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Model release pace

Monthly counts by original publication date. Completed months compare with their previous month; the current month compares equal completed days. A zero denominator has no percentage growth. This is not an exhaustive model census.

Model release pace

Model release pace2024-10-01: 11.00; 2024-11-01: 8.00; 2024-12-01: 13.00; 2025-01-01: 10.00; 2025-02-01: 4.00; 2025-03-01: 10.00; 2025-04-01: 6.00; 2025-05-01: 7.00; 2025-06-01: 4.00; 2025-07-01: 10.00; 2025-08-01: 11.00; 2025-09-01: 8.00; 2025-10-01: 6.00; 2025-11-01: 19.00; 2025-12-01: 12.00; 2026-01-01: 1.00; 2026-02-01: 9.00; 2026-03-01: 9.00; 2026-04-01: 17.00; 2026-05-01: 6.00; 2026-06-01: 9.00; 2026-07-01: 7.00; 2026-08-01: 8.00; 2026-09-01: 12.0009.5192024-10-01: 11.00 2024-11-01: 8.00 2024-12-01: 13.00 2025-01-01: 10.00 2025-02-01: 4.00 2025-03-01: 10.00 2025-04-01: 6.00 2025-05-01: 7.00 2025-06-01: 4.00 2025-07-01: 10.00 2025-08-01: 11.00 2025-09-01: 8.00 2025-10-01: 6.00 2025-11-01: 19.00 2025-12-01: 12.00 2026-01-01: 1.00 2026-02-01: 9.00 2026-03-01: 9.00 2026-04-01: 17.00 2026-05-01: 6.00 2026-06-01: 9.00 2026-07-01: 7.00 2026-08-01: 8.00 2026-09-01: 12.00 10/0109/01 UTC

Monthly release growth

Monthly release growth2024-10-01: -15.38%; 2024-11-01: -27.27%; 2024-12-01: 62.50%; 2025-01-01: -23.08%; 2025-02-01: -60.00%; 2025-03-01: 150.00%; 2025-04-01: -40.00%; 2025-05-01: 16.67%; 2025-06-01: -42.86%; 2025-07-01: 150.00%; 2025-08-01: 10.00%; 2025-09-01: -27.27%; 2025-10-01: -25.00%; 2025-11-01: 216.67%; 2025-12-01: -36.84%; 2026-01-01: -91.67%; 2026-02-01: 800.00%; 2026-03-01: 0.00%; 2026-04-01: 88.89%; 2026-05-01: -64.71%; 2026-06-01: 50.00%; 2026-07-01: -22.22%; 2026-08-01: 14.29%; 2026-09-01: 71.43%-91.7354.28002024-10-01: -15.38 %2024-11-01: -27.27 %2024-12-01: 62.50 %2025-01-01: -23.08 %2025-02-01: -60.00 %2025-03-01: 150.00 %2025-04-01: -40.00 %2025-05-01: 16.67 %2025-06-01: -42.86 %2025-07-01: 150.00 %2025-08-01: 10.00 %2025-09-01: -27.27 %2025-10-01: -25.00 %2025-11-01: 216.67 %2025-12-01: -36.84 %2026-01-01: -91.67 %2026-02-01: 800.00 %2026-03-01: 0.00 %2026-04-01: 88.89 %2026-05-01: -64.71 %2026-06-01: 50.00 %2026-07-01: -22.22 %2026-08-01: 14.29 %2026-09-01: 71.43 %10/0109/01 UTC

Total 1,072 · Page 39/43 · Observed 9/27/2026, 3:30:50 AM

NameGroupReported valueDateNotesSource
Two Stage Feature Extraction (MNIST)New York University (NYU)—2009-09-01UnreleasedSource ↗
MatrixFac for RecommendersYahoo Research,AT&T—2009-08-07—Source ↗
Pragmatic Theory solution (Netflix 2009)Pragmatic Theory Inc.—2009-08-01—Source ↗
BigChaos OptiBlendAT&T—2009-08-01—Source ↗
BellKor 2009AT&T—2009-08-01—Source ↗
BellKor 2008AT&T—2009-08-01—Source ↗
GPU DBNsStanford University—2009-06-15—Source ↗
RBM Image ClassifierUniversity of Toronto—2009-04-08—Source ↗
BP-DBNUniversity of Toronto—2009-01-01UnreleasedSource ↗
GNNUniversity of Siena—2008-12-09Open weights (unrestricted)Source ↗
HLBLUniversity of Toronto—2008-12-08—Source ↗
BigChaos 2008AT&T—2008-11-25—Source ↗
Sparse digit recognition SVMUniversity of Lubeck—2008-11-19—Source ↗
Denoising AutoencodersUniversity of Montreal / Université de Montréal—2008-07-05—Source ↗
Deep Multitask NLP NetworkNEC Laboratories—2008-07-05—Source ↗
BLSTM for handwriting (2)University of Bern,IDSIA,Technical University of Munich—2007-12-03—Source ↗
Enhanced Neighborhood-Based FilteringAT&T—2007-10-28—Source ↗
BLSTM for handwriting (1)University of Bern,IDSIA,Technical University of Munich—2007-09-23—Source ↗
SB-LMGoogle—2007-06-22—Source ↗
KN-LMGoogle—2007-06-22—Source ↗
λ-WASPUT Austin—2007-06-01—Source ↗
Greedy layer-wise DNN trainingUniversity of Montreal / Université de Montréal—2006-12-04—Source ↗
Local Binary Patterns for facial recognitionUniversity of Oulu,IEEE—2006-12-01—Source ↗
Dimensionality ReductionUniversity of Toronto—2006-07-18—Source ↗
Deep Belief NetsUniversity of Toronto,National University of Singapore—2006-07-18—Source ↗

Data: Epoch AI · CC BY · View source · Automatically synced; not an exhaustive global sample