​​​I​ntelligent Systems: A study on AI and Machine learning

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 01 | Page :
    By

    Kartik Singh Jadon,

  • Indresh Sharma,

  • Khwaish saini,

  • Aisha Rafi,

  1. Student, Artificial Intelligence And Data Science(AI&DS) Poornima Institute Of Engineering And Technology Jaipur, Rajasthan, India
  2. Student, Artificial Intelligence And Data Science(AI&DS) Poornima Institute Of Engineering And Technology Jaipur, Rajasthan, India
  3. Student, Artificial Intelligence And Data Science(AI&DS) Poornima Institute Of Engineering And Technology Jaipur, Rajasthan, India
  4. Assistant Professor, Artificial Intelligence And Data Science(AI&DS) Poornima Institute Of Engineering And Technology Jaipur, Rajasthan, India

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are dynamic branches of computer science that focus on developing systems capable of executing tasks commonly associated with human intelligence. These activities encompass making choices, resolving issues, understanding language, identifying patterns, and learning through experience. Artificial Intelligence refers to the broad area of designing systems and frameworks that enable machines to perform tasks resembling human thought and behavior. This field integrates diverse technologies such as machine learning, language interpretation, robotics, and visual data processing. AI applications range from simple tasks, such as recommendations on streaming services, to complex ones, like autonomous driving vehicles. Machine Learning, a subset of Artificial Intelligence, focuses on developing algorithms that allow computers to recognize patterns and make informed decisions using data, without the need for detailed programming for every task. These algorithms enhance their accuracy by learning from past experiences and continuously optimizing their results. The field includes several methodologies—such as supervised, unsupervised, and reinforcement learning—each designed to address different types of challenges and data formats. The integration of AI and ML into various sectors has led to significant advancements, including improved healthcare diagnostics, enhanced customer service through chatbots, efficient data analysis, and automation of routine tasks. However, it also poses ethical and societal challenges, such as job displacement, privacy concerns, and ensuring fairness in AI algorithms. Overall, AI and ML represent transformative technologies that are reshaping industries, augmenting human capabilities, and opening new frontiers in scientific research and innovation.

Keywords: Artificial Intelligence, Machine Learning, Bias, Supervised Learning, Unsupervised Learning

How to cite this article:
Kartik Singh Jadon, Indresh Sharma, Khwaish saini, Aisha Rafi. ​​​I​ntelligent Systems: A study on AI and Machine learning. Journal of Artificial Intelligence Research & Advances. 2026; 13(01):-.
How to cite this URL:
Kartik Singh Jadon, Indresh Sharma, Khwaish saini, Aisha Rafi. ​​​I​ntelligent Systems: A study on AI and Machine learning. Journal of Artificial Intelligence Research & Advances. 2026; 13(01):-. Available from: https://journals.stmjournals.com/joaira/article=2026/view=237209


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Ahead of Print Subscription Review Article
Volume 13
01
Received 05/04/2025
Accepted 29/07/2025
Published 19/02/2026
Publication Time 320 Days
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