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Utilize the full power of the hardware, including multiple cores, vector units, and exotic accelerator units, with the world's most advanced compiler and heterogenous runtime. Achieve performance on par with C++ and CUDA without the complexity. Play with Mojo🔥.
Mojo is designed to solve a variety of AI development challenges that no other language can, because Mojo is the first programming language built from the ground-up with MLIR (a compiler infrastructure that's ideal for heterogeneous hardware, from CPUs and GPUs, to various AI ASICs).
Extend your Python code with high-performance Mojo, a new programming language with the expressiveness of Python and the performance of C. Learn about Mojo Develop locally, deploy globally to any cloud.
If you're new to Mojo, we suggest you learn the language basics in the introduction to Mojo. To learn more about the magic tool, read Get started with Magic . Explore more code examples in the the Mojo repo .
Sep 7, 2023 · Mojo is a new programming language for AI developers that will grow into being a superset of Python over time. It already supports integrating with arbitrary Python code seamlessly and has a scalable programming model to target performance-critical systems, including accelerators (e.g. GPUs) that are pervasive in AI.
While many other projects now use MLIR, Mojo is the first major language designed expressly for MLIR, which makes Mojo uniquely powerful when writing systems-level code for AI workloads. A member of the Python family
Yet, we've designed Mojo to be flexible, so you can incrementally adopt systems-programming features like strong type checking as you see fit—Mojo does not require strong type checking. On this page, we'll introduce the essential Mojo syntax, so you can start coding quickly and understand other Mojo code you encounter.
Mojo is a general purpose programming language, so it has no specific implementations for ML training or serving, although we use Mojo as part of the overall Modular AI stack. The Modular AI Engine, for example, supports deployment of PyTorch and TensorFlow models, while Mojo is the language we use to write the engine’s in-house kernels.
May 2, 2023 · The Mojo Language Server now reports a warning when a local variable is unused. Several mojo subcommands now support a --diagnostic-format option that changes the format with which errors, warnings, and other diagnostics are printed.
Mojo is still in early development and many language features will arrive in the coming months. We are highly focused on building Mojo the right way (for the long-term), so we want to fully build-out the core Mojo language features before we work on other dependent features and enhancements.
