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Thanks for the kind words! I'm glad you found the information...

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    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://hotcopper.com.au/data/attachments/6348/6348145-b429edd25b6fd5b0f2cdd8a56471718b.jpg


    https://machinelearning.apple.com/papers/apple_intelligence_foundation_language_models.pdf
    https://hotcopper.com.au/data/attachments/6348/6348150-f91ba6bcb94ad49b1d5638e1c0a5b8b1.jpg








 
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