AI Jargon Buster
AI news and the language around it, simplified.
What is Federated Learning?
Federated learning is a way to train artificial intelligence models across many different devices, such as smartphones or local office computers, without moving the data to a central server. Instead of gathering all the information in one place, the system sends the model to the data. Each device learns from its own local information and sends back only the updated mathematical patterns. The central system combines these patterns to improve the overall model. This process ensures that the raw data, which might contain sensitive or private details, never leaves the device where it was created.
Why this matters to you
It allows organizations to build powerful, accurate tools while respecting strict privacy regulations and protecting user data. By keeping information on local devices, companies reduce the risks associated with data breaches and satisfy the need for data security in industries like healthcare and finance.
How you might hear this
Our team is exploring federated learning to ensure we can improve our predictive analytics tools without compromising the confidentiality of our clients' internal records.
AI Jargon Buster
Search any AI term, explained in plain English.
Type a term below and search. You will be taken straight to the tool.
Related terms
See how your CV performs against the ATS algorithms that screen candidates before a human ever reads your application.
Try the CV Optimiser →How AI job displacement actually works, what it means for your career, and what to do about it. Written by someone who has been in recruitment for 25 years.
When the Ground Shifts →