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Signalcrest
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devtoolsentity · one source so far

apple silicon

for mac developers

Steadygithub
Signal score
0
as of 18d ago
Live items
1
Trajectory
Too early
needs a few more snapshots

Why this scored 0

every term, weighted
Velocity+0.0 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+11.6 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+0.0 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty16.8 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite-5.2 → clamped to 0

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, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Signal history

7-day window (free)
Not enough history yet — the trend line fills in as snapshots accrue (every 30 min).

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.

  1. 1
    17

    Apple Silicon and macOS VMs: Faster LLM Inference with llama.cpp

    Faster LLM inference · for ai devs

    hackernewsSteadyai34d ago
  2. 2
    16

    We rebuilt the Linux MicroVM stack on Apple Silicon

    Rebuilt Linux microVM stack to run natively on Apple Silicon hardware. · for platform engineers, devops

    hackernewsSteadyhardware24d ago
  3. 3
    16

    H3-metal – Native MiniMax-H3 inference for Apple Silicon

    Native inference for Apple Silicon · for hardware devs

    hackernewsSteadyhardware34d ago
  4. 4
    0

    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 · linux72d ago
  5. 5
    0

    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

    githubSteady 2 · gemmaai19 saturated47d ago