Local inference

Intelligence close to the person, their context, and their machine.

Keeping the loop nearby

Local models connect questions of capability with questions of ownership. In a learning system, local inference can sit beside the student’s notes, retrieved knowledge, and agent runtime.

The interesting tradeoff is broader than model size. What becomes possible when a person can inspect, keep, and change the system that works with their context?

A working entry. The connections may change.

↳ /connected to

Sato

local inference → supports the architecture of

Student-owned knowledge

local inference → can reinforce

Open systems

local inference → belongs in the conversation about