Zero GPT

Freemium

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ZeroGPT AI Detector leverages DeepAnalyse™ Technology to accurately identify content produced by AI, including ChatGPT, GPT3, GPT4, Bard, and LLaMa models. It employs a robust multi-stage methodology, carefully designed to maximize detection precision while reducing incorrect identifications. This comprehensive deep learning approach is trained on a vast array of text samples from the internet, educational materials, and unique synthetic AI datasets.

How ZeroGPT AI Detector can help you:

Determines the likelihood of text being AI-generated, aiding in authenticity assessments.
Enhances content trustworthiness by verifying human authorship.
Supports academic integrity by detecting potential AI plagiarism.
Serves industries requiring content verification to maintain standards.

Why choose ZeroGPT AI Detector : Key features

Advanced DeepAnalyse™ Technology for precise detection.
Minimized rates of false positives and negatives for reliable results.
Trained on diverse and extensive text collections for robust performance.
Capable of identifying content from a wide range of AI language models.

Who should choose ZeroGPT AI Detector :

Educators and academic professionals monitoring for plagiarism.
Publishers and content creators ensuring originality in written material.
Businesses verifying the authenticity of user-generated content.
Researchers studying the impacts of AI-generated text.

About Zero GPT

Website

https://www.zerogpt.com

Release Date

November 2023

Pricing

Freemium

Related fields

Categories

Productivity, Project management, Coding automation, Task automation, Large language model

Related News

OpenAI Has Developed A Tool For AI Detection, But Seems Reluctant To Roll It Out Despite Growing Concerns

OpenAI has revolutionized the world of artificial intelligence since the inception of ChatGPT and keeps evolving to bring more advancements in user interaction with the AI tool and how information is accessed. There is no denying that the company has brought convenience and utility to users from varied fields, but data is sometimes misused by users at workplaces and academic institutions, and to deal with this problem, OpenAI has been working for the past year on a detection tool but is not releasing it yet, despite the growing concerns. OpenAI with ChatGPT has changed the AI game and how content is generated and used. Like any AI tool, the language model has brought forth more enhanced access to information and how it's presented, but it also posed issues regarding students using the tool for cheating and content creators using text generated through prompts as original through different workarounds. To minimize this problem, OpenAI has been working on a tool to detect users who rely entirely on ChatGPT for content creation. However, despite how widespread the concern regarding the loopholes seems to be, the company has still not rolled out the tool and is still weighing the potential impact and outcomes, as per a Wall Street Journal report. OpenAI updated its blog post regarding its tool for detecting AI-generated content and its watermarking method. It suggested that the technique is effective in localized tampering, such as paraphrasing, but would not be as accurate with globalized tampering that involves rewriting, for instance. Since the method can let bad actors find a workaround and potentially discourage non-native speakers from using the tool, OpenAI seems hesitant and is internally discussing whether to release the tool. Even though OpenAI confirmed to TechCrunch that the method's accuracy is close to 99.9 percent, it will still go with a 'deliberate approach.' The company's spokesperson said that they are dealing with caution due to: "The complexities involved and its likely impact on the broader ecosystem beyond OpenAI." Another possible reason OpenAI seems reluctant to release the tool is the potential ChatGPT users it could lose due to the watermarking. About 30 percent of ChatGPT users mentioned that they might not use the tool as frequently once the watermarking system is intact. OpenAI also mentioned in its blog post that they are exploring text metadata as an alternative approach since it is cryptographically signed, ensuring no false positives. However, it is still too early to know if this approach would be effective and what kind of impact would it have.

Wccftech

Mon, 5 Aug, 2:08 PM UTC

OpenAI's Dilemma: Withholding ChatGPT Detection Technology

OpenAI has developed technology to detect AI-generated text but is hesitant to release it. The company cites concerns about potential misuse and the need for a careful approach in addressing academic integrity issues.

