GoKawiilRust-built PSSA model outpaces transformer in speed and loss on WikiText-103 test
A developer built PSSA, a non-transformer language model coded from scratch in Rust without any ML framework, using a recurrent state-space layer, an episodic memory bank, and weights that update while the model runs. Tested against a matched-parameter standard transformer on identical data, PSSA reached a training loss of 3.98 versus the transformer's 4.43 over 12.7 million tokens, and generated text about twelve times faster on the same CPU. On a held-out 198,939-token slice neither model trained on, PSSA also scored lower loss throughout every checkpoint.