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多模态与大型多模态模型（LMMs）全面解析
原标题：Multimodality and Large Multimodal Models (LMMs)
AI 摘要
Chip Huyen 在其博客文章中深入探讨了多模态与大型多模态模型（LMMs）的概念，指出自然智能需要处理多种数据模态，并介绍了多模态系统的类型、基础训练方法（如 CLIP 和 Flamingo）以及当前的研究方向（如生成多模态输出和适配器）。文章强调了多模态在医疗、机器人等领域的必要性，并提及了 GPT-4V 等模型。
以上摘要由 AI 生成，可能存在误差。事实请以原文为准。
正文节选
For a long time, each ML model operated in one data mode – text (translation, language modeling), image (object detection, image classification), or audio (speech recognition). However, natural intelligence is not limited to just a single modality. Humans can read, talk, and see. We listen to music to relax and watch out for strange noises to detect danger. Being able to work with multimodal data is essential for us or any AI to operate in the real world. OpenAI noted in their GPT-4V system card
发布时间：2023-10-10 08:00
抓取时间：2026-08-02 00:21
来源机构：Chip Huyen