MetalML
Quiet signalscikit-learn on your Mac's GPU, one import change
Launched 5d ago
Signal
18
Velocity
21
What this means
20%Vote pace is below typical for Developer Infrastructure.
Running at 20% of comparable launches.
24Founder Conviction Index: 24 — low signal.
Few of the conviction sub-signals (reputation, velocity, buyer-intent, tagline clarity) are firing yet.
4 launchesSerial maker — this is their 4th launch.
Best prior: Ollie Calorie Journal, attention 2.
Prediction
Top-5 finish probability
9%
today
Projected end-of-day votes
2range 2–3
Trajectory
stable
Not enough snapshots yet to detect trajectory.
Speed vs peers
0.2×
29 Developer Infrastructure launches
About
MetalML brings Metal GPU acceleration to scikit-learn. Change your import, keep fit, predict and transform, and supported operations run on the GPU with automatic CPU fallback. Open source, Apache 2.0. pip install metalml
AI Summary
MetalML enables GPU acceleration for scikit-learn on Mac devices by allowing a simple import change. It is open source under the Apache 2.0 license and supports automatic CPU fallback for operations not compatible with the GPU.
Attention & discussion velocity
Not enough snapshots yet. Run the snapshot worker every 15 min to build the time-series.
Performance
Pace needs two or more snapshots. This launch has 1, so velocity and momentum read as unmeasured rather than zero.
Velocity—
not measured
Momentum—
not measured
Virality—
not measured
Engagement—
not measured
Signal sources
2 of 6 active- Launch tracking1 reading since we picked it up
- AI analysisDeveloper Infrastructure
- Comment intelligencethread not yet analysed
- Outside discussionnot checked — domain is a storefront or shared
- Revenue signalsno match on this domain
- Editorial scoringbelow the signal threshold for this pass
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.