We plan the growth in the use of ZK Tech both to move towards homomorphic tournaments and to make private-data-based research reproducible. Part of the finalists of the DeSci London 2023 Hackathon, our Lead Quant, Matteo Manzi, presented [our work](https://desci.crunchdao.com/projects/crunchdao/desci-london) on the use of IPFS to foster the reproducibility of machine learning papers.