Co
Commentate – Join a live discussion with your favourite philosophers
Hacker NewsCommentate – Join a live discussion with your favourite philosophers
I've always dreamed of listening in on conversations between legendary minds in art and philosophy. I created a couple "rooms" that allow us to join in on these conversations, even participate. Still very early, with so many interesting ideas I want to implement. I would also love for the foundation contexts for commentators to be "open-sourced." Link below for anyone curious about how the base narratives are referenced. https://github.com/cmteone/commentators
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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: context, open · Missing: mac, agents, macos39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit12%12% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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