[Medical] AI Engineering
Understanding the risk posed by AGI is like standing at the foot of an accelerating train track; you can debate the exact speed or the final destination, but the wisdom lies in recognizing the immediate need to step off the tracks before the exponential approach leaves you with no remaining options. We must achieve clarity … Read more
Insights From Nyari Lake: Some local snail captures I was clearing the lake outlet/hatchery yesterday evening (23/11/2025) when I saw these snails (image below) in large numbers in the fish hatchery that I maintain at the outlet point. I keep this hatchery clear of leaves and 3 to 4 times a year have to dredge … Read more
There’s a growing fascination with off-grid communication. Whether for backcountry adventures, emergency preparedness, or simply reclaiming a piece of digital sovereignty, people are exploring ways to stay connected without relying on traditional infrastructure. This journey often leads to the world of DIY radio projects and decentralized mesh networks, promising long-range messaging powered by little more … Read more
For many years, I have had the privilege of training aspiring Machine Learning and Deep Learning students, helping them transition from coders to effective AI practitioners. To date, I have trained more than 600 AI practitioners, with student backgrounds ranging impressively from medical doctors to high school graduates.How do we achieve such success with such … Read more
While being highly focused on developing the Kenyan LoRa network I’m looking at all modes of establishing communications in a disaster situation. Here is one of them that I’m looking at setting up. It is an amateur radio data transceiver hotspot, capable of handling all digital amateur radio communication modes, including email, SMS, and various … Read more
As Chair of the Amateur Radio Emergency Network of the Radio Society of Kenya (RSK-AMRAN), I am spearheading the development of a long-range (LoRa) mesh network across Kenya. This project, documented on this website, focuses on using Meshcore technology over Meshtastic to build this critical infrastructure. This website serves as a resource for tracking the network’s construction, uses, and … Read more
AI in Diagnostic Imaging A prominent use case for AI in medicine is in diagnostic imaging, particularly in radiology and pathology.1 AI-powered tools can analyze medical images, such as X-rays, CT scans, MRIs, and pathology slides, to assist healthcare professionals in detecting abnormalities and making more accurate, faster diagnoses.2 How it Works: Diabetic Retinopathy Screening … Read more
Retrieval-Augmented Generation (RAG) is a powerful technique that enhances a model’s ability to generate responses by dynamically retrieving relevant information from external memory sources and incorporating it into the model’s context. This approach addresses key limitations of large language models (LLMs) and large multimodal models (LMMs), often referred to as “foundation models”. Here is a … Read more
As an AI Engineer I’ve found that Chip Huyen’s book, “AI Engineering: Building Applications with Foundation Models,” serves as a comprehensive and practical guide for professionals seeking to design and deploy generative AI applications in production. It feels to me like it provides timeless foundational knowledge for building scalable AI products, rather than focusing on … Read more
Mechanistic interpretability (Mech Interp) is a fascinating and rapidly evolving field within AI research that aims to reverse-engineer neural networks to understand their internal algorithms and mechanisms. Chris Olah, one of the pioneers of this field, likens it to neurobiology, as AI models are not programmed in the traditional sense but rather “grown” through training, … Read more