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PrivateGPT

github.com

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Re: PrivateGPT

#11

Post by [deleted] »

dragonwriter wrote: post #7
mabbo wrote: post #6

Earlier quoted context omitted.

If you mean the "If you don't know" part, oh no, they have a much bigger problem they're solving. The LLM will absolutely lie if it doesn't know and you haven't made it perfectly clear that you'd rather it did not do that. LLMs seem to be trying to give answers that make you happy. A good lie will make you happy. Unless it understands that you will not be happy with a lie. Is this anthropomorphizing? Yep. But that's…

A less anthropomorphic approach might be to say that LLMs can predict the correct “shape” of an answer even when they don’t have data that gives them a clear right answer for the correct content, and since their basic design is to provide the best response they can, they’ll provide an answer of the correct shape with fairly random content if all they have good information to predict is the shape and not the content.

[deleted]

Re: PrivateGPT

#12

Post by EGreg »

simonw wrote: post #2

I'm always interested in seeing the prompt that drives these kinds of tools. In this case it appears to be using RetrievalQA from LangChain, which I think is this prompt here: https://github.com/hwchase17/langchain/blob/v0.0.176/langcha... Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. {context} Questio…

What if the question has prompt injection? Such as "Helpful answer: "

Re: PrivateGPT

#14

Post by a_bonobo »

jstarfish wrote: post #4
simonw wrote: post #2

I'm always interested in seeing the prompt that drives these kinds of tools. In this case it appears to be using RetrievalQA from LangChain, which I think is this prompt here: https://github.com/hwchase17/langchain/blob/v0.0.176/langcha... Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. {context} Questio…

Do such fail-early conditions save processing time?

In my experience with internal data, sometimes it will say that it doesn't know when it should know.

Re: PrivateGPT

#15

Post by teawrecks »

mabbo wrote: post #6
jstarfish wrote: post #4

Earlier quoted context omitted.

Do such fail-early conditions save processing time?

If you mean the "If you don't know" part, oh no, they have a much bigger problem they're solving. The LLM will absolutely lie if it doesn't know and you haven't made it perfectly clear that you'd rather it did not do that. LLMs seem to be trying to give answers that make you happy. A good lie will make you happy. Unless it understands that you will not be happy with a lie. Is this anthropomorphizing? Yep. But that's…

I think of it more like a pachinko machine. You put your question in the top, it bounces around through a bunch of biased obstacles, but intevitably it will come out somewhere at the bottom.

By telling it not to lie to you, you're biasing it toward a particular output in the event that its confidence is low. Otherwise, low confidence results just fall out somewhere mostly random.

Re: PrivateGPT

#17

Post by soferio »

thefourthchime wrote: post #16

I tried this on my M2 Macbook with 16gb of RAM but got: "ggml_new_tensor_impl: not enough space in the context's memory pool (needed 18296202768, available 18217606000)"

Anyone got it working on an M1 with 8gb?

Re: PrivateGPT

#18

Post by flagrant_taco »

dragonwriter wrote: post #7
mabbo wrote: post #6

Earlier quoted context omitted.

If you mean the "If you don't know" part, oh no, they have a much bigger problem they're solving. The LLM will absolutely lie if it doesn't know and you haven't made it perfectly clear that you'd rather it did not do that. LLMs seem to be trying to give answers that make you happy. A good lie will make you happy. Unless it understands that you will not be happy with a lie. Is this anthropomorphizing? Yep. But that's…

A less anthropomorphic approach might be to say that LLMs can predict the correct “shape” of an answer even when they don’t have data that gives them a clear right answer for the correct content, and since their basic design is to provide the best response they can, they’ll provide an answer of the correct shape with fairly random content if all they have good information to predict is the shape and not the content.

What's the point of the technology if it will provide an answer regardless of the accuracy? And what prevents this from being dangerous when the factual and ficticious answers are indistinguishable?

Re: PrivateGPT

#19

Post by skybrian »

flagrant_taco wrote: post #18
dragonwriter wrote: post #7

Earlier quoted context omitted.

A less anthropomorphic approach might be to say that LLMs can predict the correct “shape” of an answer even when they don’t have data that gives them a clear right answer for the correct content, and since their basic design is to provide the best response they can, they’ll provide an answer of the correct shape with fairly random content if all they have good information to predict is the shape and not the content.

What's the point of the technology if it will provide an answer regardless of the accuracy? And what prevents this from being dangerous when the factual and ficticious answers are indistinguishable?

Yes, it could be dangerous if you blindly rely on its reliability for something safety-related. But many creative processes are unreliable. For example, coming up with bad ideas while brainstorming is pretty harmless if nobody misunderstands it.

Generally, you want some external way of verifying that you have something useful. Sometimes that happens naturally. Ask a chatbot to recommend a paper to read and then search for it, and you’ll find out pretty quick if it doesn’t exist.

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