AfirkaLLM Part 4: What is still missing, and where you come in
The biggest gap is data that was never online. If you speak an African language or hold text in one, this part is for you.
Advancing Data Science and Natural Language Processing for African languages and societal impact
We bridge the gap between cutting-edge data science research and real-world societal challenges, with a special focus on African language technologies.
Research that drives meaningful change in society
Developing methods and tools that enhance decision-making capabilities while ensuring user-centered approaches to data science research.
Advancing natural language processing for African languages through innovative tools, datasets, and methodologies.
Developing ML approaches that address real-world challenges while considering ethical and societal implications.
Our latest contributions to the scientific community
Our research spans multiple domains, from developing language technologies for under-resourced African languages to creating data-driven solutions for societal challenges. We publish in top-tier venues and actively contribute to open science through our datasets, models, and tools.
We believe in open science and making our work accessible to all
Curated datasets for African language research and social impact studies
Open-source tools and pre-trained models for researchers worldwide
Comprehensive guides and tutorials for using our resources
Machine translation platform for African languages, making communication across language barriers more accessible.
Grassroots organization focused on advancing NLP research and applications for African languages.
Comprehensive data repository tracking COVID-19 in South Africa, supporting research and policy decisions.
The biggest gap is data that was never online. If you speak an African language or hold text in one, this part is for you.
PhD student Thapelo Sindane visits the Responsible AI Lab at KNUST, presents his SASL research, and reflects on collaboration between RAIL, MCAAI and DSFSI.
PhD student Thapelo Sindane visits the Maseno Centre for Applied AI in Kenya to give a guest lecture, join a sign-language panel and share his SASL research.
How a university lab trains a model on borrowed compute, and why every dataset we touch stays on its owner's terms.
Interested in contributing to cutting-edge research that makes a difference? We welcome collaboration and new members.
© Data Science for Social Impact - University of Pretoria | Advancing Data Science for Social Impact