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.
Mohd. Wasiullah,
Piyush Yadav,
Ankit Yadav,
- Principal, Dept. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
- Academic Head, Dept. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
- Scholar, Dept. 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. Artificial intelligence (AI) 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 (DL) and machine learning (ML). 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, Neural Networks, Natural Language Processing (NLP)
[This article belongs to Recent Trends in Parallel Computing (rtpc)]
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):-.
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):-. Available from: https://journals.stmjournals.com/rtpc/article=2025/view=193067
References
- Zamindar A. Artificial intelligence in self-driving cars research and innovation. Int Res J Mod Eng Technol Sci. 2022;4(3):889-96.
- Collins C, Dennehy D, Conboy K, Mikalef P. Artificial intelligence in information systems research: A systematic literature review and research agenda. Int J Inf Manag. 2021 Oct 1;60:102383.
- Shukla SS, Vijay J. Applicability of artificial intelligence in different fields of life. Int J Sci Eng Res. 2013;1(1):28-35.
- Medhi U. A case study on applications of artificial intelligence in human life. Int J Biotechnol Biomed Sci. 2020;6(2):18-25.
- Theodosiou AA, Read RC. Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician. J Infect. 2023 Jul 17.
- Ray S, Sikdar DP. Artificial intelligence in education: Navigating the nexus of innovation and ethics for future learning landscapes. Int J Res Granthaalayah. 2023;11(12):163-74.
- Verma M. Artificial intelligence and its scope in different areas with special reference to the field of education. Online Submiss. 2018 Jan;3(1):5-10.
- Patel RB, SS. Concept, uses, advantages and limitations of artificial intelligence in education. Int J Creat Res Thoughts. 2022;140-6.
- Parveen S, Chadha RS, Noida C, Kumar IP, Singh J. Artificial intelligence in transportation industry. Int J Innov Sci Res Technol. 2022;7:1274-83.
- Soori M, Arezoo B, Dastres R. Artificial intelligence, machine learning and deep learning in advanced robotics: A review. Cogn Robot. 2023 Jan 1;3:54-70.
- Mudakavi AM, Mudakavi LV, Kataraki P, Desai SM, Jarali V. Review paper on deep fake detection using deep learning. Int J Res Publ Rev. 2023;4(12):3055-9.
- Lalwani T, Bhalotia S, Pal A, Rathod V, Bisen S. Implementation of a chatbot system using AI and NLP. Int J Innov Res Comput Sci Technol. 2018 May 31;6(3).
- Lakshmi GV, Sharada N. Artificial intelligence-based pattern recognition. SSRN 3540843. 2019 Apr.
- Marda V. Artificial intelligence policy in India: A framework for engaging the limits of data-driven decision-making. Philos Trans R Soc A Math Phys Eng Sci. 2018 Nov 28;376(2133):20180087.
- Bezboruah T, Bora A. Artificial intelligence: The technology, challenges and applications. Trans Mach Learn Artif Intell. 2020 Nov;8(5):44-51.
- Doohan NV, Kadam S, Phursule R, Wadne VS, Junnarkar A. Implementation of AI-based safety and security system integration for smart city. Int J Electr Electron Res. 2022.
- Behailu Y. The impact of artificial intelligence on society. Int Res J Mod Eng Technol Sci. 2023;5(10):3120-5.
- Bezboruah T, Bora A. Artificial intelligence: The technology, challenges and applications. Trans Mach Learn Artif Intell. 2020 Nov;8(5):44-51.
- Da K, Cheng G. Discussion on philosophy of information and artificial intelligence. In: Joint Int Adv Eng Technol Res Conf. 2018 Mar;442-5.
- Gupta R. Research paper on artificial intelligence. Log Tech Comput Sci. 2024 Sep 9;2(2):60-1.
- Slimi Z, Carballido BV. Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global AI ethics policies. TEM J. 2023 May 1;12(2).
- Safdar NM, Banja JD, Meltzer CC. Ethical considerations in artificial intelligence. Eur J Radiol. 2020 Jan 1;122:108768.
- Bousmaha WL. Exploring the benefits of artificial intelligence (AI) in developing applications for humans. United Int J Res Technol. 2023;4(5):122-5.
- Mar W, Thaw YM. An analysis of benefits and risks of artificial intelligence. Int J Trend Sci Res Dev. 2019 Aug;3(5):2456-6470.
- Nadimpalli M. Artificial intelligence risks and benefits. Int J Innov Res Sci Eng Technol. 2017 Jun;6(6).
- Behailu Y. The impact of artificial intelligence on society. Int Res J Mod Eng Technol Sci. 2023;5(10):3120-5.
- Molfino R, Cepolina FE, Cepolina E, Cepolina EM, Cepolina S. Robots trends and megatrends: Artificial intelligence and the society. Ind Robot. 2024 Jan 26;51(1):117-24.
- Chopra R. Artificial intelligence in robotics: A review paper. Int J Res Appl Sci Eng Technol. 2023;11(4):2345-9.
- Achary R. Artificial intelligence transforming Indian banking sector. Int J Econ Manag Syst. 2021 Aug 3;6.
- Karnati A, Mehta D. Artificial intelligence in self-driving cars: Applications, implications and challenges. Ushus J Bus Manag. 2022 Oct 1;21(4).
Recent Trends in Parallel Computing
Volume | 12 |
Issue | 01 |
Received | 14/12/2024 |
Accepted | 04/01/2025 |
Published | 08/01/2025 |