AI Acceleration Business Research Project: Summer 2024 – Riverbed
Job Description Riverbed Acceleration Business Research Project: Summer 2024 === Duration: est. 8 weeks Requirements: Education: PhD-seeking student Summary: Area: Research into leveraging network optimization for Artificial Intelligence at the edge workflow for increased performance and security. Candidate Key areas of understanding: Large Language Models, AI training, hybrid AI techniques, Cloud AI, Edge device AI, AI Federated Learning Description: We are interested in investigating if there are ways to leverage network optimization strategies to help enable AI at the Edge. The research project includes investigating how hybrid AI scenarios with Federated Learning techniques could be optimized for performance and security using network optimizations. We are interested in scenarios using a hybrid technique where some of the processing is done locally and some in the cloud. Hybrid AI also allows for devices and cloud to run models concurrently – with devices running ‘light’ versions of the model for low latency while the cloud processes multiple tokens of the ‘full’ model in parallel and corrects the device answers if needed. We are interested in researching how much data is being transferred and if network optimizations such as scalable data referencing (SDR) be leveraged for reducing latency. Apply here Riverbed Acceleration Business Research Project: Summer 2024
AI Acceleration Business Research Project: Summer 2024 – Riverbed Read Post »