Abstract

Artificial intelligence (AI) is a rapidly evolving field of technology that involves the development of intelligence that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and making decisions based on data. This paper explores the relation of AI and scientific research. AI facilitates the extraction of meaningful insights from large datasets, enabling researchers to uncover patterns, correlations, and trends that might otherwise remain obscured. Moreover, Artificial intelligence aids in predictive analytics, allowing scientists to forecast outcomes and identify potential areas for further investigation. Additionally, AI systems are increasingly employed in experimental design and optimization, streamlining processes and enhancing efficiency in laboratory settings. Despite its myriad benefits, the integration of AI into scientific research presents challenges related to data quality, interpretability, and ethical considerations.
Artificial Intelligence (AI) is a branch of computer science that focuses on creating intelligent programs (systems) capable of performing tasks traditionally requiring human intelligence. AI systems can learn from data, identify patterns and make decisions with minimal or no human intervention. By combining sophisticated algorithms with powerful computing resources, these systems can process large amounts of information quickly and accurately. This makes them invaluable tools for scientists in many fields who must analyse complex datasets or generate predictions about future events. For example, AI has been used by researchers studying climate change as it allows them to run simulations faster than ever and gain insights into the impact of (Sreenu , 2023)