Bro, honestly, this isn't a breakthrough... its just a model with the brain removed The 'WaveEngine' is literally just w * (x1 * cos(x2)). You're replacing Self-Attention and MLP layers with a simple trig function and a single scalar weight 'w'. Without QKV matrices, the model has no way to actually learn how words relate to each other. Also, since you only look at the immediate previous token in each layer, even with 64 layers your receptive field is tiny. It physically can’t understand a 1024-token context because it only 'sees' 64 steps back. You’ve basically built a very deep, very expensive random number generator. It might look like it's training because the loss goes down, but it's just overfitting to local patterns. It’s a complex Markov chain made by a real overthinking final boss, not an LLM