41–50 of 163 posts
> I'm a high school student with a passion for tackling misinformation online. Inspired by the need for more reliable content verification tools, I decided to create Factful. It's an AI-powered web app I stopped reading here because LLMs do not deal in facts. LLMs are statistical models of the relationships between words. An LLM can regurgitate facts that appear in its training data, but they are incapable of disting…
Andrew, you and your friends should be proud. It's really encouraging to see people, especially in your generation, thinking seriously about the problem of misinformation. There are fundamental challenges you all will face in this idea: - most current LLMs are trained on large amounts of web data that itself contains facts, opinions, and misinformation. These things are treated equally, so I would expect the LLM to g…
Thinking out loud... I don't think these problems can be solved. If you are going to do it anyway, I would suggest: - Using a RAG architecture on top of a database of factual information. Wikipedia is probably your best bet. It is not 100% factual or correct either, but maybe as good as it gets. Scaling RAG to wikipedia size is not trivial, but I think it can be done. - Prompting the LLM to cite its sources so people…
Despite what criticisms you may receive, you put something into existence. You may not have gotten everything right but, it is admirable. Congratulations. At your age, many of your detractors probably didn’t do something so bold. Keep with it.
1. When a voyage starts and when a voyage ends are two different things. 2. As with most things in history nailing down when something actually happened is a range of values. You say he made it to China in 1271... but that's not fully accurate is it? It's a range of time in which he actually made it to China.
Hello! I built Fakts ( https://fakts.co/ ) a few years ago pre-LLMs as a college project. It attempts to highlight true, false, or inconclusive statements in a given article by checking them against a database of reputable sources. Feel free to send an email -- I'd be happy to share some of the learnings!
Hi there, that would be great! What is your email? Mine is andrew@factful.io
Btw, awesome job and huge kudos to you and your friends for publishing it here!
Earlier quoted context omitted.
Thinking out loud... I don't think these problems can be solved. If you are going to do it anyway, I would suggest: - Using a RAG architecture on top of a database of factual information. Wikipedia is probably your best bet. It is not 100% factual or correct either, but maybe as good as it gets. Scaling RAG to wikipedia size is not trivial, but I think it can be done. - Prompting the LLM to cite its sources so people…
There's a whole art to prompting a LLM to say it's unsure. I need to write a blog post about this, it's deep.
Cool stuff, only feedback I have is that it could be a bit clearer on the homepage what your product does - I only found out when playing around (I didn't read your post before trying). Maybe make it clear what it does before letting people play with it so have the test box in a 2 column layout or perhaps later on down the page? I didn't expect there was any other content/scroll on the homepage when I first landed on…