In recent years, significant progress has been made in artificial intelligence technology, but challenges still exist between computational efficiency and multi-functionality. Many advanced multi-modal models, such as GPT-4, typically require substantial computational resources, limiting their use on high-end servers and making it difficult for intelligent technologies to be effectively utilized on edge devices like smartphones and tablets. Furthermore, real-time processing of tasks such as video analysis or speech-to-text still faces technical barriers, highlighting the need for efficient and flexible AI models to achieve seamless performance under limited hardware conditions.

On September 21, 2024, Alibaba announced several technological innovations and business developments at the Yunqi Conference in Hangzhou. Among these, the Modao community officially launched the AIGC section, aimed at providing developers with a comprehensive AI creation and development platform. This platform currently offers all functional areas and GPU computing power for free, with the first batch featuring 157 selected multi-modal models, including popular community models and various stylized LoRa models contributed by designers.

MiniMax Xiyu Technology recently announced that since its establishment at the end of 2021, it has built trillion-parameter MoE large text models, speech models, and image models. It has also launched native applications such as Xingye and Hailuo AI, while providing an open platform API service for enterprises and developers.

PaddleMIX 2.0 is a multi-modal model development kit launched by Baidu, aimed at simplifying multi-modal application development and supporting scenarios such as autonomous driving, smart healthcare, and search engines. Key highlights include: 1. **Rich Model Library**: Covers images, text, video, and audio, with the addition of LLaVA series models, providing cutting-edge technology support. 2. **Full Process Development Experience**: Equipped with DataCopilot and Auto modules to simplify the training process of multi-modal models. 3. **High Performance Training Capability**

In the dazzling galaxy of AI, Leap Star Company has emerged as a shining star with its innovative multimodal models. At the WAIC conference, they showcased three uniquely crafted AI models, highlighting their multimodal capabilities. Step-2: The MoE model with 10 billion parameters is currently available for experience upon application. Step-1.5V, a billion parameter multimodal model, not only demonstrates extraordinary talents in image understanding but also opens up new horizons in video under

Apple and researchers from the Swiss Federal Institute of Technology (EPFL) have jointly developed a single model that can handle arbitrary-to-arbitrary modalities. This model can be trained on dozens of highly diverse modalities and perform joint training on large-scale multimodal datasets and text corpora. Named 4M-21, it is trained on 21 different modalities, completing at least three times more tasks than existing models without losing performance.