Nyalleng Moorosi is part of a movement aimed at involving more African voices in AI policymaking. The room is draped in white curtains, and a giant screen blinks with videos created with generative AI. A classic East African folk song by the Tanzanian singer Saida Karoli plays loudly on the speakers. Friends greet each other as waiters serve arrowroot crisps and sugary mocktails. A man and a woman wearing leopard skins atop their clothes sip beer and chat; many women are in handwoven Ethiopian garb with red, yellow, and green embroidery. "The best thing about the Indaba is always the parties," computer scientist Nyalleng Moorosi tells me.

At ICRA 2022, Benjamin Rosman delivered a keynote presentation on an organization he co-founded called "Deep learning Indaba". Deep Learning Indaba is based in South Africa and their mission is to strengthen Artificial Intelligence and Machine Learning communities across Africa. They host yearly meetups in varying countries on the continent, as well as promote grass roots communities in each of the countries to run their own local events. An indaba is a Zulu word for a gathering or meeting. Such meetings are held throughout southern Africa, and serve several functions: to listen and share news of members of the community, to discuss common interests and issues facing the community, and to give advice and coach others.

Some stood in front of posters, which wound around the tree's sprawling roots, depicting machine learning systems that promised to predict everything from soil nutrition, to whether a small-scale farmer would repay a loan, to how a self-driving car might navigate the bustling streets of Cairo. Over the last three years, academics and industry researchers from around the African continent have begun sketching the future of their own A.I. industry at a conference called Deep Learning Indaba. The conference brings together hundreds of researchers from more than 40 African countries to present their work, and discuss everything from natural language processing to A.I. ethics. Founded in 2017, Indaba is a direct response to Western academic conferences, which are often difficult for researchers from distant parts of the world to access. Take, for instance, the Conference on Neural Information Processing Systems, the most well-known meeting dedicated to artificial neural networks.

This week more than 700 machine learning researchers from over 30 African countries will come together at Kenyatta University in Nairobi, Kenya for the third annual Deep Learning Indaba. On paper it looks a lot like other artificial intelligence (AI) convenings around the world. There are keynotes from luminaries, talks from up-and-coming researchers, and trainings on new methods. But as we've worked with the Indaba organizers to sponsor the event over the last few months, we've learned that the Indaba represents so much more: First, the Indaba is a hub and catalyst for Africa's growing AI community. At The Rockefeller Foundation, we know that supporting communities of dedicated engineers can change the world.

Using machine learning to accelerate ecological research Using machine learning to accelerate ecological research Share Pushmeet Kohli * External authors The Serengeti is one of the last remaining sites in the world that hosts an intact community of large mammals. These animals roam over vast swaths of land, some migrating thousands of miles across multiple countries following seasonal rainfall. As human encroachment around the park becomes more intense, these species are forced to alter their behaviours in order to survive. Increasing agriculture, poaching, and climate abnormalities contribute to changes in animal behaviours and population dynamics, but these changes have occurred at spatial and temporal scales which are difficult to monitor using traditional research methods. There is a great urgency to understand how these animal communities function as human pressures grow, both in order to understand the dynamics of these last pristine ecosystems, and to formulate effective management plans to conserve and protect the integrity of this unique biodiversity hotspot.

Last year we took our annual data science survey to the next level by turning over the results to YOU through an open-ended Kernel competition. We were overwhelmed by the response and quality of kernels submitted. Not only are Kagglers amazing data scientists, but they're incredible storytellers as well! Mhamed Jabri was one of those skillful enough to take our data and shape it into something meaningful-- not just for Kaggle, but for the data science community at large. We hope you enjoy getting to know him as much as we did.