Scholars build AI models for climate change

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Zindi Chief Executive Officer and Co-Founder, Celina Lee

by SAVIOUS KWINIKA
JOHANNESBURG, (CAJ News) – STUDENTS from around the continent have teamed up to build artificial intelligence (AI) models to tackle climate change.

They participated at the just-ended single largest pan-African machine learning hackathon, which attracted 1 000 students.

At the UmojaHack Africa 2023, Zindi attracted the students from 345 universities in 36 countries to build machine learning models for climate change.

For the Rubik’s Cube Reinforcement Learning Challenge, the winners were Akram Badreddine Laissaoui and Nazim Bendib from École Nationale Supérieure d’Informatique (ENSI), Algeria.

For the Cryptojacking Detection Challenge, the winners were Wiem Khlifi, Malek Sahlia, and Firas Jaadari from École Nationale des Sciences de l’Informatique (ENSI), Tunisia.

For the Carbon Dioxide Prediction Challenge, the winner was Stephen Kolesh, from Multimedia University (MMU), Kenya.

Students won prizes of cash and online learning licenses amounting to more than US$10 000.

“With the world facing a dramatic shortage of data talent in the next 5-10 years, UmojaHack Africa serves a critical global need in unearthing and upskilling emerging data talent from new markets,” said Celina Lee, Chief Executive Officer and co-founder of Zindi.

“We are thrilled with the turnout and enthusiasm of the students who participated in UmojaHack Africa 2023 this year, and look forward to seeing these rising stars develop into successful professionals on the Zindi platform,” Lee said.

Avishkar Boopchand, Senior Research Engineer at DeepMind, addressed participants on the day.

“We need Africans to build African solutions to African problems. I’m really excited by the young, talented, and enthusiastic population on the continent,” Boopchand said.

It was one of sponsors, alongside Ar, African Energy Chamber, InstaDeep, Kaggle, MPOWER Financing, and Mara.

UmojaHack Africa 2023 was hailed as a powerful demonstration of the potential of machine learning to drive positive change in the continent.

Africa is worst impacted by climate change.

– CAJ News

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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