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@article{201544,
        author = {Shivam Singgh and Shorya Gupta and Divyanshu Panwar and Naman Agarwal},
        title = {Large Al models consume huge computational power and energy.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5063-5067},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201544},
        abstract = {Today AI is doing amazing things but often at a price that nobody really seems to notice. Behind the incredibly capable language models today is a massive demand on power and compute. This paper analyses this cost up to a point. It has all done to investigate the systems such as the ones powering models such as GPT 4, PaLM 2, LLaMA 2, and Gemini Ultra. We investigate the relationship between performance and resource scale, the impact on the environment of large training runs and the hardware required. We also consider what can be done specifically including building models that are slimmer and running data centres that are greener. One number in particular stand out. The training of a single top of the line model can consume as many carbon emissions as the lifetime of a handful of cars.},
        keywords = {},
        month = {May},
        }