AI models
Distributed representation NN
Training compute
3.9×10⁸ FLOP
Parameters
432
Published
Aug 15, 1986
Distributed representation NN is an AI model developed by Carnegie Mellon University (CMU) (United States), first published in August 1986. It works in the other domain, on tasks such as representation learning. It counts among the frontier models: the systems trained with the most compute of their moment.
Training it took an estimated 3.9×10⁸ FLOP of compute (estimation method: operation counting). The model has 432 parameters. It was trained on roughly 100 datapoints.
Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Carnegie Mellon University (CMU)
- Country of organization
- United States
- Domain
- Other
- Task
- Representation learning
- Training compute
- 3.9×10⁸ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 432
- Dataset size
- 100
- Epoch confidence
- Confident
More from Carnegie Mellon University (CMU)
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