AI in Creative Industries: Redefining Art, Music

Main Article Content

Prof. Payal Davuluri

Abstract

Artificial Intelligence is transforming creative industries by generating art, composing music, and writing literature. This paper investigates the intersection of AI and creativity, analyzing how algorithms like GANs, transformers, and neural networks are redefining artistic expression. It explores ethical questions surrounding authorship, originality, and the societal impact of AI-generated content. Case studies illustrate the potential of AI to complement human creativity, while recommendations are made for fostering collaboration between AI and artists.

Article Details

How to Cite
Davuluri , P. P. (2022). AI in Creative Industries: Redefining Art, Music. International Journal of Computer Vision and Computer Science, 4(4). Retrieved from https://ijaisd.com/index.php/IJCVCS/article/view/8
Section
Articles

References

Davuluri, M. (2022). Comparative Study of Machine Learning Algorithms in Predicting Diabetes Onset Using Electronic Health Records. Research-gate journal, 8(8).

Davuluri, M. (2020). AI-Driven Predictive Analytics in Patient Outcome Forecasting for Critical Care. Research-gate journal, 6(6).

Davuluri, M. (2018). Revolutionizing Healthcare: The Role of AI in Diagnostics, Treatment, and Patient Care Integration. International Transactions in Artificial Intelligence, 2(2).

Vattikuti, M. C. (2022). Comparative Analysis of Deep Learning Models for Tumor Detection in Medical Imaging. Research-gate journal, 8(8).

Vattikuti, M. C. (2020). A Comprehensive Review of AI-Based Diagnostic Tools for Early Disease Detection in Healthcare. Research-gate journal, 6(6).

Vattikuti, M. C. (2018). Leveraging Edge Computing for Real-Time Analytics in Smart City Healthcare Systems. International Transactions in Artificial Intelligence, 2(2).

Vattikuti, M. C. (2018). Leveraging AI for Sustainable Growth in AgTech: Business Models in the Digital Age. Transactions on Latest Trends in IoT, 1(1), 100-105.

Kolla, V. R. K. (2018). Forecasting the Future: A Deep Learning Approach for Accurate Weather Prediction. International Journal in IT & Engineering (IJITE).

Kolla, V. R. K. (2016). Analyzing the Pulse of Twitter: Sentiment Analysis using Natural Language Processing Techniques. International Journal of Creative Research Thoughts.

Kolla, V. R. K. (2015). Heart Disease Diagnosis Using Machine Learning Techniques In Python: A Comparative Study of Classification Algorithms For Predictive Modeling. International Journal of Electronics and Communication Engineering & Technology.

Kolla, V. R. K. (2020). Paws And Reflect: A Comparative Study of Deep Learning Techniques For Cat Vs Dog Image Classification. International Journal of Computer Engineering and Technology.

Kolla, V. R. K. (2016). Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling. International Journal of Information Technology & Management Information System.

Kolla, V. R. K. (2021). Cyber security operations centre ML framework for the needs of the users. International Journal of Machine Learning for Sustainable Development, 3(3), 11-20.

Velaga, S. P. (2017). “ROBOTIC PROCESS AUTOMATION (RPA) IN IT: AUTOMATING REPETITIVE TASKS AND IMPROVING EFFICIENCY. IEJRD-International Multidisciplinary Journal, 2(6), 9.

Velaga, S. P. (2018). AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS. International Journal of Innovations in Engineering Research and Technology, 5(2), 78-85.

Velaga, S. P. (2020). AIASSISTED CODE GENERATION AND OPTIMIZATION: LEVERAGING MACHINE LEARNING TO ENHANCE SOFTWARE DEVELOPMENT PROCESSES. International Journal of Innovations in Engineering Research and Technology, 7(09), 177-186.

Gatla, T. R. (2017). A SYSTEMATIC REVIEW OF PRESERVING PRIVACY IN FEDERATED LEARNING: A REFLECTIVE REPORT-A COMPREHENSIVE ANALYSIS. IEJRD-International Multidisciplinary Journal, 2(6), 8.

Gatla, T. R. (2019). A CUTTING-EDGE RESEARCH ON AI COMBATING CLIMATE CHANGE: INNOVATIONS AND ITS IMPACTS. INNOVATIONS, 6(09).

