According to most search engines including Google which is arguably the biggest of them all, Al-generated content is susceptible to poor SEO practices. It’s against this background that most search engines discourage the publishing of Al content while in extreme cases like that of Google, Al-generated content is flagged and the site it is published on is blacklisted for going against Google’s Al content guidelines. While this is the case, there are still many writers who rely on Al models to generate content. As such, SEO experts and content marketers before they proceed to publish the content they receive need to check if there are any instances of Al-generated text included. It’s on this front that GLTR comes in handy.
What GLTR Offers
GLTR in full Giant Language model Test Room is an Al detection tool. This tool is unique when compared to other Al detection tools in that it does not detect sentences of Al-generated text. Rather, it analyses each and every word in the content you provide. Each word is then rated according to GLTR parameters of Al-generated text. Collectively thereafter, the scores of each word checked are tabulated and a final result is given.
Owing to the fact that GLTR analyses each word first and then the whole text afterwards, it has the highest probability of detecting Al text even in rewritten or paraphrased documents. GLTR’s parameters assert that when it comes to Al content, the “text will have a certain set of words at each position predefined”. However, with human writing, words are written in a more unpredictable format. The GLTR tool, therefore, analyses the placing of words in detecting the potential use of Al-generated text.
GLTR does a robust job in detecting instances of Al text not just in articles and documents but also when it comes to social media profiles. From Facebook to Twitter among other social media platforms, GLTR also detects fake profiles by analysing profile data.
How GLTR Works
Using GLTR is very simple. All that users need to do is to launch the official site. Once they do that, they can copy and paste the text they want to check. After pasting, proceed to check the text. Note that when the results come back, each word will be highlighted. The colour that it’s highlighted with determines if it’s being flagged as an Al written word or not. The colours used by GLTR are as follows:
- Green: Words highlighted in green are theoretically found in the top 10 predicted words
- Yellow: Words highlighted in yellow are theoretically found in the top 1000 predicted words
- Red: Words highlighted in red are theoretically found in the top 1000 predicted words
- Purple: Words highlighted in purple will not appear in the predicted words.
In interpreting the results, users ought to note that more words highlighted in red and purple suggest that there are free instances of Al-generated text or in some ways, the text was 100% written by humans. On the other hand, if the highlighted words are mostly in green and yellow, it means that there are instances of Al-generated text or in some instances, the whole text was Al generated.
GLTR Pricing
A great thing to note about GLTR is that it’s completely free. You aren’t charged a dime for checking your content regardless of how long it is for as long as it falls within the supported character count.
Round Up
The mere fact that GLTR detects instances of Al-generated content by looking at the placement of each word makes it one of the best Al detection tools. This is necessitated by the fact that it has the power to even detect rewritten or paraphrased content. Moreover, GLTR can also detect such things as fake social media profiles. The major downside of GLTR is that it uses GPT-2 as the language model. As such, its results are more accurate when detecting GPT-2 written content.