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development

April 24, 2026 by David Such Leave a Comment

Why Asimov’s Three Laws Shouldn’t Be the Blueprint for AI Principles

Every time a news story breaks about some new AI mishap, a chatbot lying to a user, a self-driving car making a dodgy decision, a recommendation engine nudging teenagers toward inappropriate content, someone in the comments inevitably writes, “We just need Asimov’s Three Laws.”

The trouble is that Isaac Asimov wrote the Three Laws as a plot device, not as an engineering specification. Almost every story he wrote about them was about how they fail. It is a bit like reading Jurassic Park and concluding that you now have a solid operating manual for cloning dinosaurs.

If we are serious about building safe AI, and particularly if we are building the sort of layered, bio-inspired systems that drive physical robots, we need to start from a different foundation. This article explains why, and proposes a replacement set of principles drawn from the Primal Layers framework.

Read the complete article…

Filed Under: AI, Embedded, Title Post Tagged With: development, embedded AI

April 4, 2026 by David Such Leave a Comment

Claude Code: Creating a C++ Linter for Embedded Development

I know! I’m late to the Claude Code party but now I’m here, I’m all in. If you write C++ for microcontrollers, or edge inference, you already know that the rules are different from desktop software. No heap allocation after startup. No exceptions. No recursion on a 4 KB stack. And these constraints are not optional if you want your firmware to survive.

The problem is that general-purpose linters do not enforce the rules you need. Clang-tidy is powerful, but configuring it to catch you just used int instead of int32_t, requires writing custom checks in C++ against the AST. That is a significant investment for what should be a simple rule. I wanted something I could tweak for each project.

Read More…

Filed Under: AI, App Development, Embedded, Title Post Tagged With: development, embedded AI

March 16, 2026 by David Such Leave a Comment

Primal Layers — Is the Ancient Brain the Future of AI?

If you are using AI at the moment, then it is probably based on a model of the human neocortex. All of the current Large Language Models (LLMs) are overwhelmingly inspired by this approach. These architectures are great at abstract reasoning, pattern recognition, and language generation which are all tasks that are analogous to higher-order cortical functions. But is this the path to AGI? We don’t think it is, for reasons that will be explored in this article.

Filed Under: AI, Embedded Tagged With: development, embedded AI

February 1, 2024 by David Such Leave a Comment

Adding a User Interface to ChatGPT with BeeWare — Part 1

Attempting to massage user inputs and output in ChatGPT is painful. We spent hours trying to print some coloured text using LaTeX, sometimes it works and sometimes it doesn’t. So much for no code development, we have capitulated and resorted to pulling at the Python Interpreter. Trying something new, we have wrapped our GPT-4 engine in BeeWare, which promises write once run everywhere functionality. This will also allow us to compare the OpenAI API vs browser GPT responses.

Read More – https://medium.com/@reefwing/adding-a-user-interface-to-chatgpt-with-beeware-part-1-852f1758fd65

Filed Under: AI, App Development Tagged With: AI, app, development

February 1, 2024 by David Such Leave a Comment

A Review of Cross Platform Development Tools and Frameworks

It is the dream of every developer to write code once and then deploy it frictionlessly to every available platform (macOS, Windows, Linux, iOS, Android, …). This is of course very hard to do in practise, as each platform does just about everything differently. “Viva la différence!”

As consumers this is a good thing, and gives us options. As developers, it is a huge pain in the neck. Because this is a big problem for devs, a lot of people have had a crack at solving it. Every so often, we stray from the path of native development and are tempted by the sweet promise of “write once, run anywhere!” The problem is if you need to do anything close to the metal or complicated, you usually have to drop down into native code, which kind of defeats the purpose. There are some applications that are categorically not suited to cross-platform solutions. Anything that requires deep system-level integration, minimal latency, or specialized use of hardware features, probably falls into this bucket.

