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
Artificial Intelligence (AI) has become a transformative technology for enhancing Intelligent Decision Support Systems (IDSS) by enabling accurate, adaptive, and data-driven decision-making across diverse computer science applications. This review examines 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. It further discusses emerging trends such as human-centered AI, edge AI, federated learning, digital twins, hybrid AI models, and responsible AI that are reshaping intelligent decision-making. The review also highlights the applications of AI-enabled IDSS in cybersecurity, software engineering, cloud computing, the Internet of Things, healthcare informatics, robotics, big data analytics, smart manufacturing, and education technologies. In addition, key challenges related to data quality, explainability, scalability, privacy, ethics, computational complexity, and user trust are critically discussed, followed by future research directions emphasizing foundation models, neuro-symbolic AI, Green AI, Quantum AI, AI governance, and autonomous decision intelligence. Overall, the review provides a comprehensive overview of recent advancements and identifies promising opportunities for developing trustworthy and efficient AI-driven intelligent decision support systems.
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
Artificial intelligence (AI) fundamentally alters how humans interact with technology, moving from static systems to algorithms capable of autonomous reasoning and problem-solving. This article examines the practical realities of AI implementation in modern society, focusing specifically on the evolution and application of voice assistants. By tracing the development of major platforms like Siri, Alexa, Google Assistant, and Cortana, the study evaluates how these tools simplify human-computer interaction, automate daily routines, and improve access to information. The primary aim of this research is to analyze the modern applications of AI voice assistants in public and private life. The study identifies the core technological mechanisms driving these systems, assesses their current areas of application, and measures their role in accelerating broader digital transformation. While the findings confirm that AI heavily fosters innovation and enhances operational efficiency, they also highlight critical vulnerabilities. The widespread adoption of voice technologies introduces significant security, privacy, and ethical concerns. Ultimately, the article argues 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
