Keyword density helper – This tool comes with a built-in keyword density helper in some ways similar to the likes of SurferSEO or MarketMuse the difference being, ours is free! This feature shows the user the frequency of single or two word keywords in a document, meaning you can easily compare an article you have written against a competitor to see the major differences in keyword densities. This is especially useful for SEO’s who are looking to optimize their blog content for search engines and improve the blog’s visibility.
File compare – Text comparison between files is a breeze with our tool. Simply select the files you would like to compare, hit “Upload” and our tool will automatically insert the content into the text area, then simply hit “Compare” and let our tool show you where the differences in the text are. By uploading a file, you can still check the keyword density in your content.
Comparing text between URLs is effortless with our tool. Simply paste the URL you would like to get the content from (in our example we use a fantastic blog post by Sherice Jacob found here) hit “Submit URL” and our tool will automatically retrieve the contents of the page and paste it into the text area, then simply click “Compare” and let our tool highlight the difference between the URLs. This feature is especially useful for checking keyword density between pages!
You can also easily compare text by copying and pasting it into each field, as demonstrated below.
Ease of use
Our text compare tool is created with the user in mind, it is designed to be accessible to everyone. Our tool allows users to upload files or enter a URL to extract text, this along with the lightweight design ensures a seamless experience. The interface is simple and straightforward, making it easy for users to compare text and detect the diff.
Multiple text file format support
Our tool provides support for a variety of different text files and microsoft word formats including pdf file, .docx, .odt, .doc, and .txt, giving users the ability to compare text from different sources with ease. This makes it a great solution for students, bloggers, and publishers who are looking for file comparison in different formats.
Protects intellectual property
Our text comparison tool helps you protect your intellectual property and helps prevent plagiarism. This tool provides an accurate comparison of texts, making it easy to ensure that your work is original and not copied from other sources. Our tool is a valuable resource for anyone looking to maintain the originality of their content.
User Data Privacy
Our text compare tool is secure and protects user data privacy. No data is ever saved to the tool, the users’ text is only scanned and pasted into the tool’s text area. This makes certain that users can use our tool with confidence, knowing their data is safe and secure.
Compatibility
Our text comparison tool is designed to work seamlessly across all size devices, ensuring maximum compatibility no matter your screen size. Whether you are using a large desktop monitor, a small laptop, a tablet or a smartphone, this tool adjusts to your screen size. This means that users can compare texts and detect the diff anywhere without the need for specialized hardware or software. This level of accessibility makes it an ideal solution for students or bloggers who value the originality of their work and need to compare text online anywhere at any time.
After OpenAI's failed attempt at building an ChatGPT text detector due to the reasons discussed below they have focused on a watermarking solution. Basically watermarking is the process leaving a fingerprint based on the selection of words the LLM has made when creating the text. This fingerprint can be identified after.
However, it has been reported that despite building this watermarking solution they have been reluctant to release it for the following reasons:
We have some news and updates to share about this review of OpenAI’s Text Classifier.
OpenAI has made the tough call to discontinue their text classifier due to its “ poor rate of accuracy”, according to Techcrunch. You can see how OpenAI’s Text Classifier performed in our accuracy post here: https://originality.ai/blog/ai-content-detection-accuracy
This industry is challenging and we absolutely empathize with the team at OpenAI. As the creators of ChatGPT, we can imagine the considerable pressures they faced as being considered the source of "truth" within the application.
Analyzing the situation as a third party, we believe that with OpenAI being at the forefront of AI technology and essentially viewed as the creators of AI generated content, meant that their approach to AI detection likely had to be more conservative and cautious. As the creators of ChatGPT, the scrutiny over false positives that they would have faced would have been exceptionally difficult to navigate.
Developing an AI detection tool to identify ChatGPT generated text is not an easy task! It requires working through complex challenges as well as acknowledging that there is never going to be a 100% perfectly accurate solution, no matter what! Balancing the need for accuracy while avoiding the backlash of false positives is a delicate tightrope to walk, even more so for OpenAI than anyone else.
We believe that both transparency and accountability are crucial in this industry, and we commend OpenAI for making the tough call to shut it down when its performance fell short of the desired standard.
Take a Look at the video we did on OpenAI’s accuracy :
You may already know that AI content writing tools enable people to produce engaging and informative content quickly. However, since AI is not perfect, there are often quality issues and the potential for plagiarism. This is when AI detection tools come into play.
AI content detectors are capable of detecting content generated by AI-powered software, even if it’s free of plagiarism. This service is especially useful now that Google penalizes websites that contain unnatural or artificially generated text.
