AI Explained
Artificial intelligence in plain English.
What is explainable AI, and why is it so hard to explain AI decisions?
Explainable AI helps people understand AI-assisted decisions, but complex models rarely give simple reasons. Here is what useful explanations should…
What is edge AI, and why run AI on a device instead of in the cloud?
Edge AI runs models on phones, laptops and sensors. Learn why local AI can help with speed, privacy and offline…
What is open source AI, and is it really open?
Open source AI is not one simple label. Learn how weights, code, data and licences decide what is genuinely open…
What is synthetic data, and why do AI companies use it?
Synthetic data is artificially generated data that mimics real data. AI companies use it for scale, privacy and edge cases,…
What is model drift, and why can AI behaviour change over time?
Model drift explains why AI behaviour can change over time, and how to monitor important AI workflows before reliability slips.
What is AI evaluation, and how do people test whether a model is safe to use?
AI evaluation tests how a model actually behaves across accuracy, safety, bias and robustness. Here is why it matters and…
What is an AI benchmark, and why should you be sceptical of scores?
AI benchmark scores look impressive, but do they reflect real-world performance? Here is what benchmarks actually test and why to…
What is fine tuning, and when does it actually help?
Fine tuning adjusts a model's behaviour from the inside. Here is what it does, how it differs from prompting and…
What is machine learning, in plain English?
Machine learning is the method behind most modern AI. Here is what it actually is, how it works, and why…
What is training data, and why does it shape every AI answer?
Training data is what every AI model learns from. It shapes what they know, where they excel, where they go…