Ve

Vector retrieval for everything Louis Rossman has posted to YouTube

Hacker News

Vector retrieval for everything Louis Rossman has posted to YouTube

We’re really excited to kickoff our new series of demos with popular online influencers. Those of you that are active in the right-to-repair scene may appreciate this one. Introducing Search and RAG over the entirety of Louis Rossmann’s video archive! For those that don’t know Louis, he is an American independent repair technician, right to repair activist, and Youtuber with over 1.8 million subscribers. He is the owner and operator of Rossmann Repair Group in Austin, Texas. And is a partner at FUTO, where we are participating in their Summer Fellows Class.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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: new · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
52%52% 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
49%49% 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
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
24%24% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscribers, active · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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