apple silicon
for ai devs, mac users
Steady10
signal score
1
live items
↓ Cooling
7-day est. ~0
Why this scored 10
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~0
range 0–0
14-day
~0
range 0–0
30-day
~0
range 0–0
Signal history
7-day window (free)— — projected trajectory (estimate, not a guarantee)
The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 10
dji-4g-vohive-mac — 在 Mac(Apple Silicon / Intel)上用 UTM 跑 Linux 虚拟机,把大疆 4G 模块(EG25-G)伪装成移远 Quectel EC25 并部署 vohive 平台的完整步骤
githubSteady🔗 2 · linux26d ago - 20
turbo-fieldfare — Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook
AI model runs on macbooks — for ai devs, mac users
githubaiSteady🔗 2 · gemma−19 saturated2d ago