An AI that gets it right starts with a human who has looked at everything first.
The reliability of an artificial intelligence system is determined before the model, in the annotation work that prepares its training data. From a real case at a deeptech client, this article shows how a stable dedicated team, organized in Antananarivo, annotated more than 160,000 medical images with an error rate below 1.2%, and what this rigor changes for the reliability of an AI product.
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