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.

Microsoft has released three new AI models aimed at enhancing its leadership in the multilingual and multimodal fields. The Phi-3.5 Mini Instruct is a lightweight model suitable for task execution, code generation, and logical reasoning, excelling particularly in multilingual and multi-turn conversations. The Phi-3.5 MoE (Mixture of Experts) model is rich in parameters and supports various inference tasks, especially outperforming peers in code, mathematics, and multilingual understanding. The Phi-3.5 Vision Instruct integrates text and image processing capabilities.

Microsoft has announced the launch of serverless fine-tuning capabilities for the Phi-3 small language model, enabling developers to easily adjust model performance on the Azure AI platform without managing underlying infrastructure, and it is free for initial use. The Phi-3 model, with 3 billion parameters, is suitable for enterprise developers, offering efficient performance at a lower cost. Although it has fewer parameters compared to OpenAI's GPT-3.5, it performs similarly across various applications. Serverless fine-tuning simplifies operations, reduces barriers, and supports the fine-tuning of small to medium models.