Where did Google open its first Africa Artificial Intelligence lab?

Asked 29-Apr-2019
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In Ghana, Google opened its first African Artificial Intelligence Lab. The Internet tech giant put forward a mission to provide the required tools in order to solve the Africa’s problem in various fields like health and agriculture specially.

Where did Google open its first Africa Artificial Intelligence lab?

A huge number of Artificial Intelligence Experts and Hubs are present in Asia, Europe, and North America. Artificial Intelligence can be used in various sectors such as agriculture, health, and education. However, the research scientist of Moustapha Cisse are heading towards Google's Artificial Intelligence brave step in Africa, says his team's goal is to provide developers with the necessary research and facility needed to build the products that can solve the problems of Africa which it faces today.
Cisse even talked about the app used by the Tanzanian farmer, which was used to diagnose her cassava's disease as an example is a type of product about which his team is planning for research to get involved with relevant and good institutes belongs under various sectors. As well as a team of University of Pennsylvania the International Institute of Tropical Agriculture are using a device which is named as TensorFlow and is used to build the new Artificial Intelligence model which also support on mobile phones as well to diagnose the crop disease.

Cisse is an expert researcher from Senegal, says the center directly engages with researchers in African universities by providing grants to those interested in the various fields of AI and giving Ph.D. scholarships. He also mentioned that Google also promotes the graduate programs in Machine Intelligence at the African Institute for Mathematical Sciences Center in Rwanda. The center will also focus on enhancing Google Translate's ability to capture African languages more precisely, with Cisse saying a continent with more than 2000 dialects deserves to be better served. The best way to go about is to have diverse teams working on these algorithms and then we will get somewhere.