Teacher-Student Neural Networks: Knowledge Distillation in Modern AI

Author(s): Shahriar Hossain

Originally published on Towards AI.

In the ever-evolving landscape of artificial intelligence, as models burgeon in complexity and size, the challenge arises: How do we deploy these colossal models on hardware with limited resources? Enter the realm of Knowledge Distillation — a technique that promises to revolutionize AI deployments, especially in resource-constrained environments.

Source: Image by the author (created using Canva)

At its core, knowledge distillation is about transferring knowledge from a large, complex model (often called the teacher) to a smaller, simpler model (the student). Instead of merely training the student model directly on the raw data, it’s trained using the outputs of the teacher model…. Read the full blog for free on Medium.

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Published via Towards AI