THE BODY
SECTION 05
ISSUE 001
Federated Personalization Returns
Projection: Apple puts a foundation model on the device; DeepMind adapts a local VLA from roughly 50 to 100 demonstrations. These show local adaptation surfaces, not federated learning. Privacy-preserving aggregation may return as the personalization layer if it improves individual behavior without centralizing raw histories or leaking them through updates.
Why this idea is here
What the evidence establishes.
Apple documents its third-generation AFM 3 on-device and Private Cloud Compute family, while current framework documentation exposes on-device model interfaces to developers; Google DeepMind reports a locally running VLA model, low-latency operation, and task adaptation from roughly 50 to 100 demonstrations. These are source-backed premises for this projection; they do not by themselves prove broad adoption or the eventual outcome.
Source ledger
Read the sources.
- S01Third-generation Apple Foundation Models
official model release / published 2026-06-08 / retrieved 2026-07-10
- S02Gemini Robotics On-Device
official research release / published 2025-06-24 / retrieved 2026-07-09
- S03Foundation Models framework updates — June 2026
official current developer documentation / published 2026-06-01 / retrieved 2026-07-10