2022年6月10日 · In this article, we have presented the CDAC AI life cycle for the design, development, and deployment of AI systems and solutions, preceded by a preliminary risk assessment for the adoption of AI. The life cycle consists of three phases (design, develop, and deploy) and 19 constituent stages across the three phases from conception to production.

2023年3月14日 · Knowledge plays a critical role in artificial intelligence. Recently, the extensive success of pre-trained language models (PLMs) has raised significant attention about how knowledge can be acquired, maintained, updated and used by language models.

2025年2月24日 · Understanding the knowledge life cycle in AI is essential for organizations looking to leverage AI technologies for improved knowledge management. By focusing on each stage of the cycle and ensuring user involvement, organizations can enhance their knowledge quality and drive better decision-making processes.

2025年2月4日 · AI must transform data into structured knowledge. KR achieves this by defining formats and methods for organizing information. With clear representations, AI systems solve problems, make decisions, and learn from new experiences. Knowledge and intelligence in AI share a symbiotic relationship:

This paper presents the ‘‘CDAC AI life cycle,’’ a comprehensive life cycle for the design, development, and deployment of artificial intelligence (AI) systems and solutions. It addresses the void of a practical and inclu-sive approach that spans beyond the technical constructs to also focus on the challenges of risk analysis of

2025年3月6日 · The knowledge life cycle in Explainable Artificial Intelligence (XAI) encompasses several critical phases that ensure the effective development and application of AI models. This cycle is essential for maintaining the integrity and interpretability of AI systems.

2022年4月1日 · This paper presents the “CDAC AI life cycle,” a comprehensive life cycle for the design, development, and deployment of artificial intelligence (AI) systems and solutions.

The AI knowledge cycle is a critical framework that outlines how artificial intelligence systems learn, adapt, and improve over time. This cycle emphasizes the importance of data quality and expert knowledge in developing effective AI models.

2024年11月19日 · In short, a well-defined AI life cycle can help teams plan their AI projects more effectively, maximizing their chances of success while minimizing potential hurdles. An Example AI Project Life Cycle

2021年8月30日 · Drawing on our experience of more than a decade of AI in academic research, technology development, industry engagement, postgraduate teaching, doctoral supervision and organisational consultancy, we present the 'CDAC AI Life Cycle', a comprehensive life cycle for the design, development and deployment of Artificial Intelligence (AI) systems and...