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> When we tell AI that we're relying heavily on its answers, it "doubles down" to provide us with more precise, thoughtful, and thorough responses. The AI isn't actually feeling the pressure If it quacks like a duck...
> When we tell AI that we're relying heavily on its answers, it "doubles down" to provide us with more precise, thoughtful, and thorough responses. The AI isn't actually feeling the pressure If it quacks like a duck...
> When we tell AI that we're relying heavily on its answers, it "doubles down" to provide us with more precise, thoughtful, and thorough responses. The AI isn't actually feeling the pressure If it quacks like a duck...
There is an alternative explanation - both AI and humans piggyback on language. Language patterns encode and express all the emotions, and they have been created by evolution. We are, much like LLMs, contextual language generators Language is our repository for both intelligence and emotion, it has its own evolution and replicates faster than biology. I don't pin AI abilities to the models, but to the datasets they a…
1) [link redacted]
The people who design and control the model should have this type of stuff baked in for us IMO.
I have to push back really hard against my proclivity to humanize it, to the point where I probably don't use it as much as I should, just because I don't want to deal with the psychic stress of reminding myself that it's not a living entity.
Am I the only one who feels bad for asking ChatGPT a "dumb" question that I know I should know, or not saying thank you when it gives me an answer? No? I'm just a weirdo? Okay. I have to push back really hard against my proclivity to humanize it, to the point where I probably don't use it as much as I should, just because I don't want to deal with the psychic stress of reminding myself that it's not a living entity.
Have you tried asking ChatGPT?
Jokes aside, I feel it sometimes as well. I wonder if it's more because I say "thank you" more as a reflex than an actual feeling of gratitude for most of my human interactions.
Am I the only one who feels bad for asking ChatGPT a "dumb" question that I know I should know, or not saying thank you when it gives me an answer? No? I'm just a weirdo? Okay. I have to push back really hard against my proclivity to humanize it, to the point where I probably don't use it as much as I should, just because I don't want to deal with the psychic stress of reminding myself that it's not a living entity.
Based on ChatGPT's answers, OpenAI think you should be saying thanks to it, because it helps you have a more natural conversation, which encourages you as the user to send more natural/productive prompts when asking real questions.
As for asking it dumb questions, how often do you use Google as a spellcheck? I wouldn't consider this any different.
Earlier quoted context omitted.
There is an alternative explanation - both AI and humans piggyback on language. Language patterns encode and express all the emotions, and they have been created by evolution. We are, much like LLMs, contextual language generators Language is our repository for both intelligence and emotion, it has its own evolution and replicates faster than biology. I don't pin AI abilities to the models, but to the datasets they a…
I had a similar realization recently. I plugged my blog post(1) two days ago and I am doing it again now so I will try and refrain for a while, but it really sticks with me: after trying to create a chat bot for a while, I feel like I have gained significant insights into how humans work. It all seems so simple now! It's a weird and awesome feeling! 1) [link redacted]
I think before RAG we need to do more legwork with the LLM on the raw text. Here is one of my blog posts that is related:
https://mindmachina.wixsite.com/ai-blog/post/the-promise-of-...
The idea is to create chain-of-thought annotations from your raw texts, that would improve the embedding and retrieval process by making implicit things explicit.
For example "the last letter of this message" would not embed similar to "e", but if it was annotated with CoT, it would work.
If LLMs are showing “better” performance when there are tokens that humans read as emotionally salient -
Then the underlying text it’s trained on shows humans give better answers when emotionally salient context is provided.
LLMs predict words. Any semantic validity is a side effect of enough training data reinforcing the close correlation of those tokens.
That is why proof of concept LLM tools are mind blowing and production tools are semantic time bombs.
Am I the only one who feels bad for asking ChatGPT a "dumb" question that I know I should know, or not saying thank you when it gives me an answer? No? I'm just a weirdo? Okay. I have to push back really hard against my proclivity to humanize it, to the point where I probably don't use it as much as I should, just because I don't want to deal with the psychic stress of reminding myself that it's not a living entity.