AI Glossary
Distributed Computing
A computing approach that uses multiple computers working together to complete tasks.
Distributed Computing
Overview
Some computing problems are too large for a single machine to handle efficiently.
Training AI models.
Processing massive datasets.
Serving millions of users.
Running global applications.
These tasks often require multiple computers working together.
This approach is known as distributed computing.
Distributed computing divides work across multiple systems rather than relying on a single computer.
A helpful way to think about distributed computing is a team project.
Instead of one person completing every task, work is shared among many individuals who contribute simultaneously.
Similarly, distributed computing allows multiple machines to share processing responsibilities.
Modern AI systems depend heavily on distributed computing because many workloads require significant computing power and storage capacity.
As models continue to grow in size and complexity, distributed computing remains a foundational part of AI infrastructure.
Why It Matters
Distributed computing enables organizations to process larger workloads more efficiently.
Real-World Example
A large language model may be trained using thousands of computers working together across multiple data centers.