Loading…
Price Range
$120,000 – $250,000
This patent describes a way to run AI models by splitting the work across multiple nearby devices instead of sending everything to the cloud, making AI faster and more private.
A system and method for partitioning and distributing neural network inference workloads across heterogeneous edge computing devices. The invention enables real-time AI processing without cloud dependency by intelligently splitting model layers across available local compute resources.
Dynamic model partitioning based on device capability profiling
Peer-to-peer inference pipeline with fault tolerance
Adaptive compression for inter-device tensor communication
Privacy-preserving distributed inference without centralized data aggregation
$120,000 – $250,000
Final price subject to negotiation
None
Get in touch with our team to discuss licensing or acquisition options.
