Tech Meridian ← ENTITY INDEX
PROMY MERIDIAN RU

COMPANY · ENTITY #7249

Jetson Thor

Related event timeline, sources and context from the news index.

EVENT TIMELINE

2

COMPANIES · 1 SOURCE · NVIDIA Developer

NVIDIA demonstrates TensorRT Edge-LLM workflow to run Nemotron-3.5 Lightning on DGX Spark 64GB

NVIDIA published a tutorial showing how to use TensorRT Edge-LLM (examples tested with Edge-LLM 0.11.1 and TensorRT 10.16.1.11) on a DGX Spark 64GB to prototype, fine-tune and test embedded AI models. The trtedge CLI downloads models and builds optimized TensorRT engines, supports serving via a local OpenAI-compatible API, and can enable DSpark speculative decoding (reported to raise mean generation from 73.4 to 126.9 tokens/s on HumanEval prompts while keeping peak memory at 27.9GB).

7.0

RESEARCH · 1 SOURCE · Microsoft Research

Study: Offloading inference boosts mobile manipulation robots' performance, battery life, and model scale

A primary technical report challenges the default of running inference solely on onboard GPUs for physical AI, showing that offloading inference to edge or cloud GPUs can raise task success rates, enable larger models, and extend battery life across mobile manipulation workloads. The authors quantify large effects—e.g., mapping/planning slowdowns up to 383% on smaller GPUs vs. an A100, navigation detection drops around 30%, accuracy losses up to ~50% for some models, and onboard GPUs increasing battery drain (example: Jetson Thor up to ~160%)—and introduce a Kubernetes-based Physical AI Toolchain for containerizing and orchestrating distributed robotics inference.

7.0