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ZENODO
Book . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Book . 2026
License: CC BY
Data sources: Datacite
ZENODO
Book . 2026
License: CC BY
Data sources: Datacite
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PUSHING THE BOUNDARIES OF ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE

Authors: Dhanalakshmi V; Gayathri B; Nivetha N; Anto Nibiya S;

PUSHING THE BOUNDARIES OF ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE

Abstract

Pushing the Boundaries of Artificial Intelligence and Computer Science Artificial Intelligence (AI) and Computer Science are closely interconnected disciplines, yet each has its own distinct focus. While computer science deals broadly with the design and development of computational systems, artificial intelligence centers on creating intelligent agents capable of performing tasks that typically require human intelligence. Artificial Intelligence, a term first introduced by John McCarthy in 1956, has grown into a vital area of research within computer science. It involves the development of algorithms, models, and technologies that enable machines to observe, learn, reason, and make decisions independently. By simulating human cognitive abilities, AI allows computer systems to address complex problems in a more efficient and adaptive manner. AI applications include problem-solving, decision-making, visual perception, speech recognition, and language translation. Through the use of advanced programming techniques, artificial intelligence continues to drive innovation and transformation within the field of computer science. This book explores the evolving landscape of AI and its integration with computer science, highlighting both current applications and future possibilities. It aims to provide readers with a comprehensive understanding of how AI is reshaping computational systems and pushing the boundaries of technological advancement.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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