From marketers and businesses buying content to educators concerned about the originality of their students’ work, AI content detection tools provide a straightforward way to learn whether a piece of text has been crafted with the aid of these specialized tools.
So today, we’re here to look at OpenAI Text Classifier, OpenAI’s own AI detector. OpenAI is well known for developing the AI transformer models ChatGPT and GPT-3. Let’s see how well its detection software performs and how its capabilities stack up against other platforms.
With its intuitive user interface and powerful algorithms, OpenAI Text Classifier simplifies the process of identifying relevant topics in large collections of documents or conversations. Its key features include:
Keep in mind that the OpenAI Text Classifier will not work on all texts. The minimum number of characters it needs is 1,000, which translates to roughly 150-250 words.
Unfortunately, this AI cannot detect plagiarism despite being trained with text-generating capabilities.
Here is where we get into the nitty-gritty. Let’s compare the performance of OpenAI Text Classifier and Originality.ai in an AI detection test using our sample texts generated with Jasper, a popular and powerful GPT2-based content generator.
As a top-ranking AI-detection tool, Originality.ai can identify and flag GPT2, GPT3, GPT3.5, and even ChatGPT material. It will be interesting to see how well these two platforms perform in detecting 100% AI-generated content.
OpenAI Text Classifier employs a different probability structure from other AI content detection tools. It labels text based on the likelihood that a piece of text was created by artificial intelligence, ranging from “very unlikely” (less than a 10% probability), “unlikely” (10%-45%), “unclear” (45%-90%), “possibly” (90%-98%), or “likely” (above 98%).
Originality.ai, however, provides results in terms of percentages that indicate how much of a text has been generated by AI and how much has been plagiarized.
Below is a side-by-side comparison of the OpenAI Text Classifier and Originality.ai.
From the get-go, OpenAI Text Classifier appears unable to accurately assess our samples as having been AI-generated.
OpenAI has been candid about the poor accuracy rate of their detection tool, reporting that it only correctly identified 26% of AI-written text when they used it on their testable data set. In the same test, false positives occurred 9% of the time. Among the seven samples used in our test, the tool was completely incorrect twice.
Meanwhile, Originality.ai confidently detected AI content in five out of seven samples, with only one error and one uncertain outcome.
It should be noted, however, that OpenAI determines its accuracy by how many times it predicted that the generated content was AI “with a very high degree of certainty.” In contrast, Originality.ai defines it as how many times it correctly predicted that the generated content was AI, explaining its high level of accuracy.
While comparable, OpenAI appears to be “less accurate,” not because its algorithm is inferior but because it is more cautious.
To give OpenAI Text Classifier some credit, OpenAI has made it clear that it should not be used as a primary decision-making tool but rather as a complement to other methods of determining text sources.
This makes Originality.ai, according to our results, the obvious choice for those seeking a precise and dependable AI content recognition program.
We took an even deeper look at the OpenAI Text Classifiers’ performance vs Originality.ai’s detection AI.
“Each document is labeled as either very unlikely, unlikely, unclear if it is, possibly, or likely AI-generated.” – OpenAI
Since we have 2 classes AI and Human, while OpenAI has 5 classes according to degrees, we will therefore include the ambiguous classes unclear if it is, possibly, or likely to be AI. The remaining classes are very unlikely, unlikely is Human
In the images below the Y-Axis is the Actual and the X-Axis is what the AI predicted.
1. All samples
2. 20 samples generated by GPT-3 and 20 samples written by human
3. 20 samples generated by GPT-J and 20 samples written by human
4. 20 samples generated by GPT-Neo and 20 samples written by human
5. 20 samples generated by GPT-2 and 20 samples written by human
6. 20 samples paraphrased from the original content (written by humans) and 20 samples written by human
If we compare OpenAI Text Classifier to Originality.ai, we can observe a few distinctions in terms of their performance:
If you’re simply interested in detecting AI-generated content using an accessible interface that provides fast, easy-to-understand results, OpenAI is certainly worth checking out.
As an added advantage, this tool was developed by the company that created ChatGPT, ensuring that it has considerable potential to grow and improve. As a complement to other AI-deception software, the classifier is also free to use.
If you’re looking for a quick and easy AI-detection tool that you can easily whip up on a browser, then OpenAI Text Classifier might well fit the bill. It’s essentially a finely tuned GPT model designed to determine whether the text has been generated by AI from a variety of sources, in particular from ChatGPT.
Using Originality.ai, however, will give you a more reliable and accurate analysis. The pay-as-you-go option gives users more flexibility when it comes to pricing, while its accuracy rate and advanced features set it apart from other options.
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.
Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.
Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.
String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.
The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.
Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.
String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.
Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.
The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
