How can we democratize the development of geospatial machine learning models, lower the barrier to entry for students and practitioners in this space, and obliterate the ‘practice’ of geospatial platform commercialization? Leveraging OSM vector data and cloud compute, through such programs such as the University of Washington’s GeoHackweek, we are able to further the removal of the knowledge barrier for scaling ML applications and flood a commercialized marketplace with models leverage-able by a broader community. If theoretically coupled with virtual (or real) incentivization or enhanced social currency, this approach could advance stagnant geospatial activities and create a community invested in producing optimal solutions that become foundational to advanced endeavors.