AI models
ALVINN
Training compute
1.1×10¹⁰ FLOP
Parameters
36.6K
Published
Dec 1, 1989
ALVINN is an AI model developed by Carnegie Mellon University (CMU) (United States), first published in December 1989. It works in the driving domain, on tasks such as self-driving car.
Training it took an estimated 1.1×10¹⁰ FLOP of compute (estimation method: operation counting). The model has 36,627 parameters. It was trained on roughly 55.2K datapoints.
The reference paper has 2,329 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Carnegie Mellon University (CMU)
- Country of organization
- United States
- Domain
- Driving
- Task
- Self-driving car
- Training compute
- 1.1×10¹⁰ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 36,627
- Dataset size
- 55.2K
- Citations
- 2,329
- Epoch confidence
- Confident
More from Carnegie Mellon University (CMU)
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