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 ...
Tech Times

Compile Once, Run Offline: New AI Method Matches 32B Models With a 23MB File

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
InfoQ

Enhancing Reliability Using Service-Level Prioritized Load Shedding at Netflix

The speakers discuss Netflix’s architecture for surviving extreme traffic spikes. They explain the mechanics of prioritized ...

The new SEO stack: What replaces your old toolset

See how LLMs, APIs and scripts cut busywork, uncover AI search signals and help teams move faster without ditching core SEO ...