You-tldr-Summarize and Interact with YouTube Videos in your language

Hacker News

Last weekend, my brother and I sat spent some time revamping one of our older products, you-tldr ( https://you-tldr.com/ ) to the latest and greatest foundational models. We launched on HN back then, so I figured we'd do it again. The front end is made with Vercel and Tailwind, and the backend is a mixture of GCP Cloud Functions and a Fly.io FastAPI that utilizes LangChain and OpenAI GPT-3.5-turbo API to do the summary and chatbot. The product itself is 10x better: You can now get a concise summary of any video in seconds, and even ask questions about it in the Q&A chat window. No more wasted time slogging through long videos to find the information you need! Feedback and comments welcome!

Visit product View on Hacker NewsMar 23, 2023

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Launch Intel predictions

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

85%85% 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.

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% 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 · Strong signals: video · Missing: mobile apps, ios, personal

37%37% 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

36%36% 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

17%17% 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

17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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