AI models
Innervator
Training compute
1.2×10⁸ FLOP
Parameters
10
Published
Dec 1, 1989
Innervator is an AI model developed by Stanford University and California Institute of Technology (United States), first published in December 1989. It works in the mathematics domain, on tasks such as pattern classification.
Training it took an estimated 1.2×10⁸ FLOP of compute (estimation method: operation counting). The model has 10 parameters. It was trained on roughly 10.2K datapoints.
The reference paper has 1,132 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Stanford University, California Institute of Technology
- Country of organization
- United States
- Domain
- Mathematics
- Task
- Pattern classification
- Training compute
- 1.2×10⁸ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 10
- Dataset size
- 10.2K
- Citations
- 1,132
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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