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.

Greenhouse gas emissions are a key driver of climate change. We asked Erica about her work, and her experience at the AfriClimate AI workshop at the Deep Learning Indaba, where her research won an award. I am Erica Kimei, a PhD candidate at the Nelson Mandela African Institution of Science and Technology in Tanzania (NM-AIST), and an assistant lecturer at the National Institute of Transport. My research focuses on leveraging machine learning and remote sensing technology to monitor and forecast greenhouse gas emissions from ruminant livestock. This work aims to contribute to sustainable agricultural practices by enabling better management of emissions and addressing the climate impacts of livestock farming.

Andrews Ata Kangah is a team leader and researcher working on democratizing AI and AI solutions for environmental problems. We spoke to him about his research, attending the AfriClimate AI workshop at the Deep Learning Indaba, and what inspired him to work in AI and on climate-related projects. My name is Andrews Ata Kangah. I also double as a researcher at Armtos, which is a non-profit. At Armtos, our current goal is to build a solution to solve the illegal mining problem that's going on in Ghana. The mining is destroying the lands that are within mining areas.

AfriClimate AI is a grassroots community focused on leveraging artificial intelligence to tackle climate challenges in Africa. We spoke to Amal Nammouchi, one of the co-founders of AfriClimate AI, about the inspiration behind the initiative, some of their activities and projects, and plans for the future. Everything started last year at the Deep Learning Indaba in Ghana. The Deep Learning Indaba is the largest African AI community gathering and it happens once a year. The spark for AfriClimate AI came from a workshop with the work of one of our co-founders Rendani Mbuvha.

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we learn about a framework to evaluate diversity in datasets, find out how banks may strategically mitigate their risk from fraud in real-time payment systems, and hear about the AfriClimate AI workshop at the Deep Learning Indaba. Don't Just Claim It, Jerone Andrews and colleagues propose using measurement theory from the social sciences as a framework to improve the collection and evaluation of diverse machine learning datasets. We spoke to Jerone about this work, which won a best paper award at ICML 2024. Real-time payments offer a fast processing time (of around 10 seconds), allowing for near-immediate receipt of funds.

The 40th International Conference on Machine Learning (ICML) took place Honolulu, Hawai'i from 23-29 July 2023. There were four invited talks as part of the programme, and in this post we summarise the presentation by Shakir Mohamed – "Machine learning with social purpose". In a talk of three interwoven parts, Shakir's aim was to encourage the amplification and acceleration of work on machine learning with social purpose. He is passionate about using machine learning to contribute to overcoming some of the global challenges that we face, and, as well as demonstrating some of his research in this space, he provided guidance on how researchers can widen their horizons and consider the social implications of their work. Modelling of weather and climate can have a big impact on society, with such models often providing the basis for decisions taken by policy makers.

During a trip home to Johannesburg, South Africa, while completing an engineering master's program in Japan, Pelonomi Moiloa attended the largest machine learning community gathering she'd ever seen in Africa, just a few miles from where she grew up. In all, 600 people from 22 nations attended 2017's Deep Learning Indaba, held at the University of Witwatersrand, discussing topics like health care and agriculture solutions custom-made to meet the needs of African people. That week-long gathering made Moiloa feel she could have an impact on the lives of Africans, and it helped convince her to move back to South Africa and look for a way to put her engineering skills to work on her home continent. "The conversations were around making a genuine impact and positive change in African lives on a mass scale, and that was something I really wanted to be a part of," she says. This month, Moiloa will join some organizers of Deep Learning Indaba to launch Lelapa, a commercial and industrial AI research company focused on serving the needs of the 1 billion people in Africa.

Young scientists want machine learning revolution in Africa Kudzai Mashininga 29 September 2022 Cameroon national Loic Elnathan Tiokou Fangang concluded his masters degree in mathematical sciences at the African Institute for Mathematical Sciences (AIMS) earlier in 2022 and, as he awaits an opportunity to pursue a PhD in machine learning, he believes the dream of the institute's founders – of producing the next Einstein – has already been accomplished. AIMS is a network of six centres of excellence, which are based in South Africa, Senegal, Ghana, Cameroon, Tanzania and Rwanda. Students who join the institute get to work on driving the continent's STEM (science, technology, engineering and mathematics) agenda. The founder of AIMS, South African physicist Neil Turok, in 2008 gave a speech in which he declared his wish that the next Einstein would be from Africa. In an interview with University World News, Fangang said that, each year, AIMS is producing African Einsteins as it invests in its students – and not just by equipping them with mathematical skills.

What do I mean by the Artificial Intelligence (AI) revolution? With all the AI hype, it is worth explaining it again from my point of view. Coined by Stanford University researcher John McCarthy, AI is the ability of a machine or a computer to think and learn – and therefore act in ways that are smart. The broad concept or idea here is to build machines capable of thinking, acting and learning like humans. In the past decade, AI has been cited as one of the transformative technologies that have made big strides in many industries including retail, healthcare, banking and finance, agriculture, manufacturing, travel and entertainment, education, public administration and many more.

Deep Learning Indaba is currently taking place in Tunis, Tunisia. Find out what the participants and organisers have been up to in this round-up of tweets from attendees. This has me really thinking about how humans do this so seamlessly and the effort required from a deep learning perspective. Gabriela Csurka is delivering a powerful keynote speech on "Visual Domain Adaptation in the Deep Learning Era" at the @DeepIndaba #DLIndaba2022. Follow us to get the most recent updates of the #DLIndaba2022.