In today’s episode, we’re diving into the fascinating world of model merging—a technique that allows multiple AI models to be combined, often enhancing their capabilities without the need for costly retraining. Our focus? A groundbreaking paper titled "Do Merged Models Copy or Compose? Evaluating the Transfer of Capabilities in Model Merging" by researchers exploring the inner workings of this emerging technique.

We'll be discussing:

🔹 What is model merging? Why it's gaining traction in AI research.

🔹 Do merged models simply copy knowledge, or can they create something new?

🔹 How does merging affect generalization, robustness, and performance?

🔹 Real-world implications—from adapting models across different domains to fine-tuning AI with fewer resources.