AI models
Perceptron (1960)
Training compute
7.2×10⁸ FLOP
Parameters
1K
Published
Mar 30, 1960
Perceptron (1960) is an AI model developed by Cornell Aeronautical Laboratory (United States), first published in March 1960. It works in the vision domain, on tasks such as image classification. It counts among the frontier models: the systems trained with the most compute of their moment.
Training it took an estimated 7.2×10⁸ FLOP of compute (estimation method: hardware). The model has 1,000 parameters. It was trained on roughly 100 datapoints.
The reference paper has 394 citations. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- Cornell Aeronautical Laboratory
- Country of organization
- United States
- Domain
- Vision
- Task
- Image classification
- Training compute
- 7.2×10⁸ FLOP
- Compute estimation method
- Hardware
- Parameters
- 1,000
- Dataset size
- 100
- Citations
- 394
- Epoch confidence
- Speculative
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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