Gatla, T. R. “A GROUNDBREAKING RESEARCH IN BREAKING LANGUAGE BARRIERS: NLP AND LINGUISTICS DEVELOPMENT. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.

Gatla, T. R. (2018). AN EXPLORATIVE STUDY INTO QUANTUM MACHINE LEARNING: ANALYZING THE POWER OF ALGORITHMS IN QUANTUM COMPUTING. International Journal of Emerging Technologies and Innovative Research (www. jetir. org), ISSN, 2349-5162.

Gatla, T. R. MACHINE LEARNING IN DETECTING MONEY LAUNDERING ACTIVITIES: INVESTIGATING THE USE OF MACHINE LEARNING ALGORITHMS IN IDENTIFYING AND PREVENTING MONEY LAUNDERING SCHEMES (Vol. 6, No. 7, pp. 4-8). TIJER–TIJER–INTERNATIONAL RESEARCH JOURNAL (www. TIJER. org), ISSN: 2349-9249.

Pindi, V. (2018). NATURAL LANGUAGE PROCESSING(NLP) APPLICATIONS IN HEALTHCARE: EXTRACTING VALUABLE INSIGHTS FROM UNSTRUCTURED MEDICAL DATA. International Journal of Innovations in Engineering Research and Technology, 5(3), 1-10.

Pindi, V. (2019). A AI-ASSISTED CLINICAL DECISION SUPPORT SYSTEMS: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT RECOMMENDATIONS. International Journal of Innovations in Engineering Research and Technology, 6(10), 1-10.

PINDI, V. (2022). ETHICAL CONSIDERATIONS AND REGULATORY COMPLIANCE IN IMPLEMENTING AI SOLUTIONS FOR HEALTHCARE APPLICATIONS. IEJRD-International Multidisciplinary Journal, 5(5), 11.

DEEKSHITH, A. (2018). Seeding the Future: Exploring Innovation and Absorptive Capacity in Healthcare 4.0 and HealthTech. Transactions on Latest Trends in IoT, 1(1), 90-99.

DEEKSHITH, A. (2017). Evaluating the Impact of Wearable Health Devices on Lifestyle Modifications. International Transactions in Artificial Intelligence, 1(1).

DEEKSHITH, A. (2016). Revolutionizing Business Operations with Artificial Intelligence, Machine Learning, and Cybersecurity. International Journal of Sustainable Development in computer Science Engineering, 2(2).

DEEKSHITH, A. (2015). Exploring the Foundations, Applications, and Future Prospects of Artificial Intelligence. International Journal of Sustainable Development in computer Science Engineering, 1(1).

DEEKSHITH, A. (2014). Neural Networks and Fuzzy Systems: A Synergistic Approach. Transactions on Latest Trends in Health Sector, 6(6).

Boppiniti, S. T. (2021). Real-time data analytics with ai: Leveraging stream processing for dynamic decision support. International Journal of Management Education for Sustainable Development, 4(4).

Boppiniti, S. T. (2022). Exploring the Synergy of AI, ML, and Data Analytics in Enhancing Customer Experience and Personalization. International Machine learning journal and Computer Engineering, 5(5).

Boppiniti, S. T. (2019). Machine Learning for Predictive Analytics: Enhancing Data-Driven Decision-Making Across Industries. International Journal of Sustainable Development in Computing Science, 1(3).

Boppiniti, S. T. (2020). Big Data Meets Machine Learning: Strategies for Efficient Data Processing and Analysis in Large Datasets. International Journal of Creative Research In Computer Technology and Design, 2(2).

Dhaiya, S., Pandey, B. K., Adusumilli, S. B. K., & Avacharmal, R. (2021). Optimizing API Security in FinTech Through Genetic Algorithm based Machine Learning Model.

Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.

Sarkar, R., Malini, T. N., Adusumilli, S. B. K., Jena, M. S., & Patra, J. P. AI-INFUSED BLOCKCHAIN INNOVATIONS IN MANUFACTURING SUPPLY CHAINS FOR ECO-FRIENDLY PRACTICES TOWARDS A SUSTAINABLE FUTURE.