Thanks for the kind words! I'm glad you found the information useful and realistic. Your feedback means a lot!
Recently, Meta's Llama and Apple's papers on LLM have been published, frequently mentioning human annotation or RLHF. My understanding is that fine-tuning and post-training data both require human annotation. Large companies might develop their own annotation tools, but they still need a significant number of crowd workers. Appen has crowd worker centres in Kenya and India, which may validate Appen's revenue growth.
https://ai.meta.com/research/publications/the-llama-3-herd-of-models/
https://machinelearning.apple.com/papers/apple_intelligence_foundation_language_models.pdf
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