
Predicting Well Groundwater Quality Using Cloud-Based Machine Learning: DataKind San Francisco Partners with Aquaya and DataKind
A writeup of the partnership
An approach to machine learning where the data is not centralized
Federated Learning enables mobile phones to collaboratively learn a shared prediction model while keeping all the training data on device, decoupling the ability to do machine learning from the need to store the data in the cloud. This goes beyond the use of local models that make predictions on mobile devices (like the Mobile Vision API and On-Device Smart Reply) by bringing model training to the device as well.


A writeup of the partnership

A Feminist AI Research network that gathers a cohort of social scientists, economists, and activists, side by side with data, machine learning and computer scientists to discuss how to fix the system and leverage AI for women’s rights.
Conservation X Labs’ Sentinel transforms wildlife monitoring tools — like trail cameras and acoustic recorders — with revolutionary and intuitive AI technology, processing environmental data in real-time as it’s collected.

Our program mixes the best of both Washington and Silicon Valley, bringing together stakeholders in policy and technology to train the next generation of policy entrepreneurs.