Jupyter notebooks have evolved into powerful platforms for complex data analysis and AI development, requiring significant computational power. Traditional approaches of having dedicated GPU workstations or clusters come with challenges such as high upfront costs, underutilization during off-peak times, difficulty in scaling resources up or down based on project needs, and maintenance headaches. However, a serverless platform like Modal's provides flexible on-demand GPU resources, eliminating these challenges by allowing users to spin up and down resources as needed. With the installation of the Modal Python package and authentication with the platform, users can launch Jupyter notebooks backed by Modal GPUs in seconds, providing a seamless and scalable solution for demanding computations.