April 30, 2024
Cono 1.5
Introducing Cono 1.5, the large language model in multimodal natural language processing
April 30, 2024
Cono 1.5
Introducing Cono 1.5, the large language model in multimodal natural language processing
Introduction
Cono is an advanced large language model (LLM) developed based on the Mistral-7B-v0.1 base model from Mistral AI. One of the key enhancements of Cono is its extended context length, which reaches up to 16,000 tokens. This significant improvement enhances the model’s ability to understand and process complex and lengthy texts. Developed by Arcanic AI, Cono is also optimized for the Vietnamese language, providing substantial benefits for users both within and outside Vietnam.
Features and Innovation
Multimodal Capabilities
One of Cono’s standout features is its multimodal capability. In the context of artificial intelligence, “multimodal” refers to a model’s ability to process and integrate multiple types of data. Cono can accept three types of input data: text, images, and audio. After processing, Cono can output two types of data: text and audio. This ability opens up numerous potential applications in fields such as translation, virtual assistants, and multimedia interaction systems.
Optimization for Vietnamese
Arcanic AI has fine-tuned Cono by training it further on Vietnamese data. This includes expanding the model’s tokenizer by adding Vietnamese tokens, which helps Cono understand and process the language more naturally and accurately. This optimization is particularly important in the context of the growing AI applications in Vietnam, where there is an increasing demand for powerful language models with deep understanding of the native language.
Performance and Evaluation
Cono achieved a score of 47.6 on the VMLU (Vietnamese Multimodal Language Understanding) benchmark, a specialized evaluation set for large Vietnamese language models. This score is on par with OpenAI’s GPT-3.5, one of the most advanced large language models currently available. Compared to other Vietnamese language models such as PhoGPT and ViGPT, as well as regional models like SeaLLM from Southeast Asia, Cono demonstrates superior performance, showcasing its excellent capabilities in processing and understanding the Vietnamese language.
Applications and Prospects
With its multimodal capabilities and optimization for Vietnamese, Cono presents significant potential in both research and business applications. In the realm of data research, Cono can facilitate the development of advanced language processing tools, enhancing the understanding and manipulation of complex datasets. Researchers can leverage Cono’s ability to process and integrate text, images, and audio to explore new dimensions of data analysis and interpretation.
Future research and development
Cono’s capabilities also open new avenues for research in AI and data science. Future developments could focus on enhancing its multimodal integration, improving its contextual understanding for even longer documents, and expanding its training on diverse datasets to further improve its versatility and accuracy.
Researchers can explore how Cono’s multimodal processing can be applied to more sophisticated tasks, such as sentiment analysis across different media types, real-time translation and summarization of multimedia content, and more advanced predictive analytics.