This is the first 200,000 sequence length bert experiment from my cantor research. Trained specifically with cantor attention routing as a mechanism. The proof is attached.

This is meant to encapsulate the potential for infinite rope through cantor fractal structures. You likely won't even need to install the geofractal repo for the test case.

This showcases the direct causal response by testing how well the model can represent data along very long chains.

AI enthusiasm aside, I know distance isn't an illusion - it's a representation of measure. Gemini is a bit eccentric, however Gemini is also the most likely to rip apart ideas like this under scrutiny.

Everything led to the RoPE enhancement. Simply drop the trainer into a colab cell on an a100 80 gb and start it up.

This is proof for the baseline of this concept. The foundational math works. Everything relational to this behavior is to be expanded directly into a full wide bert with the relational complexity of a standard bert.

This model will be trained wide and shallow. The VRAM will likely fill the entirey A100 80 gig for the first sets and then shrink abruptly from there, but not necessarily required.

The cantor fractal routing has been proven, the rope has now been proven to allow skipping, and the system is entirely relationally compatible with truthful training.

I will be drafting a paper tomorrow specific to this ruleset and the importance of the necessity for certain guidelines to be upheld for full cohesion with certain elements.

If you're reading this, thank you for following me and baring with this endurance test of irrationality mixed with rationality.