As AI model intelligence peaks, its reliance on complex, human-curated data is only deepening.
They started with microtasks such as transcribing audio files, marking tick boxes, translating language and labelling objects in images. Now, data annotators are correcting software code, checking financial statements and analysing diagnostic reports, as the training needs of artificial intelligence models become more complex.
Data annotation, or simply data labelling, is the most crucial and foundational step for building high-quality datasets to train AI…
