AI-powered 24/7 QVC-style stream

Hacker News

Hey HN! Wanted to show a proof of concept for an AI-powered shopping stream, similar to QVC. Basically, an AI automatically pulls the top products from Amazon and pitches them to you, using AI-generated scripts and 3d models. Tech stack: -Sonnet 3.5 to generate the product pitches. It synthesizes data from product listing and reviews -OpenAI TTS for the voice -fal.ai for the 3d generation -three.js for the rendering environment -Amazon affiliate links Here's the Discord if you want to chat more about it! https://discord.gg/tvHSsmUJWA

Visit product View on Hacker NewsDec 12, 2024

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Actual performance

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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

80%80% 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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% 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

11%11% 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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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