OpenTMP Collaborative Intelligence Substrate

The Collaborative Intelligence Substrate (CIS) enables efficient deployment and continuous optimisation of AI models across robotics and intelligent hardware through edge-cloud collaborative inference and on-device training capabilities. In terms of inference performance CIS utilises an edge-cloud task orchestration mechanism to significantly reduce local model latency while improving In terms of inference performance CIS utilises an edge-cloud task orchestration mechanism to significantly reduce local model latency while improving stability and generalization in complex real-world environments. For training performance CIS supports on-device continuous training and distributed model updates allowing data required for model iteration to remain on local devices. This ensures strong protection of user privacy and commercial data confidentiality while enabling continuous improvement of AI capabilities. In terms of deployment efficiency CIS supports In terms of deployment efficiency CIS supports heterogeneous computing architectures including CPU GPU and NPU and is compatible with diverse device form factors. This significantly improves large-scale AI deployment efficiency across robotics and AI hardware scenarios. By reducing dependence on cloud compute resources and network bandwidth CIS also lowers total system operating costs while improving AI capabilities. By reducing dependence on cloud compute resources and network bandwidth CIS also lowers total system operating costs while improving long-term system stability and scalability.