Mo
Monitor ML model training on mobile
Hacker NewsMonitor ML model training on mobile
We developed a simple mobile app to monitor ML model training on mobile phones, with two lines of code to push training statistics. Client library (GitHub): https://github.com/lab-ml/labml App (Github): https://github.com/lab-ml/app Sample: https://web.lab-ml.com/run?run_uuid=d4722546f58411ea8addd3f9...
Share cardActual performance
7points
Made the leaderboard
Launch Intel predictions
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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, code · Missing: mac, agents, macos36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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