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Ambient AI assistant

Under a storage limit, which transcripts should an on-device assistant keep, and what survives?

research/ambient-memory

What an on-device assistant should keep from a week of simulated transcripts: BM25 retrieval, extractive summaries and byte-limited retention policies (stylised)

9 tests

What it found

Seven simulated days of 1500 utterances each with 6 planted facts per day. BM25 finds every fact (hit@5 = 1.00) when the key words are rare, which is the easy case. With the store limited to 10% of the week, dropping oldest or random utterances keeps 0.11 and 0.10 of the facts; keeping the highest mean-IDF utterances keeps 0.93, because the facts are rare-word lines by construction. An importance-ranked extractive summary at 5% of a day holds 85% of its facts, against 3% for the first lines. Index build 0.04 s, query 1.9 ms on one container CPU. Stylised: synthetic words, lexical queries, no paraphrase, no speech errors. Produced with AI assistance.

A figure from its own output

Figure produced by research/ambient-memory: retention
ambient-memory/experiments/retention.svg, written by the project's own experiment code.

Paper, code and results

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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.