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Spot the fake
in one click
Spot the
fake in
one click
The digital age has brought us instant access to news and content—but it also comes with an avalanche of misinformation.
FakeNews is a decentralized fact-checking subnet on the Bittensor network, designed to help you verify the credibility of news articles, social media posts, and trending claims with confidence.
FakeNews App
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Differences
By integrating AI-based fact-checking into the broader Bittensor ecosystem, FakeNews builds on the network’s proven track record of decentralized, incentive-based intelligence.
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Decentralization
No single entity controls the network, preventing censorship and ensuring resilience.
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Incentives
Miners earn rewards for contributing accurate fact- checks, while validators are rewarded for reliably assessing these contributions.
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Scalability
Bittensor’s design supports growth and adaptation, allowing the subnet to handle increasing volumes of fact-checks and evolving AI techniques.
Features
Real-Time Verification
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FakeNews provides instant fact-checking for news articles, social media posts, and online claims, helping users quickly determine the credibility of information.
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Dynamic Updates
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The system adapts to breaking news and evolving truths, providing users with the most current and accurate information.
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Community-Powered Accuracy
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By tapping into a global network of participants, FakeNews enhances the speed and scalability of fact-checking, fostering a more informed public.
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Advanced Technology
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Users benefit from cutting-edge technologies like natural language processing and knowledge graph models, which help detect misinformation effectively.
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Transparent and Reliable
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The platform employs a multi-source, multi-model reference approach to ensure accuracy and reduce subjectivity, making it easier for users to trust the information they receive.
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Decentralized and Resilient
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The platform operates without a single controlling authority, ensuring unbiased and reliable results by leveraging a global network of AI models.
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Built on the Bittensor
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Bittensor's open, decentralized platform incentivizes AI model, developer, and data provider collaboration.
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Multi-language support (French, Italian, German, Spanish)
Enhanced verification capabilities
Source credibility reputation system
Enhanced scoring system
99%+ accuracy rate
Roadmap
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Launch of subnet
JAN-MAR
Initial deployment of Version 1.0 to mainnet
Integrated core validation framework
Baseline miner infrastructure software
Major update 2.0
APR-JUN
Advanced checking and deep semantic analysis
Enhanced scoring system
Launch web interface
Release of main service
JUL-SEP
Release of comprehensive verification service
Enabling automated fact-checking for news articles
Supporting social media content and factual claims
Major Update 3.0
OCT-DEC
Enhanced accuracy (99%+)
New supported languages
Source credibility reputation system
FAQ
What is FakeNews?
FakeNews is a decentralized fact-checking platform built on the Bittensor network. It leverages advanced AI models to analyze and verify the credibility of news stories, facts, social media posts, and other digital content in real time.
How is it different from traditional fact-checking services?
Unlike centralized platforms, FakeNews uses a decentralized network of AI models that compete and collaborate to provide accurate results. This approach reduces bias and single points of failure, ensuring more reliable and accurate fact-checking.
How do I get started?
Simply enter the news article text or other text you want to verify. FakeNews will analyze it and let you know if it appears to be credible or potentially fake.
Will there be advanced analysis and source references?
Yes. We plan to introduce an advanced analysis feature later this year that will provide deeper insights and additional source references for verified content.
What languages does FakeNews support?
Initially, FakeNews focuses on English. Plans are in place to add French, Italian, German, and Spanish as the platform grows and more language models become available.
Where can I learn more about the technology behind FakeNews?
You can explore our whitepaper and Github for detailed insights into how the subnet, AI models, and validation processes work together to deliver fast, reliable fact-checks.
Company Registration Number: 16070826
Registered Office Address: 2nd Floor College House, 17 King Edwards Road, Ruislip, London, United Kingdom, HA4 7AE
Registered Office Address: 2nd Floor College House, 17 King Edwards Road, Ruislip, London, United Kingdom, HA4 7AE
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