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Cambrian – Copilot for AI Research

Hacker News

Cambrian – Copilot for AI Research

Everybody is struggling to keep up with the explosion in AI research. Information sources are decentralized, and there just isn’t enough time to understand each important paper that comes out. Cambrian is the all-in-one hub for discovering, understanding, and discussing AI research. - Search over 240,000 arXiv papers using natural language, or put in specific arXiv links directly. - Ask questions about the paper using CambrianGPT. - Chat directly with the PDF, with highlighting and note taking. - Conduct literature reviews on natural language topics summarizing the biggest insights in the field. - Send interesting papers to your friends on the platform, and make your bookmarks public to show the world what you’re reading. Try it out for free and let us know what you think!

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
89%89% 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: 000, io · Missing: https docs, excited, just released
63%63% 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, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, reviews · Missing: plus, intuitive, host
42%42% 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, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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