Get the gist of anyone's Twitter feed

Hacker News

Hey, I want to show you my demo AI-powered app that helps summarise someone's recent tweets to help you decide whether to follow them. It'll give you an idea of the tone and languages they use too, If you don't want to spend time scrolling through Tweets, let AI tell you what someone's been Tweeting about recently! Built with Haystack: https://github.com/deepset-ai/haystack It uses text-davinci-003 from OpenAI (for now) with a custom Haystack PromptTemplate. You can check out the source code here too: https://github.com/TuanaCelik/should-i-follow

Visit product View on Hacker NewsFeb 24, 2023

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5points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: openai, code, open · Missing: mac, agents, macos

56%56% 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: ide · Missing: https docs, excited, just released

42%42% 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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

23%23% 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

18%18% 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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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