[stnmtn]

I agree, that language could be very improved. This is not a GPT-like LLM whose training corpus is HN comments, which I found to be an extremely interesting idea. Instead, it looks like it's finds relevant HN threads and tells GPT-3 (the existing model) to summarize them.

To be clear, I think this is still very cool, just misleading.

[agolio]

Soon we will see language style transfer vectors, akin to the image style transfer at the peak of the ML craze 5-10 years ago -- so you will be able to take a HN snark vector and apply it to regular text, you heard it here first ;)

[OkGoDoIt]

Joking aside, that does seem like it would be very useful. Kind of reminds me of the analogies that were common in initial semantic vector research. The whole “king - man + woman = queen” thing. Presumably that sort of vector arithmetic is still valid on these new LLM embeddings? Although it still would only be finding the closest vector embedding in your dataset, it wouldn’t be generating text guided by the target embedding vector. I wonder if that would be possible somehow?

[efreak]

Hmm. If you're willing to be stuck in time at 2016, there's https://zenodo.org/record/45901

Build a model off of that?