Waterloo's PAW compiles task specs into 23MB LoRA adapters a 600M-parameter model runs entirely offline.

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2, 2026, a system that compiles any natural-language task spec into a 23MB ...
InfoQ

NVIDIA Dynamo Addresses Multi-Node LLM Inference Challenges

Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for ...
VentureBeat

Perplexity AI unveils hybrid local-cloud inference system at Computex 2026

Perplexity AI, the fast-growing search startup now valued at $20 billion, unveiled what it calls the first hybrid local-server inference orchestrator at Computex 2026 on Monday night, demonstrating ...
Electronic Design

Three Tips for Boosting CNN Inference Performance

How to improve the performance of CNN architectures for inference tasks. How to reduce computing, memory, and bandwidth requirements of next-generation inferencing applications. This article presents ...
SiliconANGLE

Report: Nvidia is working on a top-secret AI inference chip that could debut next month

Nvidia Corp. is reportedly working on a dedicated inference processor that will be used by OpenAI Group PBC and other artificial intelligence companies to develop faster and more efficient models, ...