Artificial intelligence has made remarkable strides, but current models like LLMs struggle with real-world problems. Why? They're built for narrow tasks and can't handle the complexity of multiple data types. Imagine a doctor diagnosing a patient using only text records, ignoring lab results and medical images. That's the limitation of current AI. This research proposes a new framework called Open General Intelligence (OGI) inspired by the human brain. Instead of a single model, OGI uses specialized modules for different data types, like vision and language, connected by a dynamic processing system. This system acts like a conductor, routing information between modules and adjusting their focus based on the task. Think of it as different parts of your brain working together—your visual cortex processing images, your language center interpreting words, and your memory recalling relevant information. OGI aims to mimic this flexible, multi-modal processing to tackle complex real-world challenges. This modular design offers a path to scalable AGI, potentially revolutionizing fields like medicine, finance, and engineering. But significant challenges remain, including real-time weight control, inter-module coordination, and multi-modal processing. Building a system that seamlessly integrates these diverse components is a major hurdle. Future research will explore techniques like reinforcement learning and probabilistic modeling to enhance OGI's adaptability and decision-making in uncertain environments. The ultimate goal is to create an AI system that can learn, adapt, and solve problems with human-like flexibility, unlocking the true potential of artificial general intelligence.