KalihoseMigisha/undeai-compute-vanguard

Multilingual ML infrastructure and Keras 3/JAX compute abstraction for the African Data Gap # UndeAI: Compute Vanguard 🚀 **Live Platform:** UndeAI.com ### Mission: Bridging the "Data Gap" Currently, only 2% of global training data represents Africa. **UndeAI** is a multilingual platform (EN/FR/PT) built to empower African ML talents by providing specialized infrastructure and curated African datasets. ### Technical Implementation This repository demonstrates the core architecture of the **Unde In-Platform Compute Hub** as seen on undeai.com: * **Backend:** Leverages **Keras 3** with the **JAX** backend to ensure high-performance XLA compilation. This architecture is designed to scale across Google TPU v4/v5 nodes. * **Frontend:** A React-based session management gateway (`frontend/ComputePage.jsx`) that bridges user authentication to high-performance compute environments. * **Architecture:** Optimized for the unique challenges of low-resource linguistic models and distributed training. ### TPU Grant Objectives With the TPU credits, we will: 1. **Scale Infrastructure:** Move our "Unde Compute Hub" from standard instances to TPU-accelerated nodes to support 100+ concurrent developers in East Africa. 2. **Regional Fine-Tuning:** Execute large-scale training on curated datasets from Tanzania and the broader continent. 3. **XLA Optimization:** Use JAX’s auto-differentiation to optimize weight updates for linguistic features unique to Swahili, Wolof, and other regional languages. --- *Built with ❤️ from rural parts of Tanzania, East Africa, for the future of African AI.*