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@article{159013,
        author = {Vijay Kumar Sahu},
        title = {Exploring the Capabilities of Chat GPT: A Study of Natural Language Processing and Generative Text Generation},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {243-246},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159013},
        abstract = {In this study, we explore the capabilities of Chat GPT, a variant of the transformer-based language model GPT-3, for natural language processing and generative text generation in the context of conversational agents. Chat GPT is trained on a small dataset of conversational text and is able to generate responses to user input in real-time. We compare Chat GPT's performance to state-of-the-art conversational agents on various benchmarks and find that it performs comparably, while requiring significantly less data and training time. Our results demonstrate the potential of Chat GPT for efficient and effective natural language processing and generative text generation in the field of conversational agents.},
        keywords = {Natural Language Processing (NLP),  Generative Text Generation, Chat GPT,  Artificial Intelligence (AI),  Machine Learning (ML), Language Understanding.},
        month = {},
        }