AI models
System 11
Training compute
2.6×10¹⁰ FLOP
Parameters
6.5K
Published
Jun 18, 1996
System 11 is an AI model developed by Carnegie Mellon University (CMU) (United States), first published in June 1996. It works in the vision domain, on tasks such as face detection.
Training it took an estimated 2.6×10¹⁰ FLOP of compute (estimation method: operation counting). The model has 6,452 parameters. It was trained on roughly 23.8K datapoints.
The reference paper has 6,011 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Carnegie Mellon University (CMU)
- Country of organization
- United States
- Domain
- Vision
- Task
- Face detection
- Training compute
- 2.6×10¹⁰ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 6,452
- Dataset size
- 23.8K
- Citations
- 6,011
- Epoch confidence
- Confident
More from Carnegie Mellon University (CMU)
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