AI Model

AI models are computational systems designed to perform tasks that typically require human intelligence, with current research heavily focused on improving their accuracy, efficiency, and fairness. Key areas of investigation include developing robust model architectures (like transformers and vision transformers), mitigating biases through techniques such as federated learning and adversarial debiasing, and enhancing explainability to build trust and facilitate human-AI collaboration. These advancements hold significant implications for diverse fields, from healthcare (e.g., improved diagnostics and risk prediction) to scientific discovery (e.g., accelerated research processes) and fraud detection, ultimately impacting both scientific understanding and practical applications.