AI models
aLSTM(depth-2)+RecurrentPolicy (PTB)
Training compute
2.4×10¹⁶ FLOP
Parameters
24M
Published
May 22, 2018
aLSTM(depth-2)+RecurrentPolicy (PTB) is an AI model developed by University of Manchester (United Kingdom), first published in May 2018. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2.4×10¹⁶ FLOP of compute. The model has 24,000,000 parameters.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- University of Manchester
- Country of organization
- United Kingdom
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2.4×10¹⁶ FLOP
- Parameters
- 24,000,000
- Model accessibility
- Unreleased
- Open weights
- No
- Epoch confidence
- Likely
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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