Rust for Embedded Software: A 2023 Update

Rust for Embedded Software: A 2023 Update


In the fast-paced world of technology, three years can bring significant advancements. Back in 2020, I wrote a blog post about Rust for embedded software development, captivated by its memory safety features and promises for the future. Now, in 2023, I am even more thrilled about Rust’s potential in the embedded world. This update aims to provide you with a comprehensive primer to help you decide if Rust is the right choice for your embedded projects.

The Power of Memory Safety

At its core, Rust’s appeal lies in its exceptional memory safety features. By eliminating an entire class of bugs at compile time, Rust shortens the developer feedback loop, resulting in more reliable code. Memory safety bugs often lead to Undefined Behavior (UB), causing unexpected behavior and making debugging a nightmare, especially in resource-restricted embedded systems. Thanks to Rust’s robust guarantees, these issues are becoming a thing of the past, setting a solid foundation for the language.

A Toolbox for Embedded Developers

Aside from memory safety, Rust offers a powerful set of tools that make embedded development a breeze. Dependency management and cross-compilation are seamless, allowing you to pull in external libraries and run firmware on multiple platforms effortlessly. Moreover, the probe-rs project enhances the development experience, streamlining the process of developing, running, and debugging Rust for embedded devices. These tools make adding new features and troubleshooting existing ones a much smoother experience.

Typically, Rust: Rust advocates writing code not for machines but for future developers and colleagues. Readable, maintainable, and robust code is achieved by embedding meaning into the codebase. Rust’s expressive type system facilitates “Semantic Typing,” enabling the compiler to catch inconsistencies and ensure code makes sense. As a result, onboarding new developers, refactoring, and debugging become significantly less time-consuming and more efficient.

AI in South Africa: Special Dilemmas and Usual Risks

AI in South Africa


When discussing artificial intelligence (AI), most people envision a futuristic world. However, AI is already a part of our lives, with applications ranging from voice-operated personal assistants to self-driving cars and advanced medical diagnoses. While AI offers numerous benefits, it also poses ethical and moral questions that demand careful consideration. This blog explores the universal ethical risks associated with AI, comparing its impact in wealthier countries with its unique challenges in South Africa and other global southern nations. Understanding these ethical dilemmas is crucial for policymakers and organizations to develop appropriate risk management strategies.

Universal Ethical Risk Themes

  1. Accountability: One major concern is the ambiguity regarding who should be held accountable for the outcomes produced by AI models and systems.
  2. Bias: Shortcomings in algorithms or biased data can lead to AI perpetuating societal biases and inequalities.
  3. Transparency: AI systems often operate as “black boxes,” making it challenging for developers and users to comprehend or validate their outputs.
  4. Autonomy: As AI advances, there is a potential risk of humans losing control over decision-making processes.
  5. Socio-economic Risks: AI’s widespread implementation may lead to job displacement and further exacerbate existing inequalities in society.
  6. Maleficence: There is a fear that AI could be exploited by criminals, terrorists, and repressive state entities for malicious purposes.