AI Quality Education

Welcome!

This AI Quality Education section will teach you core concepts and skills that you need to monitor, debug, and test AI models. Quickly create and maintain higher quality, trustworthy models. when you learn about key components of AI Quality. This section covers:

• Performance, explainability, data quality, stability, fairness and conceptual soundness
• Fundamentals of ML operations
• Advanced techniques to manage AI quality across machine learning lifecycle
• Pioneering research on the evaluation of generative AI models, including large language models. 

What To Expect ?

• Explore key topics. This section is structured around key topics. Under each topic, you will find several articles that 1) define a component of AI quality and 2) present associated challenges and 3) practical solutions to address them. 
• Follow your curiosity. Each entry can be taken in parts and there is no predetermined order.  You should pick a topic based on your background and interest. 
• Participate in the community. If you have additional questions about a specific article, feel free to share it with us in our AI Quality Forum community.

ML Monitoring

Model Testing

Generative AI

Fairness & AI Bias

Performance

AI Quality

Who Are We?

TruEra offers solutions to monitor, debug, and test machine learning models, leading to higher quality and trustworthiness, as well as faster deployment. Backed by years of pioneering research, TruEra works across the model lifecycle, is independent of model development platforms, and embeds easily into your existing AI stack. TruEra is used by major companies around the globe, from tech startups to major banks. TruEra is a multiple time Fast Company award winner.