Jul 2026· International Journal of Scientific Research in Artificial Intelligence and Machine Learning· Vol 2, pp. 16-21· 0 citations· 10 references
TL;DR
An overview of artificial intelligence is presented by discussing its fundamental concepts, definitions, historical evolution, key characteristics, major applications, recent advancements, and notable achievements.
Abstract
Artificial Intelligence (AI) is a multidisciplinary field focused on designing and developing intelligent systems capable of performing tasks that typically require human intelligence. It encompasses the creation of smart computer programs that can perceive, reason, learn, and make decisions. Although AI draws inspiration from the study of human intelligence, it is not restricted to biologically inspired methods or processes. Despite the absence of a universally accepted definition, AI is generally recognized as the study of computational techniques that enable machines to perceive their environment, reason logically, and take appropriate actions. In the modern digital era, the volume of data generated by humans and machines has increased dramatically, surpassing the capacity of individuals to efficiently process, analyze, and make informed decisions based on such information. AI addresses this challenge by enabling computers to learn from data, identify patterns, and support intelligent decision-making. As a result, artificial intelligence has become a fundamental technology driving automation, data analysis, and advanced computing applications across numerous industries. This paper presents an overview of artificial intelligence by discussing its fundamental concepts, definitions, historical evolution, key characteristics, major applications, recent advancements, and notable achievements.
This paper offers significantly crucial insights into how scientific research can be streamlined through the utilization of several AI-powered applications while maintaining the academically and methodologically agreed-upon standards and ethics.
M. Sabour· American Journal of Educatio...· 0 citations
An Algorithm-to-Intelligence Integration Framework is proposed that connects computer science foundations, artificial intelligence paradigms, system requirements, application domains, and future technologies to achieve responsible, secure, sustainable, and deployable technological advancement.
Smitha Rajagopal, S. Nirkhi, Bharati S. Pochal et al.· Future Technology· 0 citations
The fundamental concepts of AI, its major techniques, including machine learning, deep learning, expert systems, fuzzy logic, reinforcement learning, explainable AI, and generative AI, and their roles in modern decision support systems are examined.
P. S· Journal of Intelligent Decis...· 0 citations
The sections that follow trace the historical development of AI within computer science, review the principal technique families and their applications, and close with an original discussion of cross-cutting patterns, ethical obligations, and likely future directions.
Elayaraja Subbaiah, Manykandaprebou Vaitinadin, E. Kesavan· International Journal of Sci...· 0 citations
It is argued that to maximize the benefits of AI, society must develop robust, responsible implementation mechanisms to guarantee the safe and ethical use of autonomous technologies.
Ռիմմա Ասոյան, Լիանա Ազատյան· Սոցիալ-տնտեսական զարգացման ա...· 0 citations
By explaining what is 'deep' about deep learning and showing that AI is more maths than magic, the briefing aims to equip the reader with the understanding they need to engage in clear-headed reflection about AI's opportunities and challenges.
P. Boucher· 16 citations
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