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by georgelyon 1207 days ago
Am I correct in understanding that this doesn't actually generate answers based on HN, but instead finds semantically-near comments and sends them verbatim to GPT to summarize? Seems like a good enough hack, though I'd love a detailed writeup of how to actually specialize an existing LLM with additional training data (like HN).
4 comments

Technically it does give a specific answer to the question, but it is based on the semantically similar comments (and the question).

The thing people don't realize is that right now there is a very large gap between the capabilities of a few models including OpenAI's most recent ones, and most of the other LLMs. So there are several options for actually training or fine-tuning with open models, but actually none of them have the language understanding and generation capabilities at the level of those new OpenAI models.

As far as I know.

The summary itself is still generated, but has all the context to do summarization in the prompt.

It's very difficult to otherwise finetune existing LLMs. GPT itself is closed-sourced, and doesn't allow for finetuning (except via an opaque API and with limited amounts of data). Other open models are either very difficult to load in memory and/or simply not as expressive as GPT

Agreed, I think the better approach is to do some custom tuning but that becomes cost prohibitive very quickly. Not really much different than Algolia with a minor GPT-3 integration but neat project regardless.
You can literally finetune these OpenAI models using their API. In this case it probably wasn't done because the author found it too much work and/or too expensive.
>the author found it too much work and/or too expensive.

Military budgets and manpower would make sock puppets interesting. https://www.theguardian.com/technology/2011/mar/17/us-spy-op...

Does anyone find it curious Edward Snowden is mute on the military's use of this technology?

How many people would be surprised to learn they are communicating with a program on websites like this?