Title: OCR 2.0: A New Generation Optical Character Recognition Model for Easy Image Text Conversion. Recently, researchers have developed a new universal Optical Character Recognition (OCR) model called GOT (Universal OCR Theory). In their paper, they introduced the concept of 'OCR 2.0' for the first time. This new model aims to combine the advantages of traditional OCR systems with the powerful capabilities of large language models. The architecture of GOT is quite advanced, featuring an image encoder with approximately 80 million parameters and 500...

In the digital age, quickly converting text content from images into editable text is a common and important need. Now, the emergence of a new optical character recognition (OCR) model called GOT (General Optical Character Recognition Theory) marks the advancement of OCR technology into the 2.0 era. This innovative model combines the advantages of traditional OCR systems with large language models, aiming to create a more efficient and intelligent text recognition tool. The GOT model employs an innovative end-to-end architecture, a design that not only saves resources but also greatly enhances performance.

Microsoft has released Phi-3.5-vision, a lightweight, multimodal open source AI model designed for processing textual and visual inputs, supporting a context length of 128K. This model is suitable for resource-constrained environments and features capabilities such as image understanding, OCR, chart parsing, and multi-image summarization, showcasing excellent performance and low latency. Comprised of 4.2 billion parameters, it is trained with high-quality data to ensure performance and privacy. It includes three models: lightweight AI, expert mix, and multimodal model, all demonstrating outstanding performance in image and video processing benchmarks.