Revolution of Artificial Intelligence and Machine Learning

Notice

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 : 2025 | Volume : 12 | 02 | Page : –
    By

    Jasmine Kaur,

  • Arshpreet Kaur,

  • Amandeep Kaur,

  1. Student, Department of Computer Applications, BFCET College, Deon, Punjab, India
  2. Student, Department of Computer Applications, BFCET College, Deon, Punjab, India
  3. Assistant Professor, Department of Computer Applications, BFCET College, Deon, Punjab, India

Abstract

document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_197768’);});Edit Abstract & Keyword

Artificial Intelligence (AI) and Machine Learning (ML) are changing industries through the introduction of new technologies like deep learning, federated learning, reinforcement learning and natural language processes. In This paper we explore such emerging technologies in detail with their applications in various fields like healthcare, finance, and transportation, and focuses on ethical implications and challenges. It points towards future research directions in this field to provide guidance about an evolution of AI and ML towards ethical and responsible development. Strict control is necessary when AI is incorporated into many facets of society to avoid inadvertent biases, discrimination, and surveillance. It can be difficult to keep AI systems accountable, transparent, and equitable. The study discusses these issues and poses important research questions on how the AI revolution will affect privacy, ethics, labor disruptions, and society dynamics.

Keywords: Deep Learning, Federated Learning, Natural Language Processessing, Machine Learning, Reinforcement Learning

How to cite this article:
Jasmine Kaur, Arshpreet Kaur, Amandeep Kaur. Revolution of Artificial Intelligence and Machine Learning. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):-.
How to cite this URL:
Jasmine Kaur, Arshpreet Kaur, Amandeep Kaur. Revolution of Artificial Intelligence and Machine Learning. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):-. Available from: https://journals.stmjournals.com/joaira/article=2025/view=0


document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_ref_197768’);});Edit

References

  1. Grover, A., & Leskovec, J. (2016). Scalable feature learning for networks. Link
  2. Hain, D. S., & Lee, S. (2020). Machine learning and artificial intelligence for science, technology, innovation mapping and forecasting. Scientometrics. Link
  3. Swamy, J. S., Sandhya, M. U., & Ramanjanelu, K. (2024). Emerging trends in artificial intelligence and machine learning. Link
  4. Marcinkevics, R., & Vogt, J. E. (2023). Interpretable and explainable machine learning. Link
  5. Chen, X., & Zou, D. (2020). Application and theory gaps during the rise of artificial intelligence in education. Link
  6. Smith, B., & Linden, G. (2017). Two decades of recommender systems at Amazon.com. Link
  7. Lee, I., & Shin, Y. J. (2017). Fintech ecosystem: Business models, investment decisions, and challenges. Link
  8. Esteva, A., & Kuprel, B. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Link
  9. Bojarski, M., & Dworakowski, D. (2016). End to end learning for self-driving cars. Link
  10. Kavitha, T., & Manikandan, S. P. (2024). Advancements in distributed deep learning: Federated learning and its intersection with AutoML and reinforcement learning. Link
Ahead of Print Subscription Review Article
Volume 12
02
Received 11/06/2025
Accepted 30/06/2025
Published 24/07/2025
Publication Time 43 Days
82

[first_name] [last_name]

My IP

PlumX Metrics