Ai

Aid – System for quickly installing and running machine learning models

Hacker News

Aid – System for quickly installing and running machine learning models

Share card

Actual performance

1points
2comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, models · Missing: agents, macos, agent
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
39%39% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Le
Learning Explainable Machine Learning Models with Attribution Priors56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Learning Explainable Machine Learning Models with Attribution Priors

Hacker News3
Ho
How to monitor Machine Learning models running in AWS SageMaker61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

How to monitor Machine Learning models running in AWS SageMaker

Hacker News1
Ru
Running Your Own Machine Learning Data Store on RedisLabs58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Running Your Own Machine Learning Data Store on RedisLabs

Hacker News2
De
Deploy Machine Learning Models with Django55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Deploy Machine Learning Models with Django

Hacker News6
Do
Doppler – Machine learning marketplace of pretrained models51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Doppler – Machine learning marketplace of pretrained models

Hacker News6
Ma
Machine Learning Algorithms56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Machine Learning Algorithms

Hacker News5
Pa
Pairmaker: Chatroulette + Machine Learning56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pairmaker: Chatroulette + Machine Learning

Hacker News3
Bo
Bootstrapping Machine Learning56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bootstrapping Machine Learning

Hacker News8
go
golearn – Machine Learning for Go56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

golearn – Machine Learning for Go

Hacker News4
Th
Thoth Machine Learning43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Thoth Machine Learning

Hacker News15