ASTRA | Self-Learning — Learning from Usage, Not Just Datasets

05 · Self-learning

Learns from usage, not just from datasets

The four-moment pipeline behind 'self-learning': record, judge, update, consolidate.

no human retraining loop

With explicit consent, interactions are logged as structured experience — what was asked, what was done, what happened next.

The result is compared to the prediction the loop made before acting. Reward comes from outcomes, not from matching a static label.

Weight updates and policy changes are derived from that reflection. The next similar task starts from a slightly better state.

What works is folded into memory and reusable routines, so the loop gets faster at tasks it has seen before.

·Strict data consent — nothing is learned from without permission

·No silent autonomy — guardrails and sandbox are non-negotiable

·Progress is measured with honest, reproducible evaluations

·Failures are logged and studied, never papered over