Abstract
This publication describes a protocol that enables continuous generative artificial intelligence (AI) sessions by migrating active state-buffers between heterogeneous hardware devices based on spatial awareness. By utilizing proximity-triggered state buffering, cryptographic token sharing, and neural state re-hydration, the system securely transfers the tokenized and contextualized processing state of an ongoing language model conversation from a source device to a target device.
Keywords: generative artificial intelligence, AI session continuity, heterogeneous hardware, active state buffers, large language model, neural state re-hydration, proximity-triggered migration.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Goyal, Arpit, "Proximity-Triggered Context Migration for Generative AI Sessions Across Heterogeneous Devices", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9704