self-supervised-learning

Vocabulary Word

Definition
'Self-supervised learning' in artificial intelligence involves computers learning on their own by using a part of input data as the answer. It's just like solving a fill-in-the-blanks from a textbook.
Examples in Different Contexts
Machine learning experts use self-supervised learning to train models on large datasets without needing annotated examples. A machine learning engineer might explain, 'We leverage self-supervised learning to preprocess data, enhancing model performance with minimal human intervention.'
Practice Scenarios
Robotics

Scenario:

Our robot has to navigate through dynamic environments and understand objects it has not seen before. Is there a way to make it more adaptable?

Response:

Self-supervised learning could help our robot learn from the environment and adapt to unseen objects and scenarios.

AI

Scenario:

Our language understanding model needs to grasp more subtle nuances of human conversation. Can we make it learn more autonomously?

Response:

Self-supervised learning can enhance our model's ability to understand human conversation by learning from the conversational data itself.

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