AI models
bRSM + cache
Training compute
2.8×10¹⁴ FLOP
Parameters
2.5M
Published
Dec 2, 2019
bRSM + cache is an AI model developed by Numenta and Incubator 491 (United States and Australia), first published in December 2019. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2.8×10¹⁴ FLOP of compute (estimation method: operation counting). The model has 2,550,000 parameters. It was trained on roughly 912.3K datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 6 citations. Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- Numenta, Incubator 491
- Country of organization
- United States, Australia
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2.8×10¹⁴ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 2,550,000
- Dataset size
- 912.3K
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 6
- 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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