Automated Testing of AI-ML Models | Toni Ramchandani

About the talk

In this session, 𝐓𝐨𝐧𝐢 𝐑𝐚𝐦𝐜𝐡𝐚𝐧𝐝𝐚𝐧𝐢, VP at MSCI Inc., talks about the crucial role of testing in AI/ML model development. The session covers various testing techniques needed to validate AI/ML models, starting with an overview of automated testing and its importance. You can learn about tools like DeepXplore and SHAP, which help identify neural network inconsistencies and improve model transparency.

Key Highlights

35+ Sessions

60+ Speakers

20,000+ Attendees

2000+ Minutes

Live Q&As

Key Topics Covered

Gain a clear understanding of what AI hallucinations are, why they occur, and their potential impact on real-world AI applications.

Learn about key tools such as DeepXplore and how they can be utilized to identify and mitigate AI hallucinations.

Understand the principles and techniques of adversarial testing and how it helps in uncovering vulnerabilities like hallucinations in AI models.

Recognize the importance of securing AI models against hallucinations and other errors and the ethical implications of deploying untested or vulnerable AI systems.