AI models
Perceptron Mark I
Training compute
6.9×10⁵ FLOP
Parameters
1K
Published
Jan 1, 1957
Perceptron Mark I is an AI model developed by Cornell Aeronautical Laboratory and Cornell University (United States), first published in January 1957. It works in the other domain, on tasks such as binary classification. It counts among the frontier models: the systems trained with the most compute of their moment.
Training it took an estimated 6.9×10⁵ FLOP of compute (estimation method: third-party estimation). The model has 1,000 parameters. It was trained on roughly 100 datapoints.
The reference paper has 1,610 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Cornell Aeronautical Laboratory, Cornell University
- Country of organization
- United States
- Domain
- Other
- Task
- Binary classification
- Training compute
- 6.9×10⁵ FLOP
- Compute estimation method
- Third-party estimation
- Parameters
- 1,000
- Dataset size
- 100
- Citations
- 1,610
- Epoch confidence
- Likely
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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