Content Aware Studies (CAS) Series is comprised of ideas, AI experiments, objects, moving image works, films and essays. It inquires how the use of machine learning in historical analysis and reproduction as a scientific tool brings to the forefront ethical questions of bias contamination within data and automation of its analysis. Inspired by the examples of confusing para-scientific interventions such as AI-based Voynich Manuscript decryptions CAS series examines the various sides of this inquiry. It also speculates about material objects as synthetic documents of machine-rendered histories. The objects from the CAS series came through methodologies developed with data scientists and based on training artificial neural networks aiming to replenish lost fragments of sculptures, friezes and other objects of classical antiquity as well as to generate never before existing, yet “algorithmically genuine” objects of that era. The research examined outputs of advanced AI models trained on datasets consisting of thousands of 3D scans of classical sculptures from renowned international museum collections. The models generated by the algorithm were then 3D-printed in various synthetic materials, filling the voids in the eroded and damaged marble sculptures. Some of these algorithmic outputs were turned into new entire marble sculptures carved by machines. Uncanny in their algorithmic integrity, they posed questions about whether they can be considered objects of classical antiquity. They render the work of a synthetic agency that lends a faithful authenticity to the forms, while also producing bizarre errors and algorithmic normalizations of forms previously standardized and regulated by the canon of Hellenistic and Roman art. In its second iteration, CAS challenged previously established AI methodologies, against data from prehistoric and geologic time archives including first stone tools, writing systems, paleontological archives of fossilised plants, organisms and other biogenic data.