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AMEFORGE

Independent AI Research Studio

Website · GitHub · Google Play


About

Ameforge is an independent AI research studio. We design novel architectures, publish peer-reviewed research, and deploy production-ready models with software that brings these innovations directly to users.

Our work spans deep learning architecture research, natural language processing, time-series forecasting, and mobile software development.


Research

EARCP — Ensemble Adaptive Recurrent Cascade Predictor

Published on arXiv · Validated on Kaggle Hull Tactical Market Prediction (Rank 708 / 18,000+ teams · Top 24%)

A multi-expert ensemble architecture combining CNN, BiLSTM, and Transformer components for adaptive time-series prediction. Applicable to financial forecasting, sensor data, computer vision, and autonomous systems.

pip install earcp

📄 arXiv Paper · 🏆 Kaggle Leaderboard


SparseMind — Sparse Neural Architecture Research

Experimental research into high-sparsity neural architectures achieving 87.5% weight sparsity while maintaining competitive perplexity scores. Designed for efficient inference on resource-constrained environments.


NexusBPE — Custom Tokenizer Pipeline

A custom Byte-Pair Encoding tokenizer trained on a curated multilingual corpus (code, natural language, technical documents). Designed to complement Ameforge's internal language model research.


MemoryBank (LPOLMemory) — Continual Learning Research

Research into long-term memory mechanisms for neural networks, addressing catastrophic forgetting in continual learning scenarios.


Models

All published models are available under the CKL (Custom Knowledge License). Commercial licensing available — contact contact@ameforge.tech.

Model Task Status
gc_editor1 Text Generation Active
gc_editor Text Generation Active
gearcut_tok Tokenizer Active

Contact

📧 contact@ameforge.tech
🌐 ameforge.tech


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