In the past year, Generative Pre-trained Transformer (GPT) has become the most important development direction in Artificial Intelligence (AI).

GPT, by leveraging the massive amount of data accumulated by humanity on the internet, has achieved complex tasks ranging from text generation to natural language understanding, from text generation to images, and even videos.

With the rapid development of Generative AI models like GPT, we are facing challenges such as the increasing consumption of data resources, data quality, and data copyright issues:

• The speed of data consumption on the internet is accelerating. With the increase in complexity and scale of Generative AI models like GPT, the demand for data is also growing continuously. This makes the speed of data resource consumption exceed the speed of data generation, leading to a shortage of data resources.
• The quality of internet data is becoming increasingly prominent. Due to the diverse sources of Internet data, the quality of the data varies, which causes problems in the training and application of Generative AI models like GPT. For example, low-quality data may lead to biased or misleading results generated by the model, affecting its performance and reliability.
• The issue of copyright in Internet data raises more concerns. Some Internet data is copyrighted, and unauthorized use can lead to legal disputes. This problem cannot be ignored for Generative AI models like GPT, which rely heavily on large amounts of data.

Introducing our state-of-the-art Generative AI Dataset Product: Large-Scale Professional Domain Corpus Dataset — Chinese.

maadaa.ai has developed a comprehensive automated parsing and data structuring engine which can seamlessly support most of the popular e-book formats including PDF, EPUB, mobi, azw (3), and DjVu. Leveraging this engine, we can accurately restore formulas within PDF documents to Latex text, ensuring complex equations and multiline formulas are recognized with precision.

Product Name:

Large-Scale Professional Domain Corpus Dataset — Chinese

Data Type:

Multi-modal corpus, markdown format, with embedded images

Data Collection Method:

licensed or license-free e-books

Key Features:

• 120M Electronic Documents
• 2PB fine-structured data
• Most popular e-book formats
• Hundreds of professional domains
• Comprehensive Format Support: most of the popular e-book formats such as PDF, EPUB, mobi, azw (3), and DjVu.
• Advanced OCR engine for Formulas: Equations and multiline formulas in PDFs are transformed into Latex text with high accuracy.
• Precise Layout Reproduction: Ensures the original formatting of PDFs is preserved, including text arrangement, headings, and diagrams.

Application Scenarios:

Generative AI-enabled search engine, chatbot, professional Q&A, professional assistants, domain-specific content generation, etc.

maadaa.ai, founded in 2015, is a comprehensive AI data service company supplying the AI industry with professional data services in text, voice, image, and video data types. From AI data collection to data processing and labeling, and AI dataset management, maadaa.ai helps customers efficiently capture, process, and manage data, carry on model training, in order to fast and low-cost AI technology introduction.

maadaa.ai’s global data collection and labeling network spans more than 40 countries, allowing maadaa.ai to provide standardized AI data collection, processing, labeling, acceptance, and delivery services to industrial customers.