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Did you catch Fabian's presentation at SINTEF? If you missed out, he'll be doing it again in Oslo, Norway on the 15th of February!By popular request, we're publishing the slides here, and will soon have video to go with it. Make sure to subscribe to our YouTube channel to get the alert!

Strongly typed languages need some mechanism to express generic functions, other languages don't enforce types which means every function is generic. Many languages implement some form of this feature under a variety of different names:

For ModCon 2023 we'll be hosting a competition, where the best projects from around the community will be presented on stage.

Mojo SDK v0.5 is now available for download and includes exciting new features. In this blog post, I’ll discuss what these features are and how to use them with code examples. ICYMI, in last week’s Modular community livestream, we dove deep into all things Mojo SDK v0.5 with live demos of the examples shared in this blog post, while answering your questions live!

Jeff, Abdul, and Chris presented a talk about Mojo and how it relates to MLIR and LLVM, at the LLVM Developer Conference 2023.

Mojo allows you to access the entire Python ecosystem, but environments can vary depending on how Python was installed. It's worth taking some time to understand exactly how modules and packages work in Python, as there are a few complications to be aware of. If you've had trouble calling into Python code before, this will help you get started.

How do you guarantee that your software is portable, runs reliably, and scales easily in production environments? The short answer is: Use containers. Container technologies like Docker and Kubernetes are popular tools for building and deploying software applications, but until recently they were considered exotic infrastructure for IT/Ops experts. 

Learning a new programming language is hard. You have to learn new syntax, keywords, and best practices, all of which can be frustrating when you’re just starting. In this blog post, I want to share a gentle introduction to Mojo from a Python programmer’s perspective.

Today’s AI infrastructure is difficult to evaluate - so many converge on simple and quantifiable metrics like QPS, Latency and Throughput. This is one reason why today’s AI industry is rife with bespoke tools that provide high performance on benchmarks but have significant usability challenges in real-world AI deployment scenarios.

In this post, we describe Modular’s approach to solving this problem and its game-changing benefits, including a new standard in state-of-the-art (SOTA) performance on CPU as compared to existing solutions.