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.

Computers have become amazingly precise at translating spoken words to text messages and scouring huge troves of information for answers to complex questions. At least, that is, so long as you speak English or another of the world's dominant languages. But try talking to your phone in Yoruba, Igbo or any number of widely spoken African languages and you'll find glitches that can hinder access to information, trade, personal communications, customer service and other benefits of the global tech economy. "We are getting to the point where if a machine doesn't understand your language it will be like it never existed," said Vukosi Marivate, chief of data science at the University of Pretoria in South Africa, in a call to action before a December virtual gathering of the world's artificial intelligence researchers. American tech giants don't have a great track record of making their language technology work well outside the wealthiest markets, a problem that's also made it harder for them to detect dangerous misinformation on their platforms.