GPT & Generative AI and LLMs! @starconfs #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode cstar.global geni.us/Gen-AI-LLMs References Li, C., Wang, J., Zhang, Y., Zhu, K., Hou, W., Lian, J., Luo, F., Yang, Q., & Xie, X. (2023, July 14). Large Language Models Understand and Can be Enhanced by Emotional Stimuli. arXiv. Retrieved December 19, 2023, from arxiv.org/abs/2307.11760 Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022, January 28). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. arXiv. Retrieved December 19, 2023, from arxiv.org/abs/2201.11903 Xu, B., Yang, A., Lin, J., Wang, Q., Zhou, C., Zhang, Y., & Mao, Z. (2023, May 24). ExpertPrompting: Instructing Large Language Models to be Distinguished Experts. arxiv.org/abs/2305.14688. Retrieved December 19, 2023, from arxiv.org/abs/2305.14688 Zhu, K., Wang, J., Zhou, J., Wang, Z., Chen, H., Wang, Y., Yang, L., Ye, W., Zhang, Y., Gong, N., & Xie, X. (2023, June 7). Toward Evaluating the Robustness of Large Language Models on Adversarial Prompts. https://arxihttps://arxiv.org/abs/2305.14688December 19, 2023, from arxiv.org/abs/2306.04528