Skip to content

AI Foundations

Exploding gradient

An AI training problem where learning adjustments become too large and make learning unstable.

Example

Training becomes unstable after unusually large learning changes.

Why people use it

It names a training failure where changes become too large to stay stable.

What you'll hear

“The learning updates suddenly became enormous.”

What this means for you

Ask the people running training to investigate the unstable calculations before continuing.

Can you control it?

No

No direct control. This describes a wider issue, concept or result rather than something you can simply switch on or off in a tool.

Common questions

Does this mean the computer is physically overheating?
No. It describes unstable learning calculations, not the machine's temperature.
Can it make training stop completely?
Yes. Very large calculations can produce unusable numbers or prevent the process from continuing.
Does it show that the teaching examples are wrong?
Not necessarily. The learning setup can be unstable even when the examples are appropriate.

Related terms

Still have questions?

Up to 500 characters.

Ask LATHIC about AI. Relevant glossary entries may be included.

Your question, the glossary entries it matches, and a rotating pseudonymous identifier go to Microsoft Azure’s OpenAI service through Vercel AI Gateway to generate an answer. Zero retention and no training are required of the provider, and LATHIC does not save your question or answer. Privacy Notice