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A matrix is a rectangular collection of row vectors and column vectors that defines linear transformation. A matrix however, is not implemented as a rectangular grid of numbers in computer memory, we store them as a large array of elements in contiguous memory.

This will be your example-driven guide to Mojo SDK 24.2, as part of the latest MAX release. If I had to pick a name for this release, I’d call it MAXimum⚡ Mojo🔥 Momentum 🚀 because there is so much much good stuff in this release, particularly for Python developers, adopting Mojo. 

At Modular, open source is ingrained in our DNA. We firmly believe for Mojo to reach its full potential, it must be open source. We have been progressively open-sourcing more of Mojo and parts of the MAX platform, and today we’re thrilled to announce the release of the core modules from the Mojo standard library under the Apache 2 license!

Today, we’re excited to announce general availability of MAX 24.2, with several big features.

In the field of natural language processing (NLP), semantic search focuses on understanding the context and intent behind queries, going beyond mere keyword matching to provide more relevant and contextually appropriate results. This approach relies on advanced embedding models to convert text into high-dimensional vectors, capturing the complex semantics of language.

Mojo as a language offers three main benefits, namely the 3 P’s: Performance, Programmability and Portability. It enables users to write fast code, do so easier than many alternative languages, and allows code to be run across different CPU platforms, with GPU support on the roadmap.

March 14th aka 3/14 or 3.14 is known as $\pi$ Day, and it honors the mathematical constant $\pi$ (pi), which represents the ratio of a circle's circumference to its diameter. On this special day, I wanted to dedicate a blog post to the beauty of mathematics, numerical methods, $\pi$, and Mojo. So join me on this journey as I implement a fast vectorized Monte Carlo approximation method of calculating $\pi$. Happy $\pi$ Day!

MAX Engine is a high-performance AI compiler and runtime designed to deliver low latency, and high-throughput inference for AI applications. We've shared how you can get started quickly with MAX in this getting started guide, and how you can deploy MAX Engine optimized models as a microservice using MAX Serving.

When we started Modular, building a programming language wasn't our goal, it ended up being a solution to a set of problems. Specifically, as we were building our platform to unify the world’s ML/AI infrastructure, we realized that programming across the entire stack was too complicated.

Today we’re thrilled to announce that MAX Developer Edition is now available in preview for developers worldwide! 🥳🎉. In this developer blog post, we'll take an in-depth look at MAX, its key features and capabilities, and how to use it to deploy your first MAX optimized model. Using code examples we’ll illustrate its benefits, cover key concepts, and share additional resources to continue your MAX journey.