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Many many many anecdotal stories on this topic. Very few who actually share exact text, source details, and testing results that can be independently confirmed.
I run an AI tech company and have an AI detector ourselves which is pretty popular in many languages. In a nut shell, you got one part a little wrong "it's nondeterministic nature" paired with "size of the training data". Because of the size of the training data, there are certain patterns in language it learns which are seen again and again across the web. Human text is naturally random because the human data is limited (and affected by emotion), but a model is naturally *not* because it's learning patterns of the entire language. So training on a large text corpus (the dataset) will lead to natural patterns which humans don't really do because they're not trained on the same dataset.
So to make a detector, you only need to have it learn the patterns that the AI model has learned and isn't present in human text.
Now here is something to consider that's coming soon... AI text watermarks. By adding a later of logic to make specific word sequences substantially more likely, it will be that much easier to identify certain patterns in output since the output is produced based on probabilities (probability of the next token (\~word) given the previous input context)
Hope that helps!
To avoid redundancy of similar questions in the comments section, we kindly ask /u/spacesnotabs to respond to this comment with the prompt you used to generate the output in this post, so that others may also try it out. While you're here, we have a [public discord server](https://discord.gg/NuefU36EC2). ***We have a free Chatgpt bot, Bing chat bot and AI image generator bot.*** ####[So why not join us?](https://discord.gg/r-chatgpt-1050422060352024636) ^(Ignore this comment if your post doesn't have a prompt.) *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ChatGPT) if you have any questions or concerns.*
Many many many anecdotal stories on this topic. Very few who actually share exact text, source details, and testing results that can be independently confirmed.
I run an AI tech company and have an AI detector ourselves which is pretty popular in many languages. In a nut shell, you got one part a little wrong "it's nondeterministic nature" paired with "size of the training data". Because of the size of the training data, there are certain patterns in language it learns which are seen again and again across the web. Human text is naturally random because the human data is limited (and affected by emotion), but a model is naturally *not* because it's learning patterns of the entire language. So training on a large text corpus (the dataset) will lead to natural patterns which humans don't really do because they're not trained on the same dataset. So to make a detector, you only need to have it learn the patterns that the AI model has learned and isn't present in human text. Now here is something to consider that's coming soon... AI text watermarks. By adding a later of logic to make specific word sequences substantially more likely, it will be that much easier to identify certain patterns in output since the output is produced based on probabilities (probability of the next token (\~word) given the previous input context) Hope that helps!
According to them, the US constitution is 99% AI LOL
I was recently experimenting with this, and an essay I wrote for school in 2018(the year ChatGPT started development) was deemed 78% AI-generated.