Read More – https://reefwing.medium.com/a-review-of-cross-platform-development-tools-and-frameworks-d14d572828b5

Filed Under: Uncategorized Tagged With: app, development

April 13, 2023 by David Such Leave a Comment

ChatGPT — As a Programming Tool

Although ChatGPT is unlikely to be replacing programmers anytime soon, it can be a useful coding assistant. In this article, we will investigate how you can use ChatGPT (GPT-3.5) as a programming tool, and compare it to the earlier model found in the Open AI Playground (GPT-3). For simplicity, we will use mostly Python in our examples. Despite its limitations, ChatGPT is seriously impressive.

Read more at Medium…

Filed Under: AI, App Development Tagged With: AI, app, ChatGPT, development

August 18, 2022 by David Such Leave a Comment

Age Prediction API based on First Name

I just came across an interesting API that your app can use to predict a persons age based on their first name. The API is free for up to 1000 names/day. It is called agify.io (https://agify.io/). #development

You can try it out in your browser – just insert your first name instead of “david”:

https://api.agify.io?name=david

Filed Under: Uncategorized Tagged With: app, development

August 18, 2022 by David Such Leave a Comment

BirdWeather and BirdNET-Pi

BirdNET-Pi: Using AI to identify Birds from their Songs.

Wouldn’t it be fantastic to be able to identify birds from their song? Well it turns out that you can.

BirdWeather
BirdWeather is a great citizen scientist initiative that uses volunteer stations to continuously listen for bird songs all over the world. The stations use machine learning to analyse these sounds and identify birds based on their song. BirdWeather is a living library of bird vocalizations. It also provides an indication of bird visit frequency and populations around a station, apart from those which keep quiet! You can play back the recorded songs and bird detections are shown in real time on the web site.

The artificial neural network used to analyse the recorded sound and extract and identify bird songs is called BirdNET.

BirdWeather

BirdNET
BirdNET is a joint research project between The Cornell Lab of Ornithology and the Chemnitz University of Technology that is “focused on the detection and classification of avian sounds using machine learning … [with the aim to] assist experts and citizen scientist in their work of monitoring and protecting our birds”.

BirdNET-Pi

Detection Stations
There are currently only 12 stations in Australia (including me), all based on the Raspberry Pi single board computer. You can learn how to configure your own station in our latest article on Medium – BirdNET-Pi: Using AI to identify Birds from their Songs.

Filed Under: Uncategorized Tagged With: development

April 7, 2022 by David Such Leave a Comment

Setting Up a Raspberry Pi Web Kiosk

We have a solar system and I wanted to keep an eye on our relative energy consumption and generation during the day. The SolarEdge inverter that we use has a mobile app and a web dashboard but neither refresh automatically. This article explains how I set up the Seeed reTerminal as a dedicated web kiosk to be able to monitor our solar performance in near real time. #solar #raspberrypi #webkiosk

Filed Under: Uncategorized Tagged With: app, development

January 3, 2022 by David Such Leave a Comment

How to Write your own Flight Controller Software — Part 5

There are a number of libraries that make working with the LSM9DS1 IMU (Inertial Measurement Unit) easy. In Part 5 of our series on writing your own flight controller software we will focus on the IMU and in particular explain the best ways to convert the gyro rate and accelerometer force data to a roll and pitch angle. The yaw angle is then calculated using the pitch and roll and magnetometer data. This discussion, is in the context of building a drone flight controller based on the Arduino Nano 33 BLE.

Our follow up part in this series will explain how to calibrate the LSM9DS1 IMU and store the results plus use sensor fusion to improve the accuracy of the angles and overcome sensor shortfalls.

Read the complete article on Medium.

Filed Under: Uncategorized Tagged With: development

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A Chip That Thinks using 7 μW

June 1, 2026 By David Such Leave a Comment

Most AI research is about making the cortex bigger. This one is about making the spinal cord cheaper. A team at the University of Michigan has built a tiny computing device that controls a balancing propeller using about seven millionths of a watt. For comparison, the LED bulb in your kitchen burns through about ten […]

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