Charting the Path Forward: An In-Depth Analysis of Breakthroughs and Hurdles in Artificial Intelligence

Year : 2025 | Volume : 12 | Issue : 01 | Page : 13 23
    By

    Mohd. Wasiullah,

  • Piyush Yadav,

  • Ankit Yadav,

  1. Principal, Department. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  2. Academic Head, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  3. Scholar, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India

Abstract

Recent years have witnessed tremendous progress in artificial intelligence (AI), fueled by exponential increases in processing power and data accessibility. These developments have made it possible for AI to be widely used in a variety of industries, such as healthcare, finance, autonomous driving, and more. Significant difficulties are presented by the “black-box” nature of many AI systems, which lack transparency and the capacity to explain. By encouraging algorithms that can display their internal workings and decision-making, Explainable AI (XAI) seeks to address this. Notwithstanding notable advancements, issues like security, evaluation techniques, and the trade-off between performance and explainability still exist. The potential and limitations of AI technologies are highlighted in this review, which examines the most recent advancements in the field with an emphasis on approaches, applications, and the continuous attempts to overcome these obstacles. AI has quickly emerged as a revolutionary force, influencing many areas of our daily routines, including the way we interact, work, and live. This thorough analysis explores the notable developments and enduring difficulties in AI, providing a fair assessment of both its enormous potential and intrinsic complexity. Benefit: AI has advanced remarkably in recent years, especially thanks to advancements in deep learning and machine learning. These developments allow AI systems to process large volumes of data, identify complex patterns, and make highly precise judgments. Applications of AI are found in a wide range of industries, including healthcare, where it helps with early disease detection and individualized treatment plans, and finance, where it improves risk management and fraud detection. AI has made notable advancements in transportation, with key examples including autonomous vehicles and smart traffic management systems. AI-powered personalized learning experiences have revolutionized education as well.

Keywords: Artificial Intelligence (AI), machine learning (ML), deep learning (DL), neural networks, natural language processing (NLP)

[This article belongs to Recent Trends in Parallel Computing ]

How to cite this article:
Mohd. Wasiullah, Piyush Yadav, Ankit Yadav. Charting the Path Forward: An In-Depth Analysis of Breakthroughs and Hurdles in Artificial Intelligence. Recent Trends in Parallel Computing. 2025; 12(01):13-23.
How to cite this URL:
Mohd. Wasiullah, Piyush Yadav, Ankit Yadav. Charting the Path Forward: An In-Depth Analysis of Breakthroughs and Hurdles in Artificial Intelligence. Recent Trends in Parallel Computing. 2025; 12(01):13-23. Available from: https://journals.stmjournals.com/rtpc/article=2025/view=193067


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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 14/12/2024
Accepted 04/01/2025
Published 08/01/2025
230

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