Building Trustworthy AI with Agents
Key Takeaways:- Learn the principles of responsible machine learning and AI.
- Learn how to create a machine learning agent in Python.
- Learn a framework for managing multiple agents.
Description
The future is agentic! Join us for an exciting code-along session where we dive into the world of personalized AI agents! In this session, you'll learn how to build and evaluate AI agents ensuring they perform tasks reliably.
In this code-along, Shingai Manjengwa, the Head of AI Education at Theoriq (ChainML Labs), will discuss the principles of responsible AI and demonstrate how they may be implemented in a world with multiple collaborating agents. Shingai will guide you through the process of developing two distinct AI agents, each offering unique perspectives on the same task and you will learn how to create an evaluator to determine which agent gives the best output based on user criteria.
Presenter Bio
Shingai Manjengwa is the Head of AI Education and Solutions Engineering at Theoriq AI, an AI agent base layer focused on modularity and community-driven governance. She onboards partners to deploy advanced AI agents using smart contracts. Previously, she directed Technical Education at the Vector Institute, promoting AI adoption and innovation. Shingai founded Fireside Analytics Inc., offering AI literacy and data science education, with her online courses engaging over 500,000 learners. She authored “The Computer and the Cancelled Music Lessons,” a children's book on data science, and is a recognized leader in AI, receiving numerous accolades. Connect with her on LinkedIn and Twitter/X at @Tjido.