October 28–31, 2019
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From dance to diagnosis: How Tensorflow.js is shaping AI in Africa

Babusi Nyoni (Triple Black)
1:40pm2:20pm Thursday, October 31, 2019
Location: Grand Ballroom E

Who is this presentation for?

  • Developers, policy makers, and creators


New to TensorFlow


As the western world continues to explore advancements in artificial intelligence, sub-Saharan Africa lags behind. This is in part due to low internet connectivity, lack of proper information and communications technology (ICT) policy implementation, and a stunted region-wide open data economy. These factors combined greatly limit the application of common macro-AI instances that rely on big data for success.

In the face of these challenges, there presents the opportunity to harness unconventional proxies for datasets that could be used in lieu of a preferred value set. An example of this is how a United Nations agency Babusi Nyoni consults for, used the price of a goat in Somalia through collaboration with displaced populations as a proxy for displacement signals. This was after it was discovered that the market price of a goat could decrease relative to the number of people whose departure from an area was imminent.

Babusi dives into opportunities presented by small data in the development of AI-enabled solutions for the African continent. He explains how mobile-first internet connectivity trends in the sub-Saharan region have readied a generation for more personal relationships with technology and how Triple Black’s dance app experiment showed that there’s a genuine willingness on the continent to interact with new technology as long as it’s relevant. He also unpacks the approach used to apply the dance app algorithm to build a prototype for the early diagnosis of Parkinson’s disease and how, in underdeveloped communities, client-side AI such as TensorFlow.js is the future.

Prerequisite knowledge

  • A basic understanding of machine learning

What you'll learn

  • Learn that Africa needs unconventional approaches to AI, how mobile is the device of choice for connecting to the internet in Africa, and how browser-side AI libraries such as TensorFlow.js will drive AI innovation on the continent
Photo of Babusi Nyoni

Babusi Nyoni

Triple Black

Babusi Nyoni is a Zimbabwean innovator focused on the uses of artificial intelligence on the African continent. In 2016, he created what Forbes magazine described as, “the world’s first AI football commentator” for the UEFA Champions League final. In the same year, he created a prototype for the prediction of human displacement in Africa using AI, and thereafter worked with UNHCR Innovation to actualize a pilot project in the same field. He founded the Ulwazi Accelerator in 2018 to equip young Zimbabweans with the skills needed to contribute to the global digital economy. In 2019, he created an app for the early diagnosis of Parkinson’s disease and presented his findings at Oxford University on the Skoll World Forum stage. Babusi has a strong passion for fresh new ideas that will change the lives of those around him and is a firm believer that AI is shaping the technological zeitgeist worldwide.

  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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