Pinbot – An extension to privately search one's browser history with AI

Hacker News

Hello HN, I’m Kamil. The past months have been filled with news about ChatGPT, Bard, etc. Thankfully, there are some heroic attempts to bring that power to the users. I wanted to contribute to that effort with my side project, an extension for Chrome: it makes searching the history by meaning – instead of the exact words – possible. This is only a proof of concept, building on the excellent transformers.js[0], and running entirely in the browser. My goal here is to explore the possibilities unlocked by a client-side AI. I would love to have your feedback, to know which direction that project should follow! [0] https://xenova.github.io/transformers.js

Visit product View on Hacker NewsMay 17, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, chatgpt · Missing: mac, agents, macos

72%72% 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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, 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

43%43% 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: month, users · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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

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

Incorrect prediction on native model

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