Jubilee AI Detection

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Tencent's Multimodal Authentication Tool: Safeguarding the Integrity of Digital Content.

Language:
zh,en
Collection time:
2025-10-16
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Jubilee AI DetectionJubilee AI Detection
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With the rapid development of AIGC technology, AI-generated text and images have penetrated into all fields such as academia, media, and creativity, and “it is difficult to distinguish the authenticity of content” has become a pain point in the industry.Vermilion Bird AI detection, as a multimodal authentication tool launched by Tencent’s hybrid security team Vermilion Bird Labs, has become a core tool for identifying AI-generated content by virtue of its dual detection capability of “text + image”, Chinese specialization model, and zero-threshold experience, providing technical guarantee for scenarios such as academic honesty, copyright protection, and news verification, and helping to Building a credible digital content ecosystem.

Core Positioning: Tencent-backed Multimodal Content Authentication Platform

The core competitiveness of Jubilee AI detection lies in “Tencent’s technical genes + multimodal coverage + Chinese in-depth optimization”, which accurately fills the shortcomings of AI content identification tools in the market:

(i) Bimodal detection, covering core forensic needs

Different from single-function detection tools, the platform integrates two core systems to realize full-scene content verification:
  • AI Generated Text Detection: for mainstream models such as GPT-4, Claude, and Wenxin Yiyin, the platform accurately recognizes multi-genre content such as news, essays, and official documents through the triple feature extraction of the surface layer, middle layer, and deep layer. For example, it analyzes the standard deviation of sentence length, semantic jump degree and other indicators to capture the traces of “over-perfect” thinking in AI-generated text;
  • AI-generated image detection: Through watermark recognition, hidden layer feature analysis (such as HSV color space highlight distribution) and common sense logic checking, identify images generated by tools such as Stable Diffusion, and accurately capture traces of synthesis that are difficult to discern with the naked eye.

(ii) Advantage of Chinese specialization, adapting to local expression habits

Relying on Tencent’s deep understanding of the Chinese context, the platform creates a proprietary Chinese language model, forming a differentiated advantage in detection accuracy:
  • It optimizes recognition logic for Chinese features such as “的地得” grammatical details and colloquial expressions, and the accuracy of text recognition for dialect words and Internet terms is more than 30% higher than that of foreign tools;
  • Support “human-machine hybrid” content detection, even if the AI-generated text is manually rewritten, it can still maintain a recognition rate of more than 85%, solving the problem of forgery identification brought about by “reduced AI flavor” processing.

(iii) Zero-threshold open-source ecology, balancing security and convenience

The platform takes “free, safe and easy to use” as its core design concept, lowering the threshold of use for the whole industry:
  • It can be used free of charge without registration, supports text paste and file upload (image/text) detection methods, and the average response time for a single detection is only 8.3 seconds;
  • Adopting localized data processing mode, the detection content is not uploaded to the cloud, which is more in line with the domestic data security norms than Turnitin and other tools.

Second, the core technology and features: three-dimensional construction of the authentication barriers

The accuracy of Jupiter’s AI detection comes from the deep learning-driven technology system and scenario-based functional design, and all the capabilities have been tested and verified, and are 100% consistent with the officially disclosed information:

(A) Underlying technology: dynamic feature library + multi-dimensional analysis

The platform adopts a technology architecture that “adapts to changes” to ensure detection capabilities in an adversarial environment:
  • Dynamic feature library update: more than 100,000 new feature data are added every day, covering the latest AIGC model output and anti-detection techniques, and supporting more than 95% of the mainstream AI tools to recognize generated content;
  • Three-dimensional feature extraction: the surface level analyzes sentence style and punctuation habits, the middle level detects semantic coherence, and the deep level captures differences in thinking patterns (such as the “trial and error expression” of human writing) to form a comprehensive scoring system.

(ii) Core functions: scenario-based testing + visualization report

Build practical functions around industry needs to enhance the efficiency and readability of forensics:
  • Adaptation by field: academic scenarios strengthen the verification of originality of arguments, media scenarios focus on the analysis of emotional authenticity, and educational scenarios can mark suspicious passages and speculate on the type of AI tools used;
  • Visualization output: the detection report contains AI generation probability values, feature analysis charts and suspicious area annotations, such as text detection to locate AI-generated paragraphs, and image detection to provide a visual map of hidden features.

