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Scholarstream.ai – an AI-generated feed of articles from ArXiv

Hacker News

Scholarstream.ai – an AI-generated feed of articles from ArXiv

Hi HN, ScholarStream is a project I built over the holidays to explore OpenAI and ChatGPT. I’m trying to read more interesting academic papers and less social media, but have a strong firehose itch. ScholarStream tries to solve that with a feed of academic papers presented in a more engaging way using AI. I leaned into the “AI makes this page” idea by using ChatGPT to create the site name, write the landing page copy, and OpenAI to generate the logo. I wrote the code and the /about page. Feedback very welcome

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best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, openai, using · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% 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.

Correct prediction on native model

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