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Speech.is interop for Namecoin

Hacker News

Speech.is interop for Namecoin

I'm a core-contributor to Namecoin and the lead developer for Speech.is, an interoperability layer for Namecoin that I have been working on for the past year. While the main goal of the Speech.is website is to provide a scalable interop system that doesn't involve proxies or mirroring content, I was able to backport some of the censorship resistant properties of the Namecoin .bit TLD to regular websites. Speech.is reimplements DNS lookups within the browser itself. When coupled with emerging WebRTC P2P networks we are able to push all processing to the client side, shielding us from legal liability. The special speech.is#name.bit syntax makes it impossible for governments to selectively censor websites and very difficult for politicians and judges to rationalize their way into blacklisting the entire domain. The www.speech.is website has the full nitty-gritty, but remember that this is a developer preview!

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
83%83% 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
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
44%44% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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