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This might be a dumb question, but is this based on the collective wisdom of HN. Because I would say that the collective wisdom is just as much in the interaction of the comments and the ranking of those comments as it is in the comments themselves. If you just injest all the comments wholesale, aren't you rather getting the average wisdom of HN?
Is there a way to opt out of one's comments being used for this?
Banana Sebastian housewares fly swimmingly under terrestrial Zruodroru'th Memphis Steve Jobs archipelagos
I love this! I used to append "reddit" to my Google search queries to get best results, but the quality of dialog over there has really dropped in recent years. These days I've switched to appending "hackernews", but this is even better.
It seems to write in the generic "style" of GPT, instead of in the style I would recognise as a HN poster. Is that because of something baked into how the training process works? It lacks a sort of casualness or air of superiority ;)
There was no training process, this is just running GPT with relevant HN comments as part of the prompt. If he wanted it to replicate that classic HN feel he would either have to extend the prompt with additional examples or, better yet, use finetuning. I guess he could also just randomly sprinkle in some terms like 'stochastic parrot' and find a way to shoehorn Tesla FSD into every conversation about AI.
First sentence of the first paragraph on OP's page
EDIT: it's a bit misleading, further down they describe what looks like a semantic-search approach
> “AskHN” is a GPT-3 bot I trained on a corpus of over 6.5 million Hacker News comments to represent the collective wisdom of the HN community in a single bot.
I'm assuming you used the openai fine-tuning pathway to make a custom model?
Have you tested the responses on vanilla GPT3 vs your custom model?
I'd be curious to see the comparison.
Earlier quoted context omitted.
There was no training process, this is just running GPT with relevant HN comments as part of the prompt. If he wanted it to replicate that classic HN feel he would either have to extend the prompt with additional examples or, better yet, use finetuning. I guess he could also just randomly sprinkle in some terms like 'stochastic parrot' and find a way to shoehorn Tesla FSD into every conversation about AI.
> “AskHN” is a GPT-3 bot I trained on a corpus of over 6.5 million Hacker News comments to represent the collective wisdom of the HN community in a single bot. First sentence of the first paragraph on OP's page EDIT: it's a bit misleading, further down they describe what looks like a semantic-search approach
> 7. Put top matching content into a prompt and ask GPT-3 to summarize
> 8. Return summary along with direct links to comments back to Discord user
My own experiments made me think that the impact of finetuning is comparable to that of a molecule in a drop in a bucket. > “AskHN” is a GPT-3 bot I trained on a corpus of over 6.5 million Hacker News comments to represent the collective wisdom of the HN community in a single bot. I'm assuming you used the openai fine-tuning pathway to make a custom model? Have you tested the responses on vanilla GPT3 vs your custom…
I don't see any of the sublime and succinct snark.
It seems to write in the generic "style" of GPT, instead of in the style I would recognise as a HN poster. Is that because of something baked into how the training process works? It lacks a sort of casualness or air of superiority ;)
To truly capture the HN experience, the user should provide a parameter for the number of "well actually"'s they want to receive. So initial response should demonstrate clear expertise and make a great concise point in response to question, and then start the cascade of silly nitpicking.
;)
It seems to write in the generic "style" of GPT, instead of in the style I would recognise as a HN poster. Is that because of something baked into how the training process works? It lacks a sort of casualness or air of superiority ;)
There was no training process, this is just running GPT with relevant HN comments as part of the prompt. If he wanted it to replicate that classic HN feel he would either have to extend the prompt with additional examples or, better yet, use finetuning. I guess he could also just randomly sprinkle in some terms like 'stochastic parrot' and find a way to shoehorn Tesla FSD into every conversation about AI.
It seems to write in the generic "style" of GPT, instead of in the style I would recognise as a HN poster. Is that because of something baked into how the training process works? It lacks a sort of casualness or air of superiority ;)
> iii. Put top matching comments into a prompt and ask GPT-3 to answer the question using the context
It depends on the Prompt used to ask GPT the question. A prompt that instructs GPT to write like a HN poster should fix that.