GLOSSARY > TRANSFER LEARNING

Transfer Learning

A research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.

Transfer Learning allows organizations to take a massive open-source model trained on the entire public internet and transfer that fundamental linguistic capability to highly specialized, proprietary enterprise data, saving millions of dollars in compute costs while achieving state-of-the-art accuracy.

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Related Terms

Large Language Model

A deep learning algorithm that can recognize, summarize, translate, predict, and generate human language.

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Fine-Tuning

The process of taking a pre-trained foundational AI model and training it further on a highly specific, proprietary dataset.

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Model Inference

The live phase where a trained AI model processes new, unseen data to make predictions or generate outputs.

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