Artificial intelligence: A powerful paradigm for scientific research
Искусственный интеллект: мощная парадигма для научных исследований
2021-10-28
SCID: 54.1/ygey5ubt
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artificial intelligencefundamental scienceshigh-throughput data analysismachine learningscientific research
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Abstract (AI)
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.
Key Findings
1
AI and machine-learning techniques are increasingly transforming fundamental sciences by extracting insights from high-throughput data, enabling categorization, prediction, and evidence-based decisions.
2
Integration of AI into fundamental sciences is generating new research trends and opportunities for novel applications and sustainable scientific development.
3
The paper provides broad research guidance intended to help researchers understand state-of-the-art AI applications and advance AI-enabled fundamental sciences.
4
The paper surveys AI applications across information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry.
5
The survey identifies discipline-specific scientific challenges and discusses how AI methods can address them across diverse fundamental-science fields.
Research Object
Integration and application of artificial intelligence (AI) and machine learning (ML) techniques in fundamental scientific disciplines
Research Subject
The capabilities, challenges, applications, and emerging research trends of AI techniques for analyzing data and advancing fundamental sciences
Publication Details
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2021-10-28
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