AI Pipeline

An AI pipeline encompasses the entire process of developing and deploying artificial intelligence systems, from data acquisition and preprocessing to model training, evaluation, and deployment. Current research emphasizes automating this pipeline, often leveraging large language models (LLMs) and multi-agent frameworks to manage complex tasks like model selection and hyperparameter tuning, while also addressing ethical considerations such as fairness, privacy, and bias mitigation. This focus on automation and responsible AI development aims to improve efficiency, accessibility, and trustworthiness across diverse applications, ranging from biomedical research and financial modeling to digital twinning and cybersecurity.