How To Break the Enabling Barrier of Artificial Intelligence
Breaking the enabling barrier of artificial intelligence applications in real challenges is key to realizing social impacts and economic growth in marginalized communities.
In Sub-Saharan Africa, International donor agencies are the key players in building technology through R&D in partnership with local universities.
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Already programs that create home-grown and skilled artificial intelligence through the development of talent, however more work and effort are required.
I recently was on a mission to Djibouti a dry country and managed to put researchers from various disciplinary with the hope that it would increase interdisciplinary collaboration.
During the training, attention was given to aligning with innovation for ethical and relevant A.I. research in the local- context. In order to advance the applied artificial intelligence in agriculture and the environment and the contribution to the country and region
The team of researchers from departments of maths, statistics, computer science, hydrobiology, and chemistry came together, with a primary agenda discussion that focused on the;
Agriculture produces supply, demand, and market, Climate challenge impacts and implications
How to tackle challenges in climate
Understanding Image-based plant phenotyping tasks and techniques
The approach and critical aspects of Image-based plant phenotyping
Data strategy and designing well-structured data collection for specific tasks
Understanding models via data visualization and implication
The discussions and the technical engagements show a way to solve environmental problems with social impact.
Though, more work would also include the mobilization of a network of African companies, universities, research centers, and private and public institutions to collaborate on advancing the applied artificial intelligence agenda.
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