youssefabdelm
Joined 5 years ago
Joined 5 years ago
If they abstract all this away into one interface I won't know which model I'm getting. I prefer reliability.
For example the rhyming example brings to mind a feature where you give the model starting input and ending input and ask it to fill in.
Can not only imagine it being useful in that sense, but for ways at retroactively arriving at some answer, or solution or something. Like the causal chain that leads to a specific answer.
Another idea is to show all possible word variations, and then the middle is rewritten based on the chosen word.
It's not like "Oh their quality of life is exactly the same as in the US it's just cheaper! So it's totally fine for us to pay them peanuts! Right? Peanuts buy you a house there... I mean the house has no plumbing but it's a house!" No, their quality of life is absolute crap compared to first world countries (as someone from a third world country). And paying them like shit will only prolong their suffering.
The least the company could do is pay them fairly which means they can travel or live a better quality life.
GPT-4o will never offhand, unprompted and 'unprimed', suggest a rare but relevant book like Shinichi Nakazawa's "A Holistic Lemma of Science" but a base model Mixtral 8x22B or Llama 405B will. (That's how I found it).
It seems most of the RLHF'd models seem biased towards popularity over relevance when it comes to recall. They know about rare people like Tyler Volk... but they will never suggest them unless you prime them really heavily for them.
Your point on recommendations from humans I couldn't agree more with. Humans are the OG and undefeated recommendation system in my opinion.