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Multimodal AI Advancements with InternVL 1.5
Multimodal large language models (MLLMs) combine text and visual data processing to improve how artificial intelligence understands and interacts with the world. Research in this area aims to develop systems that can interpret and respond to a blend of visual and linguistic cues, resembling human-like interactions more closely.
The Challenge and Solution
Open-source MLLMs often face limitations compared to commercial models, especially in processing complex visual inputs and supporting multiple languages. To address this, the research team has introduced InternVL 1.5, an open-source MLLM designed to significantly enhance multimodal understanding. The model incorporates three major improvements:
- Enhanced Vision Encoder: The model features an optimized vision encoder for improved visual understanding.
- Dynamic High-Resolution Handling: It can handle high-resolution images up to 4K by dynamically adjusting image tiles based on the input’s aspect ratio and resolution.
- Bilingual Dataset: A high-quality bilingual dataset covering common scenes and document images annotated with English and Chinese question-answer pairs has been assembled to improve linguistic capabilities.
Performance and Applications
InternVL 1.5 demonstrates superior performance in OCR-related tasks and bilingual scene understanding, narrowing the performance gap with commercial counterparts. It achieves state-of-the-art results in various benchmarks, outperforming other open-source models and rivaling commercial models in multimodal tasks.
Practical AI Solutions
Companies can leverage InternVL 1.5 to redefine their work processes and stay competitive by identifying automation opportunities, defining measurable KPIs, selecting appropriate AI tools, and implementing AI gradually. For AI KPI management advice and insights into leveraging AI, companies can connect with the research team.
Spotlight on AI Sales Bot
Companies looking to automate customer engagement across all stages of the customer journey can explore the AI Sales Bot from itinai.com/aisalesbot. This solution is designed to redefine sales processes and customer engagement.
For more information, readers can check out the Paper and visit the GitHub Page.
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