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 ...
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 ...
MarTech on MSN

How to build a Hermes agent-style workflow

Most AI tool workflows send the model far more data than it needs. The fix is a simple shift that cuts waste without cutting ...
TMCnet

K2view vs Delphix for Enterprise Data Masking - Which is Best?

Enterprise data masking tools help organizations protect sensitive data while still making it usable for testing, analytics, ...
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 Web Is Growing A Second Layer – Almost A Third Head

Google shipped two new specs weeks apart. Here's what OKF and ARD actually do, how they differ from LLMs.txt and MCP, and ...
Investopedia

Understanding Normal Goods: Definition, Demand, and Examples

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...