4 Sources

Mon, 5 Aug, 12:01 AM UTC

Grammarly's new tool aims to detect AI-generated text. Here's how it works

In this age of AI, determining whether text was written by a bot or a person has become increasingly difficult. Several detection products have already popped up, but with decidedly mixed results. Now, Grammarly is kicking off its tool, which it believes will better detect which parts of a document were created by AI versus humans. Also: I tested 7 AI content detectors - they're getting dramatically better at identifying plagiarism Dubbed Grammarly Authorship, the new program will work across 500,000 apps and websites. The latest software will try to identify the origin of each part of the document, uncovering which sections were created by a person, which ones were pasted from another source, and which ones were cooked up by AI. This approach aims to distinguish authorship from other detection tools that analyze a document as a whole. Authorship will launch in beta in Google Docs for all Grammarly customers starting next month and expand to Microsoft Word and Apple's Pages by the end of the year. As an automated writing and editing assistant, Grammarly offers several plans, including a free basic flavor, a $12-per-month Premium subscription, a $15-per-month Business subscription, and an edition for schools and students. Also: How to pick a laptop for college: 4 big considerations (and 10 great options) Though Authorship will be available to any individual, business, or other customer, Grammarly is targeting the education market in particular. This is partly because of false positives in which students have turned in papers and assignments they wrote themselves but were flagged as AI-generated. "As the school year begins, many institutions lack consistent and clear AI policies, even though half of people ages 14-22 say they have used generative AI at least once," Jenny Maxwell, Head of Grammarly for Education, said in a statement. "This lack of clarity has contributed to an overreliance on imperfect AI detection tools, leading to an adversarial back-and-forth between professors and students when papers are flagged as AI-generated. "What's missing in the market is a tool that can facilitate a productive conversation about the role of AI in education," Maxwell added. "Authorship does just that by giving students an easy way to show how they wrote their paper, including if and how they interacted with AI tools." Once activated in a document, Authorship will automatically categorize text as typed by a human, generated by AI, modified with AI, pasted from a known or unknown source, or edited by Grammarly or a separate spell checker. Whether you're writing or reviewing the document, you'll also find key details about Authorship's analysis. Also: What is ChatGPT and why does it matter? Here's what you need to know Authorship analytics will break down the different categories, such as those typed by a human or pasted from an unknown source. The tool will then display an overall analysis of the document with such factors as the total time spent writing and the number of active writing sessions. An authorship report includes the full text of the document. Each section will be color-coded to show whether it was written by a person, generated or edited by AI, or pasted from an external source. An authoring replay will play back the text in the document, revealing how it appeared. For students, Authorship will ensure the report or assignment meets the guidelines required by the teacher and provide objective data if the student is accused of AI-generated plagiarism. Early next year, the tool will also prompt students to cite any text from external sources. Also: 10 tech gadgets you actually need for college, according to recent grads Other companies, including OpenAI, have launched or tried to launch their own AI detectors. However, achieving close to 100% accuracy has been a challenge. In 2023, OpenAI debuted and then pulled its own AI detection tool because of low accuracy. Such tools have improved, though false positives and other flaws still creep in. Will Grammarly Authorship perform better than the rest of the pack? We'll find out once it arrives next month.

ZDNet

Thu, 15 Aug, 4:06 PM UTC

Can Grammarly's AI bloodhound sniff out text written by ChatGPT?

Grammarly's expansion from writing assistance to AI tools that can write for you continued this week with a new feature designed to spot AI-composed text. Grammarly Authorship is coming to Google Docs as a beta and aims to help educators in particular work out when students are using AI to write their assignments. Teachers and education policymakers have been wrestling with the issue of figuring out when something is written using AI for a long time, but ChatGPT and its rivals heightened the sense of urgency for such a tool as they make the traditional methods unreliable. The difficulty has been compounded by issues around false positives and difficulties in picking AI compositions from those written by students learning how to write, especially those who have English as a second language. Grammarly Authorship attempts to address those problems by avoiding the way many existing AI detection tools analyze a text when it's done. Instead, Grammarly Authorship tracks the real-time writing of a text. Supposedly it can tell when something has been typed, pasted from elsewhere, or generated on the page with AI. The tool will integrate with more than half a million applications and websites, centering on writing platforms like Google Docs, Microsoft Word, and Apple's Pages. The feature can track typing as it happens and note when text is copied over or when an AI tool generates or modifies text, such as Google Gemini or Microsoft's Bing AI. Grammarly Authorship then makes a report and splits the paper up into categories based on if it was written, AI-generated, or pasted from elsewhere. It even shows a replay of the document being written to show exactly what happened. Individuals can purchase access to Grammarly Authorship, but educators are clearly the main market for the tool. AI-generated writing among students and in academic circles is contentious and has led to wrongful accusations by teachers, even as other students have admitted using AI to write papers that never get caught. "As the school year begins, many institutions lack consistent and clear AI policies, even though half of people ages 14-22 say they have used generative AI at least once," Head of Grammarly for Education Jenny Maxwell explained. "This lack of clarity has contributed to an overreliance on imperfect AI detection tools, leading to an adversarial back-and-forth between professors and students when papers are flagged as AI-generated. What's missing in the market is a tool that can facilitate a productive conversation about the role of AI in education. Authorship does just that by giving students an easy way to show how they wrote their paper, including if and how they interacted with AI tools." Of course, that only matters if educators decide to trust Grammarly's new concept. It will have to hit performance goals in real-world scenarios. That's on top of competing with possible rivals. OpenAI has developed some new tools to detect content generated by ChatGPT and its AI models with a kind of watermark. But the company decided against rolling it out yet, lest it cause problems even for those with benign interests. That follows the failure of its first AI text detector, which it shut down in just six months. Though having proof like the Authorship report would remove the question of whether a student really wrote their paper, there's an inherent privacy issue that may make some reluctant to use the tool. Students may not want to share all the false starts in their writing or all the ways it didn't go well. There doesn't have to be a secret behind wanting only to share the final product. But they may not get a choice. Writing at home may soon resemble taking a test, where a proctor keeps an eye on students to prevent cheating, and even innocent moves may evoke suspicion.

