AI teacher/student metaphor
Created: December 22, 2022 / Updated: December 22, 2022 / Status: in progress / 2 min read (~246 words)
How can we use the teacher/student metaphor in AI?
The teacher/student metaphor can be used in AI to refer to the relationship between a model that is being trained (the student) and the data it is being trained on (the teacher). In this context, the teacher provides the student with examples and the student attempts to learn from these examples by adjusting its internal parameters to better fit the data.
One way this metaphor is often used is in the context of supervised learning, where the teacher provides the student with labeled examples and the student learns to make predictions based on these examples. For example, a teacher could provide a student with a dataset of images of cats and dogs, along with labels indicating which images are of cats and which are of dogs. The student would then learn to classify new images as either cats or dogs based on the patterns it observed in the training data.
Another way the teacher/student metaphor can be used is in the context of reinforcement learning, where the teacher provides the student with a reward signal indicating whether its actions are good or bad. The student then learns to take actions that maximize the reward.
Overall, the teacher/student metaphor can be a useful way to understand the relationship between a model and the data it is trained on, and can help to clarify the role that each plays in the learning process.