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NVIDIA released Cosmos 3 Edge, a 4-billion-parameter open world model for edge devices that helps robots and vision AI agents understand surroundings, reason in real time, and generate actions. It achieves best-in-class throughput and accuracy among similar-sized models.
PrintGuard 2.0 is a major rewrite of a few-shot FDM fault detector using a ShuffleNetV2 backbone and prototypical network, now with a single Python engine that runs unmodified on both CPython and Pyodide in the browser via a platform abstraction layer, enabling per-printer sensitivity tuning and fair inference scheduling.
This paper proposes a novel framework that uses LLMs to extract analytical physics priors from scientific literature and distills them into a lightweight neural network for high-accuracy, real-time manufacturing process-property prediction, even with limited data.
Flash-WAM introduces a modality-aware distillation method for world-action models, achieving real-time inference by compressing diffusion to a single step per modality, resulting in 23x speedup.
Kog announces real-time LLM inference achieving 3000+ output tokens per second per request on standard datacenter GPUs, bringing high-speed inference previously limited to custom silicon to production hardware.
This paper presents a systematic optimization study of real-time diffusion model inference on the Apple M3 Ultra, achieving 22.7 FPS at 512x512 resolution using CoreML conversion and a distillation model, revealing that CUDA-optimized techniques do not directly transfer to Apple's unified memory architecture.