Nearly every annotation operation now uses models to assist human annotators, and the productivity gains are real. They are also easier to overstate than to sustain, because the mechanisms that make assisted labeling fast are the same ones that can quietly degrade quality. This guide covers how assisted labeling actually works, where the gains come […]

US companies building AI have generally treated European regulation as somebody else's problem, and that assumption is becoming expensive. The EU AI Act reaches providers whose systems are placed on the EU market or whose outputs are used there, which captures a large share of US software companies whether or not they have European operations. […]

Most organisations deploying AI evaluate it in some form, usually informally, usually by the team that built it, and usually most intensively just before launch. That arrangement produces predictable outcomes: evaluation is optimistic, it stops after release, and nobody can answer the question a board or regulator eventually asks, which is how you know your […]

Most organisations building AI have two groups involved with data and a gap between them. Data engineering owns the pipelines, warehouses, and infrastructure. The AI or data science team owns models. Between the two sits a set of responsibilities that neither fully owns: deciding what data a model needs, getting it into a usable state, […]

Most organisations sitting on years of proprietary data eventually ask the same question: can we use it to make a model that understands our business? The answer is often yes, and the path there is more constrained than the framing suggests. Fine-tuning is frequently the wrong tool for what teams actually want, and where it […]

Computer vision arrived in factories and fields later than in consumer applications, and it is now spreading quickly: defect detection on production lines, equipment condition monitoring, crop health assessment, livestock monitoring, and yield estimation. These deployments share a set of data problems that differ meaningfully from the ones consumer computer vision solved, and teams that […]