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Neil DeGrasse Tyson teaches you about vector search
Hacker NewsNeil DeGrasse Tyson teaches you about vector search
This is an AI generated TED talk from a system we built at the TED AI hackathon this weekend. It's built on top of ElevenLabs, SDXL and Wordware ( https://wordware.ai/ ). We also have a custom index of over 2 million arXiv papers and 6 million Wikipedia articles. All open source: https://github.com/ashvardanian/extrapolaTED
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Product HuntOn track for Day 1 leaderboard · Strong signals: elevenlabs, open · Missing: mac, agents, macos82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% 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, crypto6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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