std-training VS askai

It's well established that interrupts are a tough concept to grasp for the embedded beginner. Add to that when doing it in Rust the complexity of dealing with mutable static variables. This is because working with shared variables and interrupts is inherently unsafe if proper measures are not taken. When looking at how to do interrupts using the esp-idf-hal I first resorted to the Embedded Rust on Espressif book. Interrupts are covered under the Advanced Workshop in section 4.3, and to be honest, I was taken aback a little at what could be an additional level of complexity for a beginner. Without too much detail, this is because the book resorts to using lower-level implementations. For those interested, by that, I mean FFI interfaces to FreeRTOS which I will be creating a separate post about later.

Relative to the esp-idf-hal , as far as material goes, there exists training material that is open sourced by Ferrous systems. The training material takes a bit of a different approach where it starts with high-level IoT exercises followed by low-level control. Additionally, the training is based on the awesome Rust ESP board hardware.

Yes! The training developed with Ferrous Systems (https://esp-rs.github.io/std-training/) contains several examples, and you can find many community projects in https://github.com/esp-rs/awesome-esp-rust#projects

Good places to get started with std Rust on ESP include the Rust on ESP book, Embedded Rust on Espressif by Ferrous Systems. There's also the Awesome ESP Rust GitHub repository that contains a lot of useful material and project examples.

Embedded Rust on Espressif (Ferrous Systems training)

I must admit I've never used it for anything but tutorials yet (kids resulted in a lot of personal projects shelved), but Rust has an amazing and rapidly developing embedded ecosystem. A good starting point to get an impression of it might be training materials from Ferrous Systems 1, 2 (feel free to pay for the training itself if you feel like it's worth it for you of course). There is an embedded working group for Rust, Knurling project to improve tooling and even an attempt of Rust standard certified for safety-critical application.

AI and LLMs such as ChatGPT are amazing at what they do, but they suffer from the lack of "an opposable thumb", to use an analogy. This implies that as stand alone products, they can't really do much, if anything at all.

Prompt Engineering is the art of instructing an LLM such as ChatGPT to do what you want it to do, using nothing but natural language, logic, and reason. The process is probably easily within reach of 80% of the world's population, while less than 0.3% of the world's population knows how to code.

ChatGPT, launched in November 2022, quickly became a sensation, amassing over a million users within its first five days. This staggering adoption rate signifies more than mere curiosity; it reflects a genuine interest in AI's potential to revolutionize writing. Built on the GPT (Generative Pre-trained Transformer) architecture, ChatGPT learns from a vast corpus of online text, enabling it to generate human-like responses across a wide range of topics and styles.

If you are new to OpenAI, create your OpenAI account here. Once you’ve successfully created an account, go on to API key section by using the same credentials you used when creating your account. On the left panel of the screen, click on “API Keys” and then proceed to click on “Create new secret key”. This is shown below:

A friend of mine asked ChatGPT to suggest an open source low-code software development platform for AI solutions, and it suggested Magic. Magic is our flagship product, and when I describe what it does I tend to use a lot of words. Below is the identity definition of it.

We'll use several interesting technologies to achieve this: Strapi CMS to take care of the content management and backend, Astro which is a great new technology for quickly creating blazing fast frontend apps, and ChatGPT to provide the article summaries.

I was confused why https://chat.openai.com suddenly redirects to https://chatgpt.com which results in connection refused. Turns out chatgpt.com is in many blocklists (e.g. Pi-Hole) due to it being a potentially unsafe Domain before OpenAI acquiring it. So heads up if you use Pi-Hole / AdGuard etc.!