Will we have a popular LLM fine-tuned on people's personal texts by June 1, 2024?
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Jun 1
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chance

Popular for this market= 10mil+ users

Personal texts = dms, private chats, WhatsApp chats, discord dms, lw dms, etc.

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bought Ṁ320 NO

@metacontrarian Github Copilot only has 1.3 million users, 10 million people seems steep in comparison.

Fine-tuning on personal text is still very cool and doable, but I think the user adoption requirement sinks this.

if you wanted to do this right now, how would you do that?

How does this resolve?

Utility-wise, this has been true for some time already, as there's ample examples of davinci/turbo utilizing private data as a knowledge base by means of embeddings, often using libraries like GPT-index and langchain that fit this exact purpose very well.

If the exact criteria is fine-tuning, then that has also happened since OpenAI has exposed a fine-tuning API for their non-chat models for a while, which i would argue in the vast majority of cases is being used for private data.

If the market demands a specific product connecting to APIs for Slack/Whatsapp/Discord/Emails etc., AND demands fine-tuning, then i think the probability is close to 0% considering the ineffectiveness of that approach compared to context-length increases combined with embeddings.

@minosu Re: Para 1 -> "fine-tuned on people's personal texts"

Re: Para 2 -> It has to be fine tuned on people's personal data and the application doing that is popular - which i dont think has happened.

bought Ṁ50 of NO

@firstuserhere In that case, that's a no for me. :)

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