The presentation showcases Kenya’s leadership in AI adoption, the power of building and deploying AI locally (especially with tools like Foundry Local), the importance of responsible and observable AI, and real-world use cases that are already making an impact across industries. It provides practical steps and resources for getting started with AI at scale, tailored for the Kenyan and African context.
The concept of AI and AI Adoption in Kenya
Kenya has been ranked as the top country using ChatGPT, and in March launched the Kenya Artificial Intelligence Strategy. This keynote will base on one of the key pillars of the strategy, which is Kenya’s ambition to be both a user and exporter of AI.
The concept of LLMs and Foundry Local
In this section we explore the building blocks of Large Language Models (LLMs) and the Foundry Local, which enables the deployment of AI solutions in local environments. With Foundry Local, you can run AI on edge, ensuring data privacy and compliance with local regulations. Find the demo here
Giving your LLMs superpowers, sort of.
In this part we discuss RAG, AI Agents, and MCP. We will explore how these technologies can enhance the capabilities of LLMs, making them more powerful and versatile for various applications. For the RAG demo, we will ground our LLMs in the Kenyan Constitution and the AI Strategy, showcasing how to use local data to improve AI responses. For the AI Agents and MCP demo, we will go through leveraging Microsoft Docs MCP server and a demo for a Spotify MCP Agent.
Going global
We will cover the concept of GenAIOps and how you can evaluate your AI solutions using the AI Foundry evaluators and Foundry Observability dashboard. This will help you ensure that your AI applications are secure, grounded, performing optimally and meeting global standards.
Use cases
We will conclude with a discussion on various use cass of AI in Kenya: - co-op translator - ulizaLlama - Faststagger
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