Models from United States of America in 2014
13
Models
7 organisations
—
Open weights
0 open, 0 closed
3
Frontier
By Epoch's flag
2B
Largest traceable
Seq2Seq LSTM
2014
Span
3 with a traceable size
Releases
by monthOrganisation
Records
13| Model | Organisation | Released | Parameters | Weights |
|---|---|---|---|---|
| SNM-skip | 2014-12 | 62B * | Not recorded | |
| Fully Convolutional Networks | University of California (UC) Berkeley | 2014-11 | — | Not recorded |
| LRCN | UT Austin | 2014-11 | 143M * | Not recorded |
| Deeply-supervised nets | Microsoft Research | 2014-09 | — | Not recorded |
| GoogLeNet / InceptionV1 | 2014-09 | 7M | Not recorded | |
| Seq2Seq LSTM | 2014-09 | 2B | Not recorded | |
| Fragment embedding | Stanford University | 2014-06 | 144M * | Not recorded |
| Multiresolution CNN | 2014-06 | 126M * | Not recorded | |
| SPPNet | Microsoft | 2014-06 | — | Not recorded |
| Paragraph Vector | 2014-05 | 32M | Not recorded | |
| HyperNEAT | University of Texas at Austin | 2014-03 | 239,712 * | Not recorded |
| GloVe (32B) | Stanford University | 2014-01 | 120M * | Not recorded |
| GloVe (6B) | Stanford University | 2014-01 | 120M * | Not recorded |
An asterisk marks a parameter figure the source does not consider traceable to the people who built the model. That judgement is the source’s and it has false negatives: Kimi K3 is marked speculative at 2.8T while Moonshot’s own model card states the figure. Why that distinction carries the whole exhibit.
Counts are of models Epoch AI records as notable, not of every model released. The most recent month is always incomplete, because a model enters the dataset when it is reviewed rather than when it ships.
Epoch AI, 'Data on AI Models'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/data/ai-models-documentation' Used under CC BY 4.0.