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Breaking Language Barriers: Read the News as It's Told

Hacker News

Breaking Language Barriers: Read the News as It's Told

As a digital nomad, I’ve been to places like Turkey, Serbia, Montenegro, Thailand, and Russia. One big hassle? Finding reliable local news and translating them into something I could actually read. I missed so much—like protests shutting down cities in Turkey or big election drama in Serbia. And don’t get me started on staying informed about Russia right now. But it’s not just a problem for travelers. Even if you don’t travel, language barriers make it way too easy for media to control which stories you see. Want to know what Russia says about Ukraine? Or how local media in Thailand covers global events? Without access to diverse sources, you’re stuck with whatever narrative is being pushed your way. That’s why I built ilmondo.live. It grabs news from around the world and translates it into English, Spanish, German, and Russian (for now). More languages, sources, categories? Just ask! The goal: make global news easy to access and read, without filters. You can even save your favorite countries and check updates while you sip your coffee. Once more the link: ilmondo.live Feedback? Ideas? Let me know!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
81%81% 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
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
55%55% 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
45%45% predicted probability of success on TrustMRR, 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
28%28% 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 · Strong signals: arr · Missing: mrr, revenue, profit
14%14% 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
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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