4 ms·

Probably my ignorance talking, but I don't understand why there isn't a layer on top of an LLM that uses good old computer logic to keep track of and validate d

Probably my ignorance talking, but I don't understand why there isn't a layer on top of an LLM that uses good old computer logic to keep track of and validate data. I am baffled by the fact that when I ask ChatGPT to look up some stock data (for example) it spits out errors. How does it not have a built in ability to check its own output?

jamilton 3y ago
What do you mean by "check its own output"?
a-r-t 3y ago
Because if you had a logic layer capable of validating LLM's output, you wouldn't need the LLM.
- kendalf89 3y ago
  Even something as simple as censoring swear words would be in line with what openAI are trying to accomplish but they keep lobotomizing the model instead.
- ben_w 3y ago
  I think we still need an LLM to enable the system as a whole to understand vague and half-baked human input. I can easily ask an LLM to write be a function in a random programming language, then feed the output to a compiler, and pipe errors from the compiler back to the LLM. What doesn't work so well is typing "pong in java" into a bash shell. This isn't a perfect solution (not even for small projects), but it does demonstrate that automated validation can improve the output.
  - a-r-t 3y ago
    This is what ChatGPT's Code Interpreter does (writes code in Python and then runs it to check for errors). I'm not sure if it's enabled for everyone yet though.
- turmeric_root 3y ago
  c'mon just write a function that takes in text and tells you whether or not it's true, how hard could it be
tomr75 3y ago
people have built their own solutions to validate data like this won't be one size fits all due to various types of data - and if you could validate all types - why do you need the llm!
tayo42 3y ago
There is, I've seen it called react pattern. I'm pretty sure this is what chat gpts plug-ins feature is
BoorishBears 3y ago
It does have the ability, you haven't allowed it to. If you're completing the sentence "What is the current price of Apple?..." based on the internet as a training source, the most likely reply is not: "Well, let's think about how we'd go about this, I should do a search for AAPL, and then..." The most likely completion is: "The price of AAPL is $X" OpenAI had to "artificially" bias it to say "I can't answer that" or it'd happily tell you a million things like that. — On the other hand, give the LLM room to plan, it will plan. If you ask it "To answer x what do you need", it does better at answering x The most likely completion to "How would you tell me Apple's current price", is a logical step by step process. And that's how it gets a chance to check itself. I think people underestimate how much logic the model can do in a single pass, LLMs need to output things that we assume can be done with working memory
deleted 3y ago
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jamilton 3y ago

What do you mean by "check its own output"?

a-r-t 3y ago

Because if you had a logic layer capable of validating LLM's output, you wouldn't need the LLM.

kendalf89 3y ago
Even something as simple as censoring swear words would be in line with what openAI are trying to accomplish but they keep lobotomizing the model instead.
ben_w 3y ago
I think we still need an LLM to enable the system as a whole to understand vague and half-baked human input. I can easily ask an LLM to write be a function in a random programming language, then feed the output to a compiler, and pipe errors from the compiler back to the LLM. What doesn't work so well is typing "pong in java" into a bash shell. This isn't a perfect solution (not even for small projects), but it does demonstrate that automated validation can improve the output.
- a-r-t 3y ago
  This is what ChatGPT's Code Interpreter does (writes code in Python and then runs it to check for errors). I'm not sure if it's enabled for everyone yet though.
turmeric_root 3y ago
c'mon just write a function that takes in text and tells you whether or not it's true, how hard could it be

tomr75 3y ago

people have built their own solutions to validate data like this won't be one size fits all due to various types of data - and if you could validate all types - why do you need the llm!

tayo42 3y ago

There is, I've seen it called react pattern. I'm pretty sure this is what chat gpts plug-ins feature is

BoorishBears 3y ago

It does have the ability, you haven't allowed it to. If you're completing the sentence "What is the current price of Apple?..." based on the internet as a training source, the most likely reply is not: "Well, let's think about how we'd go about this, I should do a search for AAPL, and then..." The most likely completion is: "The price of AAPL is $X" OpenAI had to "artificially" bias it to say "I can't answer that" or it'd happily tell you a million things like that. — On the other hand, give the LLM room to plan, it will plan. If you ask it "To answer x what do you need", it does better at answering x The most likely completion to "How would you tell me Apple's current price", is a logical step by step process. And that's how it gets a chance to check itself. I think people underestimate how much logic the model can do in a single pass, LLMs need to output things that we assume can be done with working memory

deleted 3y ago

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