Explainers & Fundamentals
Plain-language primers on how AI actually works, so the rest of it makes sense.
6 articles
What AI Can Actually Do for an African Business Today
AI is a capability multiplier, not a decision-maker. A grounded look at the specific tasks it handles well for African SMEs today, the myths it cannot deliver, and a simple test before you adopt.
AI Hallucinations Explained: Why Confident AI Is Often Wrong
AI does not tell the truth - it predicts plausible words, and it sounds equally confident whether it is right or making things up. Here is why hallucinations happen and how to manage them with RAG, human review and verification.
The State of AI in Africa 2026: A Practical Map
Africa's AI economy in 2026 is real, funded and still small enough to shape. A grounded map of the hubs, the money, the obstacles nobody should sugarcoat, and where builders actually win.
Open vs Closed AI Models: Why the Choice Matters for the Global South
Open-weight models like Llama, Mistral and DeepSeek have nearly closed the capability gap. For the Global South, the choice between open and closed AI is not about price - it is about control, currency, privacy and sovereignty.
Your Data Is the Foundation: Why AI Fails Without It
AI extracts intelligence from your data - it cannot create it. Why data readiness must come before any AI purchase, why African SMEs face this harder, and the practical steps to build a foundation that works.
One Bad Request Killed Your Whole vLLM Server: AsyncEngineDeadError Explained
AsyncEngineDeadError means one request crashed vLLM's shared background loop and took every other request down with it. Here is the architecture behind it and the mitigations that actually contain it.