From 9772d3b8fc16ecc2aea2b33897ce901a1dddc379 Mon Sep 17 00:00:00 2001 From: Lawal Olanrewaju Israel <61704062+lawallanre00490038@users.noreply.github.com> Date: Sat, 27 Jan 2024 09:54:13 +0000 Subject: [PATCH] Update portfolio_gallery.html --- portfolio_gallery.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/portfolio_gallery.html b/portfolio_gallery.html index eeb267c..4ba5c04 100644 --- a/portfolio_gallery.html +++ b/portfolio_gallery.html @@ -128,7 +128,7 @@

Trafrika

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Large Language Models for locally nuanced, multimedia Science
Learning content development

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Large Language Models for locally nuanced,
multimedia Science
Learning content development

A proposed solution that uses advanced AI language models to create educational science content that is tailored to local contexts and includes multimedia elements. These models can analyze and understand complex scientific topics and then generate text, images, and possibly other media types that are specifically adapted to the cultural, linguistic, and educational needs of different local audiences. It also analyzes the learning trends and patterns of the learners and recommends content accordingly. This solution won The Bill and Melinda Gates Foundation Grant in Education in 2023.