With SnapML, developers can train and leverage machine learning models to power increasingly complex solutions on Snap’s AR platform. Through hand and body tracking, audio classification, segmentation models, and more, SnapML helps accelerate AR innovation.
Through Ghost, we’re funding research that leads to new machine learning models with potential to advance AR product development.
This track is best suited for individual developers and research teams with professional-level expertise in machine learning—specifically in the fields of deep learning for computer vision, speech, audio, and natural language processing. If you or your team believe in the power of AR & ML working hand in hand and are interested in pursuing high impact R&D work, consider applying for an ML Research grant.
By the end of the term, Fellows should have a paper, notebook, or Lens Studio project that demonstrates the outcome of their research.
If you’re interested in leveraging a new or existing model to power a specific product, please apply to either the Prototype or Launch track instead.
Est. Fellowship Term: 3 Months