compatibility with Python.
https://www.w3resource.com/mojo/
Mojo is a new programming language that bridges the gap between research and production by combining the best of Python syntax with systems programming and metaprogramming. Its usability, programmability, performance, interoperability, and extensibility are discussed here, and links to Mojo references, tutorials, and documentation hardware are included, including a link to an online form that can be used to request further access and information on aspects of Modular's projects.
https://mojolang.org/
This New Programming Language is Likely to Replace Python
This article by Mohit Pandey, published in AIM (Analytics India Magazine) on May 3, 2023, introduces Mojo, a new programming language developed by Modular AI, which combines the syntax of Pythonn with the portability and speed of C. Its key features are outlined, along with comparisons with Julia, Rust, and Swift, and speculation about whether it will eventually supplant Python or become merely another competitor. Beyond AI, its role as a standalone programming language is also discussed.
https://analyticsindiamag.com/this-new-programming-language-is-likely-to-replace-python/
