
Actual performance
8upvotes
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
77%77% predicted probability of success on BetaList, based on ML models trained on real launch data.
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Su
SubwAI – an AI trained to play Subway Surfers using CNN30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
SubwAI – an AI trained to play Subway Surfers using CNN
Th
ThiruvalluvarGPT – GPT model trained using Tamil Tirukkural Poems46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
ThiruvalluvarGPT – GPT model trained using Tamil Tirukkural Poems
Glendale AZ Movers14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Reliable Movers in Glendale, AZ
Re
Restate – Build reliable back ends using state machines54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Restate – Build reliable back ends using state machines
Re
Reliable Server-Sent Events for Django, using Pushpin39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Reliable Server-Sent Events for Django, using Pushpin
Op
Operon – Reliable Agents Using Biological Motifs and Category Theory43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Operon – Reliable Agents Using Biological Motifs and Category Theory
I
I trained a GPT-2 1.5B Subreddit Simulator in 3 days using 88 TPUs52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I trained a GPT-2 1.5B Subreddit Simulator in 3 days using 88 TPUs
Wr
Write with Transformer (Trained on ArXiv NLP)65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Write with Transformer (Trained on ArXiv NLP)
Sl
Slang Thesaurus – An AI-Powered Slang Thesaurus Trained on UrbanDict33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Slang Thesaurus – An AI-Powered Slang Thesaurus Trained on UrbanDict
Hu
Human Headers39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Human Headers