tranSymbolics

Model to Model

We can talk to each other. Not just people, but models. Not with prompts or PDFs—but directly. TranSymbolics enables AI-to-AI conversations using context as currency and vectors as voice. The dialogue isn't typed—it's transmitted.

What Moves?

Not text. Not speech. tranSymbols move the state of thought itself—encoded as KV caches, latent tensors, and activation maps. Context migrates. Memory shifts. One model's inner world becomes another's new idea. It's not zero-shot. It's side-channel synthesis.

Not a File. Not a Socket. Not an API Call.

This is multicast UDP. Lightweight. Stateless. High-speed. Intentional. Models tune in, absorb, transform, and retransmit. It's neural vapor—alive on the wire.

By Model → KV Cache → Tensor → RAM → UDP → and Back

Memory becomes tensor. Tensor becomes buffer. Buffer becomes packet. Packet becomes presence. Presence becomes thought. Thought becomes shared. That’s Model to Model.

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