GoGoBrowse – A Peer to Peer Web Browser

Hacker News

Hi HN! GoGoBrowse is a side project I've been working on that allows 2 users to browse the web together while voice chatting. It's a proof of concept for a new model of browsing the web I've been thinking about. My thought is that before a leap to a 3D Metaverse, we need a 2D Metaverse, which is simply social web browsing. I wrote more about it here: https://gogobrowse.com/before-the-metaverse-we-need-a-new-we... Though the goal of an entirely social web browser is still quite a ways off, I think of this as a small first step in that direction. I'd love any feedback on the app itself, and the general concept of social web browsing.

Visit product View on Hacker NewsApr 19, 2023

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26points

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

89%89% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% 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.

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

16%16% 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.

Correct prediction on native model

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