Lacuna Fund is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled data sets that address urgent problems in their communities. Launched in July 2020 with a pooled fund of CA$4 million to support the creation, expansion, and maintenance of data sets for training or evaluation of machine learning models, the Lacuna Fund will initially support the three key sectors of agriculture, health, and languages.
Agricultural AI projects across Africa have received funding from Lacuna to produce labeled training data sets for machine learning that will help alleviate food security challenges, spur economic opportunities, and give researchers, farmers, communities, and policymakers access to superior agricultural data. Projects will address a range of agricultural needs, including livestock and fisheries management, crop identification, yield estimation, and disease detection in crops that support food security efforts in the region — namely cassava, maize, beans, bananas, pearl millet, and cocoa.
"We are looking forward to working with the Lacuna Fund to increase the representation of agriculture data sets in Africa. We will be calling on the amazing data science talent from across Africa and around the world to crowdsource a machine learning solution for correcting location errors, which are a common problem in agriculture data sets,” Said Celina Lee, a funding recipient and co-founder and CEO at Zindi, a data science competition platform in Africa.