What is Lifelong Learning?
Artificial intelligence's ability to continuously learn with new data without losing old information.
Overview
Lifelong learning is an approach that enables an artificial intelligence model to leave a static training process and acquire new knowledge throughout its life. While traditional models are often limited to the knowledge of the moment they are trained, these systems adapt to a changing world over time. The model uses special techniques to avoid forgetting old skills when learning something new.
How it works
Special layers are added to the model's architecture, where new information can be built on top of old information. Additionally, a 'memory' mechanism is used to recall important parts of old data. Thus, artificial intelligence does not have to delete the basic information it has learned in the past when learning a new subject.
Where it is used
It is used in personal assistants, constantly updated news analysis systems and robotic applications.
Commonly confused with
It is almost the same as continuous learning, but lifelong learning refers to a more long-term and comprehensive development process.
Frequently asked questions
Why doesn't every AI do this?
Because models tend to forget old data while learning new data, this is called 'catastrophic forgetting' and is difficult to solve.
Related terms
Related tools
This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →