• Devansh Agarwal
• Prof. Naren J.

Non-alcoholic wine has gained increasing popularity in recent years due to the rising awareness of the health risks associated with excessive alcohol consumption. In this research paper, we explore the production of non-alcoholic wine using Generative AI, through Reinforcement Learning in text GPT models like ChatGPT. Using an experimental analysis with the help of iterative algorithms, we investigate the production process of non-alcoholic wine. Our results indicate that the production process of non-alcoholic wine involves the removal of alcohol from wine using various methods, such as vacuum distillation and reverse osmosis. These methods affect the sensory characteristics of non-alcoholic wine by altering its aroma and flavour. We also found that the grape variety, fermentation conditions, and aging process can significantly affect the sensory properties of non-alcoholic wine. Based on our findings, we recommend that producers of non-alcoholic wine pay close attention to the production process and grape selection in order to achieve desirable sensory characteristics. Furthermore, we develop syrup from this wine which has many uses, such as taste enhancers, wine substitutes, emulsifiers and reconstituted drinks.

Generative AI, Reinforcement Learning, Iterative Algorithms, GPT Models.

"The Production of Non Alcoholic Wine and Subsequent Syrups using Generative AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.c881-c886, April-2024, Available :http://www.jetir.org/papers/JETIR2404294.pdf

"The Production of Non Alcoholic Wine and Subsequent Syrups using Generative AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppc881-c886, April-2024, Available at : http://www.jetir.org/papers/JETIR2404294.pdf