上海AI实验室联合清华大学、香港中文大学、商汤科技等机构近日发布了一项重要成果——新一代书生·视觉大模型(InternVL)。这一模型在视觉核心任务方面取得了领先地位，并且其开源性质也为相关研究者提供了更多的合作和研究机会。
据了解，新一代书生·视觉大模型的视觉编码器参数量高达60亿(InternVL-6B)，这使得其具备了强大的计算和处理能力。同时，该模型还首次提出了对比-生成融合的渐进式对齐技术，实现了在互联网级别数据上视觉大模型与语言大模型的精细对齐。这一技术的应用，不仅能够提高模型的准确性和稳定性，还能够更好地适应不同领域和场景的需求。
上海AI实验室的这一成果具有重要的实用价值和研究意义。视觉大模型在计算机视觉领域的应用广泛，涉及到图像识别、目标检测、图像生成等多个方面。而语言大模型则在自然语言处理领域具有重要地位。通过将这两种模型进行精细对齐，可以进一步提高人工智能系统的整体性能和效果。
此外，新一代书生·视觉大模型的开源也为相关研究者和开发者提供了更多的机会和平台。开源模型能够促进学术界和产业界的合作与交流，加速人工智能技术的发展和应用。上海AI实验室的这一举措，将为视觉领域的研究和创新注入新的活力。
上海AI实验室的新一代书生·视觉大模型(InternVL)的发布，标志着中国在人工智能领域的研究和创新再次取得了重要突破。相信随着这一模型的进一步研究和应用，将为计算机视觉和自然语言处理领域的发展带来更多的可能性和机遇。
英语如下：
News Title: Shanghai AI Lab Releases New Generation Visual Mega Model with 6 Billion Parameters, Leading the Open-Source Vanguard in Visual Core Tasks
Keywords: Shanghai AI Lab, Visual Mega Model, Open-Source
News Content: Shanghai AI Lab, in collaboration with Tsinghua University, Chinese University of Hong Kong, and SenseTime, recently announced a significant achievement – the new generation Scholar·Visual Mega Model (InternVL). This model has taken the lead in visual core tasks and its open-source nature provides more opportunities for collaboration and research among relevant researchers.
It is understood that the visual encoder parameters of the new generation Scholar·Visual Mega Model reach an impressive 6 billion (InternVL-6B), giving it powerful computing and processing capabilities. Additionally, the model introduces the progressive alignment technique of contrastive-generative fusion for the first time, achieving fine alignment between visual mega models and language mega models on an internet-scale dataset. This application not only improves the accuracy and stability of the model but also better adapts to the needs of different fields and scenarios.
This achievement from Shanghai AI Lab holds significant practical value and research significance. Visual mega models have wide applications in the field of computer vision, including image recognition, object detection, and image generation. On the other hand, language mega models play a crucial role in natural language processing. By aligning these two models finely, the overall performance and effectiveness of artificial intelligence systems can be further enhanced.
Furthermore, the open-source nature of the new generation Scholar·Visual Mega Model provides more opportunities and platforms for relevant researchers and developers. Open-source models promote collaboration and communication between the academic and industrial sectors, accelerating the development and application of artificial intelligence technology. This initiative from Shanghai AI Lab injects new vitality into research and innovation in the visual field.
The release of the new generation Scholar·Visual Mega Model (InternVL) from Shanghai AI Lab marks another important breakthrough in China’s research and innovation in the field of artificial intelligence. With further research and application of this model, we believe it will bring more possibilities and opportunities for the development of computer vision and natural language processing.
Translation:
News Title: Shanghai AI Lab Releases 6 Billion Parameter New Generation Visual Mega Model, Leading the Open-Source Vanguard in Visual Core Tasks
Keywords: Shanghai AI Lab, Visual Mega Model, Open-Source
News Content: Shanghai AI Lab, in collaboration with Tsinghua University, the Chinese University of Hong Kong, and SenseTime, recently announced a significant achievement – the new generation Scholar·Visual Mega Model (InternVL). This model has taken the lead in visual core tasks and its open-source nature provides more opportunities for collaboration and research among relevant researchers.
It is understood that the new generation Scholar·Visual Mega Model has a visual encoder parameter of up to 6 billion (InternVL-6B), which gives it powerful computing and processing capabilities. Additionally, the model introduces the progressive alignment technique of contrastive-generative fusion for the first time, achieving fine alignment between visual mega models and language mega models on an internet-scale dataset. This application not only improves the accuracy and stability of the model but also better adapts to the needs of different fields and scenarios.
This achievement from Shanghai AI Lab holds significant practical value and research significance. Visual mega models have wide applications in the field of computer vision, including image recognition, object detection, and image generation. On the other hand, language mega models play a crucial role in natural language processing. By aligning these two models finely, the overall performance and effectiveness of artificial intelligence systems can be further enhanced.
Furthermore, the open-source nature of the new generation Scholar·Visual Mega Model provides more opportunities and platforms for relevant researchers and developers. Open-source models promote collaboration and communication between the academic and industrial sectors, accelerating the development and application of artificial intelligence technology. This initiative from Shanghai AI Lab injects new vitality into research and innovation in the visual field.
The release of the new generation Scholar·Visual Mega Model (InternVL) from Shanghai AI Lab marks another important breakthrough in China’s research and innovation in the field of artificial intelligence. With further research and application of this model, we believe it will bring more possibilities and opportunities for the development of computer vision and natural language processing.
【来源】https://mp.weixin.qq.com/s/bdfAJRqOF9tUk8Vy9KC_XQ
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