TechRadar

Tue, 20 Aug, 6:04 AM UTC

AI and human writers share stylistic fingerprints: New work by researchers detects writing patterns of LLMs

People write with personal style and individual flourishes that set them apart from other writers. So does AI, including top programs like Chat GPT, new Johns Hopkins University-led research finds. A new tool can not only detect writing created by AI, it can predict which large language model created it, findings that could help identify school cheaters and the language programs favored by people spreading online disinformation. "We're the first to show that AI-generated text shares the same features as human writing, and that this can be used to reliably detect it and attribute it to specific language models," said author Nicholas Andrews, a senior research scientist at Johns Hopkins' Human Language Technology Center of Excellence. The work, which could reveal which programs are prone to abuse and lead to stronger controls and safeguards, was presented at an AI conference, the International Conference on Learning Representations in May. The advent of large language models like ChatGPT have made it easy for anyone to generate fake writing. Much of it is benign but schools are wrestling with plagiarism and bad actors are spreading spam, phishing and misinformation. Following the 2016 election and concerns surrounding foreign influence campaigns on social media, Andrews became interested in developing technologies to help combat misinformation online. "I said let's try to build a fingerprint of someone online and see if those fingerprints correspond to any of the disinformation we're seeing," Andrews said. "Now we have this hammer we spent years building, and we can apply it to detect what's fake and what's not online. Not only that, we can figure out if it was ChatGPT or Gemini or LLaMA, as they each have linguistic fingerprints that separate them from not only human authors but other machine authors, as well. "The big surprise was we built the system with no intention to apply it to machine writing and the model was trained before ChatGPT existed. But the very features that helped distinguish human writers from each other were very successful at detecting machine writing's fingerprints." The team was surprised to learn that each AI writing program has a distinct style. They'd assumed all machine writing would share the same generic linguistic fingerprint. Their detection tool, trained on anonymous writing samples from Reddit, works in any language. It is available for anyone to freely use and download. It has already been downloaded about 10,000 times. The team is not the first to create an AI writing detection system. But its method appears to be the most accurate and nimble, able to quickly respond to the ever-changing AI landscape. "Law enforcement originated this concept, parsing ransom notes and other writing by suspected criminals and trying to match it to individuals," Andrews said. "We basically scaled that up. We took away the human, manual process of defining these written features, threw lots of data at the problem and had neural network decide what features are important. We didn't say look at exclamation marks or look at passive or active voice. The system figured it out and that's how we were able to do much better than people have." When the team presented the work at the International Conference on Learning Representations, lead author Rafael Rivera Soto, a Johns Hopkins first-year Ph.D. student advised by Andrews, created a thought-provoking demo. He ran all the peer reviews from the conference through the detector. It flagged about 10% of the reviews as likely machine generated -- and probably ChatGPT. Authors include Johns Hopkins doctoral student Aleem Khan; Kailin Koch and Barry Chen of the Lawrence Livermore National Laboratory; and Marcus Bishop of the U.S. Department of Defense.

Tech Xplore

Mon, 18 Nov, 8:19 PM UTC

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