Beloga, Restoring Trust in Digital Media

Hacker News

Hello HN Community! I am excited to introduce Beloga, a platform we've built to help restore the trust of the public in information on the digital media landscape. As we all know, the digital age and generative AI has brought with it an explosion of possibilities, but also an overload of fake news and misinformation. This has created challenges for governments, individuals, and content creators alike, as they try to navigate the increasingly chaotic online space. With Beloga, we're aiming to address these problems by offering a platform that: - Helps individuals easily identify and consume factually accurate content. - Empowers content creators to speak their truth without the fear of censorship. Here's how Beloga works: - Our GPT-powered fact check tooling makes it easier for users to research specific claims made in each article. - We encourage community-driven moderation, allowing users to report and flag misleading information, further strengthening the accuracy of content on the platform. - Content creators can share their opinions, news, and other content with a web3 backend so that articles posted will have a censorship-resistant copy. - We believe that by giving content creators a safe space to express themselves and providing users with reliable information, we can restore trust in digital media and contribute to a more informed society. We would love to hear your thoughts, feedback, and suggestions as we continue to improve Beloga. Feel free to ask any questions or try out the platform at https://beloga.xyz. Let's work together to build a better digital media landscape! Check out Beloga: https://beloga.xyz Join us on Discord: https://discord.gg/ZpqnAxfw

Visit product View on Hacker NewsMay 8, 2023

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

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AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

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TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

29%29% 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 · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: web3, introduce · Missing: chat, 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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