AI models
Credibilty Network
Training compute
5.4×10⁶ FLOP
Parameters
324
Published
Jul 1, 1999
Credibilty Network is an AI model developed by University College London (UCL) and University of Toronto (United Kingdom and Canada), first published in July 1999. It works in the vision domain, on tasks such as character recognition (ocr) and image classification.
Training it took an estimated 5.4×10⁶ FLOP of compute (estimation method: operation counting). The model has 324 parameters. It was trained on roughly 2.8K datapoints.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- University College London (UCL), University of Toronto
- Country of organization
- United Kingdom, Canada
- Domain
- Vision
- Task
- Character recognition (OCR), Image classification
- Training compute
- 5.4×10⁶ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 324
- Dataset size
- 2.8K
- Model accessibility
- Unreleased
- Open weights
- No
- 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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