Articles
AI is moving fast, and so are the questions around privacy, security, cost, infrastructure, regulation and control. Here we examine the facts behind the decisions organisations face when they adopt AI. Each article takes one specific question and answers it with dated facts, named organisations, primary documents and reputable sources. No hype. No vague claims. Just evidence, context and practical analysis, so you can see what is changing, what it means for your organisation, and where AI belongs.
7 min read
The regulator's own wording on when a model may be treated as anonymous, the two likelihoods that must both be insignificant, and why "the model contains no names" is not an argument anybody should make.
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6 min read
How to read a throughput figure, why it is not response time, what concurrency does to it, and the language effect that a Romanian buyer should ask about before accepting an English benchmark.
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6 min read
Where the memory goes, why context length multiplies it, what quantisation buys and costs, and the question that replaces "how fast is the GPU?" when you are buying for local inference.
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6 min read
Training against inference, the two phases inside a single request, the variables that decide how fast it feels, and the eight-item list that turns "fast AI" into something a buyer can verify.
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