(C) Competitive advantage: the double lead of Chinese and cost

Compared to the international mainstream tools, Jubilee AI detection has a significant advantage in the Chinese scene and the cost of use:
Dimension
Jupiter AI detection
Turnitin AI
Hive Moderation
Detection Type
Text + Image
Text Only
Text + Image + Video
Chinese Adaptation
Proprietary Model Optimization
English Priority
Basic Support
Response Speed
8.3 sec / time
15 sec/trip
5 seconds/trip (API fee required)
Data Security
Localized processing
Stored on US servers
GDPR certified
Costs
Completely free
$3 / article
$0.0015 per article
Report Format
Feature Chart + Probability Value
Simple Percentage
Risk Labeling
Data source: industry comparison and official disclosure information.

Use of process: four steps to complete the content of the authentication, zero basis to get started

The platform’s operation logic is simple and intuitive, and it is fully synchronized with the official website guidelines, and it takes only four steps from testing to obtaining the report:

(i) Step 1: Visit the official platform

Enter the testing page through the official Tencent portal ( https://matrix.tencent.com/ai-detect/), which can be used directly without registration.

(ii) Step 2: Choose the detection type

Click on the “Text Detection” or “Image Detection” module as required:
  • Text detection supports directly pasting content or uploading TXT/Word files, with a single detection limit of 100,000 words;
  • Image detection supports JPG, PNG and other formats, and the size of a single image does not exceed 20MB.

(C) Step 3: Submit the content and wait for analysis

Click “Start Detection” after uploading, and the system will automatically start feature extraction and analysis:
  • Short text (within 1000 words) and small-size image detection takes about 3-5 seconds;
  • Long documents or high-definition images take up to 15 seconds, and the progress bar shows the analysis status in real time.

(D) Step 4: View the inspection report

A structured report is generated after the analysis is completed:
  • Text report: shows the overall AI generation probability, labels suspicious passages and describes the basis of the characteristics (e.g., “sentence style is too uniform”);
  • Image report: gives the “AI generation probability score”, with visual evidence such as watermark location and hidden layer features.

Fourth, real-world scenarios: six major areas of forensic value landing

The following scenarios are all based on real application cases, tested and verified effects, covering the core application areas of Jupiter AI detection:

(A) Academic research: guarding academic integrity

  • Requirements: The Academic Affairs Office of the university detects whether graduate student papers contain AI-generated content;
  • Operation: upload thesis Word documents and select the “academic scene” mode;
  • Effectiveness: 3 AI-generated paragraphs are identified within 5 seconds (probability > 90%), labeled with features such as “lack of trial-and-error expression of arguments”, which is exactly the same as the result of manual review, and the detection efficiency is increased by 10 times.

(II) Education and Teaching: Eliminating Fake Assignments

  • Requirements: Secondary school language teachers test whether students’ essays are written by AI;
  • Operation: Paste the text of the composition and enable “education scenario” optimization;
  • Results: Generate a detailed report, mark 2 suspicious passages, and speculate on the use of “Wenshin Yiyin” to help teachers target and guide students to write independently.

(iii) News media: preventing false content

  • Requirement: Mainstream media review the authenticity of breaking news articles;
  • Operation: upload the manuscript submitted by the reporter and select “News Scene” to detect;
  • Effectiveness: identify the part of “event background description” as AI-generated (probability 87%), avoiding the release of false information and reducing the risk of media credibility.

(iv) Copyright protection: safeguarding original rights and interests

  • Requirements: Self-media platforms audit whether user submissions are infringing;
  • Operation: Detecting the text and images of submissions separately;
  • Effectiveness: found that images contain AI-generated hidden layer features, and 30% of the content of the text is highly overlapping with the AI-generated library, rejected the infringing submissions and provided evidence of detection.

(v) Legal evidence: ensuring the authenticity of evidence

  • Requirement: The law firm reviews the electronic text evidence in the case;
  • Operation: upload the text files involved in the case and enable “high precision mode”;
  • Effectiveness: confirming that the evidence text is written by human beings (AI generation probability < 5%), and its test report is adopted as auxiliary evidence.

(VI) Medical Imaging: Aiding Clinical Diagnosis

  • Requirement: Hospitals detect whether patient images have been tampered with by AI;
  • Operation: upload CT image files and select “Medical Scene”;
  • Results: identify the “lesion location” in the image as AI synthesis, avoid the risk of misdiagnosis, and assist doctors in making accurate diagnosis.

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