What is few-shot learning in robotics?

What is few-shot learning in robotics?

Few-shot learning in robotics refers to the ability of a robot to learn new tasks with very few examples, mimicking human learning.

How does it differ from traditional machine learning?

Traditional machine learning often requires large datasets to train models, while few-shot learning can generalize from just a few examples.

Can you give an example of few-shot learning in action?

Sure! For instance, a robot might learn to pick up different objects by seeing just a couple of examples of each object type.

What are the challenges in implementing few-shot learning in robotics?

Challenges include ensuring the robot can generalize well, dealing with variations in object appearance, and optimizing learning algorithms.