Harnessing AI to help solve some of the world’s greatest challenges
SPARROW, developed by Microsoft’s AI for Good Lab, is an AI-powered edge computing solution designed to monitor and protect wildlife in the most remote regions of the world. Solar-powered and equipped with advanced sensors, it collects biodiversity data—from camera traps, acoustic monitors,…
Open Source fuels the AI for Good Lab’s mission by providing research tools, data, and code that drive innovation, foster collaboration, and enhance accessibility for the global community. Explore our full library of resources to start building and collaborating today.
This framework aims to assist in the documentation of datasets to promote transparency and help dataset creators and consumers make informed decisions. You can read more about it in our paper: Open Datasheets: Machine-readable Documentation for Open Datasets and Responsible AI…
Assistive software applications have been developed for a variety of day-to-day tasks, including currency recognition. BankNote-Net is an open dataset for assistive currency recognition.
Code supplementing AI for Good Lab’s work on long COVID sequelae using EHR data. This project aimed to discover long COVID sequelae (symptoms) from Electronic Health Records (EHR) data using causal impact analysis of time series and analyze its association with…
This repository contains code for an active learning (opens in new tab) pipeline for detecting whales in high-resolution satellite imagery.
Mapping electrical infrastructure can support measuring access to electricity and can help identify opportunities to improve or extend existing power infrastructure.
This project automates the identification of buildings and solar panels in aerial imagery, aiding humanitarian mapping. In many developing regions, maps are often outdated or missing, hindering development planning and disaster response. Our work accelerates the creation of up-to-date maps,…
This repository contains code for running a giraffe keypoint detection model. The model estimates 4 keypoint locations in images containing a single giraffe, namely: top of ossicone, top of head, neck indent, and front bottom hoof.
