👉 Looked computing, also known as human-in-the-loop or interactive machine learning, is a paradigm where human input and oversight are integral to the machine learning process. Unlike traditional machine learning, which relies solely on algorithms and large datasets for training, looked computing involves humans actively participating in various stages of model development, validation, and refinement. This can include providing feedback on model predictions, labeling data, correcting errors, and guiding the learning process to improve accuracy and relevance. By integrating human intelligence with computational power, looked computing aims to enhance the robustness, adaptability, and trustworthiness of AI systems, making them more aligned with human needs and expectations.
