As
Associative Memory, Perceptions, and Unconscious Bias
Hacker NewsAssociative Memory, Perceptions, and Unconscious Bias
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto86%86% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released36%36% 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, personal35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
A
A tool to mitigate against journalism bias52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A tool to mitigate against journalism bias
Hacker News1A
A better bias estimation for HyperLogLog33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A better bias estimation for HyperLogLog
Hacker News3Ge
Gender Bias Viewer32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Gender Bias Viewer
Hacker News3Ge
Gender Bias Viewer32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Gender Bias Viewer
Hacker News1Wo
Word2Vec Gender Bias Explorer32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Word2Vec Gender Bias Explorer
Hacker News4Wo
Word2Vec Gender Bias Explorer32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Word2Vec Gender Bias Explorer
Hacker News1Ho
How to Fix Media Bias with Staking and Slashing30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
How to Fix Media Bias with Staking and Slashing
Hacker News1To
Toasted – Remove gender bias from your writing48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Toasted – Remove gender bias from your writing
Hacker News5UnbiasedAI30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Media Bias Analyzer
Indie Hackerscommitment-side-projectTa
Tagged memory and minion cores in the lowRISC SoC43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Tagged memory and minion cores in the lowRISC SoC
Hacker News9