👉 Retrieval computing is an advanced approach to artificial intelligence that focuses on efficiently accessing and utilizing pre-existing knowledge or data stored in external memory or databases, rather than relying solely on training a model from scratch. This method significantly reduces the computational resources and time required for tasks such as natural language processing, image recognition, or decision-making by leveraging the power of large-scale data storage and retrieval systems. Instead of generating new knowledge during inference, retrieval computing selects the most relevant information from these external sources, applying it to the current task with minimal processing overhead. This approach is particularly valuable in scenarios where real-time decision-making is critical, and the cost of training new models is prohibitive. By combining the efficiency of retrieval with the flexibility of machine learning, retrieval computing aims to create more practical and scalable AI systems.
