Learn how feedback loops and dynamic models enable AI systems to continuously learn, adapt, and improve through real-time experimentation.
| City | Time |
|---|---|
| San Francisco (UTC−7) | 7:00 AM |
| New York (UTC−4) | 10:00 AM |
| London (UTC+1) | 3:00 PM |
| Johannesburg / Cape Town (UTC+2) | 4:00 PM |
| Singapore (UTC+8) | 10:00 PM |
In this session, our Head of Product, Eric unpacks how feedback loops drive continuous learning in AI systems. We’ll explore how dynamic models evolve through feedback, adapting to new data, user interactions, and real-world changes.
Using the ecosystem.Ai Prediction Platform, Eric will walk through several algorithms used to support Dynamic Experimentation, showing how they learn, refine, and improve outcomes over time.
