Why is human LLM annotation so expensive? [D]

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Scale AI and similar services charge a significant amount for annotation, making it unaffordable for many small teams that need to calibrate their models or fine-tune LLMs. Mechanical Turk is often used but suffers from poor quality, especially for tasks requiring domain-specific expertise. There seems to be no viable middle ground for this niche market.

• Small teams are struggling to find a cost-effective solution that matches the quality needed for model calibration and fine-tuning.
• The lack of suitable alternatives has led some teams to resort to manual annotation, which is both time-consuming and expensive.
• There’s an ongoing need for innovative solutions or partnerships between tech companies and human annotators to bridge this gap in the market.

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