👉 Shaft computing is an innovative approach to artificial intelligence that focuses on creating efficient, specialized AI models optimized for specific tasks rather than general-purpose models. It leverages a modular architecture where each component, or "shaft," is designed to handle particular aspects of intelligence, such as natural language understanding, reasoning, or perception. These shafts are interconnected and can be dynamically configured and updated, allowing for flexible and scalable AI systems. By concentrating computational resources on the most relevant parts of a task, Shaft computing aims to reduce energy consumption and improve performance, making AI more accessible and practical for real-world applications. This method also facilitates continuous learning and adaptation, as shafts can be updated independently without disrupting the entire system.
