Recent Advancements in Computer Science: A Comprehensive Review of Emerging Technologies and Innovations
DOI:
https://doi.org/10.36676/jrps.2023-v14i1-42Keywords:
Computer Science, Recent Advancements, Emerging Technologies, Artificial Intelligence (AI)Abstract
Recent advances in computer science have led to many new technologies and inventions that continue to affect our environment. This extensive study highlights some of the most significant computer science discoveries and their possible applications. This assessment begins with AI, which has driven many recent achievements. Cutting-edge machine learning methods, deep neural networks, reinforcement learning, and explainable AI are discussed. AI and adjacent sciences like natural language processing (NLP) and computer vision have led to innovative applications in healthcare, finance, autonomous cars, and smart cities. The second part discusses quantum computing, which promises exponentially increased processing power. Qubits were created by studying quantum physics concepts like superposition and entanglement. These qubits enable quantum computers to tackle complicated problems that traditional computers cannot. The review discusses quantum hardware, error correction, and algorithms and their potential applications. Next, blockchain technology, which has changed data management and security, is examined. Cryptocurrencies and DApps and smart contracts have grown due to blockchain's decentralisation and tamper-resistance. This section discusses new consensus techniques, scalability, and blockchain's use in supply chain management and digital identification. In this study, the Internet of Things (IoT) shows how linked gadgets have changed businesses and customer experiences. IoT, cloud, and edge computing have established an environment for real-time data processing, predictive analytics, and autonomous decision-making. Privacy, security, and standards issues are discussed. Given the growing dangers from malevolent actors in a digitalized environment, the evaluation finishes with cybersecurity advances. This section discusses improved encryption, AI-driven cybersecurity, and quantum-resistant cryptography in light of quantum computing's ability to break standard cryptographic algorithms.
References
"Virtual Reality: Concepts and Technologies" by Philippe Fuchs and Guillaume Moreau (2011).
"Augmented Reality: Principles and Practice" by Dieter Schmalstieg and Tobias Hollerer (2016).
IEEE Transactions on Visualization and Computer Graphics (TVCG).
"Green IT: Technologies and Applications" edited by Mohammad Dastbaz, et al. (2011).
"Energy-Efficient Computing and Networking" by Kerry Hinton and Samee U. Khan (2011).
"Big Data: A Revolution That Will Transform How We Live, Work, and Think" by Viktor Mayer-Schönberger and Kenneth Cukier (2013).
"Data-Intensive Text Processing with MapReduce" by Jimmy Lin and Chris Dyer (2010).
Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig (2021).
"Pattern Recognition and Machine Learning" by Christopher M. Bishop (2006).
Quantum Computing for Computer Scientists" by Noson S. Yanofsky and Mirco A. Mannucci (2008).
"Quantum Computation and Quantum Information" by Michael A. Nielsen and Isaac L. Chuang (2010).
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Re-users must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. This license allows for redistribution, commercial and non-commercial, as long as the original work is properly credited.