cfregly/ai-performance-engineering — GitHub trend

FINDING #3132 · UNIT ID 970097176

cfregly/ai-performance-engineering

Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.

[ PYTHON ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.00658

ENGAGEMENT0.33

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

1% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

8.33

ACCEL

-1.50

RETENTION

54.2%

PEAK 2026-08-27 · FORK-RETENTION 0.0% · 25 STARS / WINDOW

Author Audience

AUDIENCE

1,227

FOLLOWERS

1,030

OWNER ★

1,977

Engagement Signals

FORKS

262

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 25 / 25 (DIVERSITY 1.00)

Why This Is A Finding

cfregly/ai-performance-engineering собрал 25 звёзд за окно, тогда как у автора всего 1,030 подписчиков — эффективная аудитория ≈ 1,227. Это даёт surprise-индекс 0.00658 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

Related Findings

RANKS ABOVE 66% OF 9102 FINDINGS

#08User0332/rewards-farmer[ PYTHON ]0.75 #09wang2122/sprix-sage-router[ PYTHON ]0.62 #16amagine-ai/Amagine3D[ PYTHON ]0.50 #19framepipe-dev/media-inference-worker[ PYTHON ]0.47 #24zeenie-ai/OpenCompany[ PYTHON ]0.44

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9102 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00+0.00ABOVE 66%

VELOCITY8.335.67+2.67ABOVE 64%

RETENTION54.2%45.5%+8.7 PPABOVE 61%

FORKS262340-77ABOVE 45%

SURPRISE0.010.00+0.00ABOVE 57%