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Category Technologies

Mojo a new programming language for all AI developers

Modular, an AI infrastructure company, has unveiled a new programming language called Mojo for AI developers, combining full Python compatibility with advanced low-level programming features and the ability to harness GPUs and other AI accelerators. The language uses MLIR, the Multi-Level Intermediate Representation compiler framework, to provide low-level systems programming and advanced compilation features.

Mojo was designed to bridge the gap between research and production, leveraging Python syntax as well as systems programming and compile-time metaprogramming. Modular claims that Mojo is faster than C++, more hackable than Nvidia’s CUDA, and as safe as Rust. The language aims to offer an innovative programming model for machine learning accelerators while supporting general-purpose programming.

Mojo is intended to be a superset of Python and is fully compatible with existing Python programs. The language supports Python core features such as async/await, error handling, and variadics, with the exception of classes, which are not yet supported. The goals of the language include:

  • Full compatibility with the Python ecosystem
  • Predictable low-level performance and control
  • The ability to deploy code subsets to accelerators
  • Avoidance of ecosystem fragmentation

The Mojo standard library, compiler, and runtime are not yet available for local development. However, Modular has provided a hosted development environment called the Mojo Playground for developers to test and experiment with the language, requiring sign-up for access.

Mojo’s roadmap includes features such as tuple support, keyword arguments in functions, improved package management support, and standard library features like canonical arrays and dictionary types. Additionally, the language aims to provide full support for dynamic features in Python classes and C/C++ interoperability.

Mojo represents an exciting development for AI developers looking for a high-performance and flexible tool to accelerate their research and production, while leveraging the strengths of Python and advanced low-level programming features.

LANGUAGES TIME (S) * SPEEDUP VS PYTHON
PYTHON 3.10.9 1027 s 1x
PYPY 46.1 s 22x
SCALAR C++ 0.20 s 5000x
MOJO 🔥 0.03 s 35000x

*Algorithm – Mandelbrot | Instance – AWS r7iz.metal-16xl – Intel Xeon

DevOps Roadmap

DevOps Roadmap – A Guide to Your Journey

 

Introduction

DevOps is a software development approach that combines development and operations to improve the efficiency and effectiveness of the development process. It involves the use of various tools and techniques to automate the process of building, testing, and deploying software. In this post, we will discuss the DevOps roadmap, which outlines the key steps involved in implementing DevOps in your organization.


Step 1: Learn the Basics

The first step in the DevOps roadmap is to learn the basics of DevOps. This involves understanding the principles of DevOps, such as collaboration, automation, and continuous delivery. You should also learn about the various tools and technologies used in DevOps, such as Jenkins, Docker, and Kubernetes.


Step 2: Implement Continuous Integration

The second step in the DevOps roadmap is to implement continuous integration. This involves using tools like Jenkins to automate the process of building and testing software. Continuous integration helps to ensure that code changes are tested and integrated into the main codebase as quickly as possible.


Step 3: Implement Continuous Deployment

The third step in the DevOps roadmap is to implement continuous deployment. This involves using tools like Docker and Kubernetes to automate the process of deploying software to production. Continuous deployment helps to ensure that new features and updates are delivered to customers quickly and efficiently.


Step 4: Monitor and Improve

The fourth and final step in the DevOps roadmap is to monitor and improve. This involves using tools like Prometheus and Grafana to monitor the performance of your applications and infrastructure. You should also use feedback from customers and stakeholders to continuously improve your software development process.


 

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Thank you for reading our guide to the DevOps roadmap. We hope you find it helpful in your journey to implementing DevOps in your organization.


Cloud Engineer Roadmap

Cloud Engineer Roadmap

If you’re interested in becoming a Cloud Engineer, here’s a high-level roadmap to get you started:

  1. Develop foundational skills in computer science, networking, and operating systems.
  2. Gain experience with Linux and Windows operating systems and command-line tools.
  3. Learn the basics of cloud computing and the major cloud platforms (AWS, Azure, Google Cloud, etc.).
  4. Develop proficiency in at least one cloud platform by taking online courses, reading documentation, and experimenting with the platform.
  5. Obtain a certification in the cloud platform of your choice, such as AWS Certified Solutions Architect or Microsoft Certified Azure Solutions Architect.
  6. Learn programming and automation skills, including scripting, infrastructure-as-code, and configuration management tools.
  7. Gain experience with containerization technologies such as Docker and Kubernetes.
  8. Learn about cloud security and compliance best practices and obtain certifications such as Certified Cloud Security Professional (CCSP) or Certified Information Systems Security Professional (CISSP).
  9. Stay current with industry trends and technologies by attending conferences, participating in online communities, and reading industry publications.

Remember that this is just a high-level roadmap, and the specifics of your path to becoming a Cloud Engineer will depend on your background, interests, and goals. You may need to supplement this roadmap with additional coursework or certifications to achieve your desired level of expertise.

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