CAMERA's gpCAM is an advanced Gaussian-process-driven tool for autonomous data acquisition for experiments and simulations. gpCAM combines two upstream API's (also developed by CAMERA) to deliver flexible and HPC-ready autonomous data acquisition to the scientific community. First, the Gaussian-process engine, called fvGP, uses PyTorch-accelerated linear algebra and user-defined kernel, mean, and optimization functions to provide a full Gaussian uncertainty quantification given a dataset. fvGP is able to use advanced training and prediction methods. Second, a high-performance hybrid optimizer can find regions of maximal uncertainty or knowledge gain to provide the instrument with an optimal next step. To learn more about gpCAM, please visit the website.