From backend developer to AI researcher. Building analytical alternatives to backpropagation.

🧮 BackLoss — Single-formula weight computation without gradient calculation. 22x faster than backprop in classification, 99.77% on MNIST (world #7).

🔗 PropLoss — Multi-layer gradient-free learning system. Outperforms backprop by 50.9 percentage points at 6 layers. pip install proploss

⚡ LazySmart Optimizer — Combines Shampoo-lite + Lookahead + P3. Beats AdamW by 14.4%. Trains Shakespeare language models on CPU in 120 seconds.

📐 Backloss Gradient Scaling — Analytical gradient correction for transformer linear layers. Derived from linear regression closed-form solution: grad_new = grad / (n × |x|)

🚀 ChunkBLAS Linear Attention — BLAS-friendly alternative to softmax attention. 42% faster on CPU at ctx=512 with O(n) complexity.

Transformer optimization · Gradient-free learning · CPU-first AI training · Small language models (SLM)

"Intelligence is sometimes simplicity. My formula proves it."