Investigations into the Evolution of Generative AI

Authors

  • Xueyi Cheng Duke University

DOI:

https://doi.org/10.5281/zenodo.14003350

ARK:

https://n2t.net/ark:/40704/JCTAM.v1n4a14

Disciplines:

Artificial Intelligence

Subjects:

Artificial Neural Networks

References:

7

Keywords:

Machine Learning, Artificial Neural Networks, Genrative AI

Abstract

Machine Learning, a pivotal technology within the realm of artificial intelligence, has experienced remarkable progress in recent times. This research offers a thorough and structured presentation of machine learning. It begins with a comprehensive look at the evolution of machine learning throughout history, then zeroes in on dissecting the foundational algorithms that underpin the field. Following this, the study sheds light on the cutting-edge developments in machine learning, with the goal of thoroughly examining its applications across different sectors and contemplating the prospective trajectories for its future.

Author Biography

Xueyi Cheng, Duke University

Researcher at Duke University.

References

Che, C., Hu, H., Zhao, X., Li, S., & Lin, Q. (2023). Advancing Cancer Document Classification with R andom Forest. Academic Journal of Science and Technology, 8(1), 278-280.

Che, C., Li, C., & Huang, Z. (2024). The Integration of Generative Artificial Intelligence and Computer Vision in Industrial Robotic Arms. International Journal of Computer Science and Information Technology, 2(3), 1-9.

Lin, Q., Che, C., Hu, H., Zhao, X., & Li, S. (2023). A Comprehensive Study on Early Alzheimer’s Disease Detection through Advanced Machine Learning Techniques on MRI Data. Academic Journal of Science and Technology, 8(1), 281-285.

Che, C., Huang, Z., Li, C., Zheng, H., & Tian, X. (2024). Integrating generative AI into financial market prediction for improved decision making. Applied and Computational Engineering, 64, 155-161.

Liu, H., Wang, C., Zhan, X., Zheng, H., & Che, C. (2024). Enhancing 3D Object Detection by Using Neural Network with Self-adaptive Thresholding. arXiv preprint arXiv:2405.07479.

Huang, Z., Che, C., Zheng, H., & Li, C. (2024). Research on Generative Artificial Intelligence for Virtual Financial Robo-Advisor. Academic Journal of Science and Technology, 10(1), 74-80.

Che, C., Lin, Q., Zhao, X., Huang, J., & Yu, L. (2023, September). Enhancing Multimodal Understanding with CLIP-Based Image-to-Text Transformation. In Proceedings of the 2023 6th International Conference on Big Data Technologies (pp. 414-418).

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Published

2024-11-02

How to Cite

Cheng, X. (2024). Investigations into the Evolution of Generative AI. Journal of Computer Technology and Applied Mathematics, 1(4), 117–122. https://doi.org/10.5281/zenodo.14003350

Issue

Section

Articles

ARK