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no matter what I put into it.
111–120 of 163 posts
"Error occurred processing text500"
no matter what I put into it.
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But how do you know if the LLMs agree, when all of them word the response differently For example LLM 1: Yes, it is true that fireworks were invented in China LLM 2: Fireworks were indeed invented in China
This is trivially achievable with function calling, assuming the model you use supports this (which most models do at this point). Define a function `reportFactual(isFactual: boolean)` and you will get standardized, machine-readable answers to do statistics with.
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Sample a bunch of LLMs with the same question, if they disagree much then they are unsure. You can even sample the same LLM with high enough temperature, text augmentations, different prompts or different demonstrations. When they are correct they say the same thing, but when they make mistakes, they make different ones. This only works for factual or reasoning tasks, but that's where it matters.
But how do you know if the LLMs agree, when all of them word the response differently For example LLM 1: Yes, it is true that fireworks were invented in China LLM 2: Fireworks were indeed invented in China
Not only is this an impressive use of LLMs, it's highly relevant to our social media of today, and I can imagine use cases for user-facing apps like giving context to a user comment (which may or may not be factual).
Are there API client libraries where I can see developer usage? That's likely how I would use a product like this.
Very impressive work for high school - I was making Lunar Lander in VB6 with MS Paint graphics at that age :) very cool to see work of this quality from a 16-year-old.
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Damn, what the MVP does right now, is check for already established facts. So basically, what we define as fact is something that has proof. For example, we stray away from political views as those are opinions, and stay with “facts”. As for disputed facts, we would also stay away from them unless they have a significantly larger backing than the other. The source currently is LLMs that are trained on huge amounts of…
Historic facts like why the Civil War began?
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Yea, thank you for your feedback!
> “…which has the potential to do as much harm as good.” I find this is one of the more difficult things for people to learn to fully integrate into their psyche. Many people never learn to truly care about this and everything it means. They go on forever primarily caring about what’s good for them personally.
I mean look at the world. Essentially everybody puts themselves first and it’s clear as day. Don’t trick yourself into being the sap doing things for the greater good.
And who cares if there’s equal potential for harm and good? The harm might be less than we imagine and the good might be better than we think it could be. “This might be bad” is a terrible reason to not do something. Nearly everything might be bad!
People are pretty resilient. They can generally deal with you being selfish.
How incredibly cool to see young people that are interested and capable of building things! I have a couple of rhetorical questions. How do you expect a language model to see through propaganda and other large-scale misinformation by power/money with a megaphone? How do you expect a computer program that can't reliably determine what letter a word starts with to determine objective truth? I appreciate that you have a…
Thank you! We are working on our own LLM that is based of a multitude of data, we also will double check or even triple check all the information through our DB and the internet. We are working to make it as reliable as possible.
But while enthusiasm is great, delusion is not. Since you're striving to be a founder and not a hobbyist, you have to be realistic about what you're trying to build.
What you're describing is fundamentally not possible to provide assurances on without some kind of legititmate AGI, which you lack the resources to build yourself.
Many better resourced companies are trying to provide grounded, factually accurate information, so it just seems like an area of effort far too broad to ever succeed in.
I would suggest a pivot into demonstrating legitimacy in a very narrow niche before attempting to be a genralist know-it-all. Providing fine-tuning as a service to a point of assured factual grounding is itself a hard enough open challenge in AI.
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> “…which has the potential to do as much harm as good.” I find this is one of the more difficult things for people to learn to fully integrate into their psyche. Many people never learn to truly care about this and everything it means. They go on forever primarily caring about what’s good for them personally.
Strong disagree. Put yourself first nearly 100% of the time. Nobody cares about you so don’t think others are doing anything but prioritizing themselves. I mean look at the world. Essentially everybody puts themselves first and it’s clear as day. Don’t trick yourself into being the sap doing things for the greater good. And who cares if there’s equal potential for harm and good? The harm might be less than we imagine…
This sort of hustle culture belief is definitely present in the world, especially among finance and us techie types, but there's tons of examples of people Not acting like this. Teachers don't do it for the pay, etc. There's a reason meaningful jobs tend to pay less, and its because so many people want to do useful helpful things that badly.
Anyways point is, that I want to explicitly condemn this type of thinking. Yeah don't let fear of doing the wrong thing paralyze you but also think through the consequences