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The Real-World AI Foundry is a decentralized AI initiative by IoTeX that uses blockchain to reward contributors of live data, compute and validation for open Real-World Models, enabling secure, privacy-preserving AI across mobility, energy, healthcare and robotics.
Open, blockchain-powered AI ecosystem enabling verified live-data inputs.
Participants earn crypto rewards when models use their verified data or compute.
Built on ioID for decentralized identity, with encryption and zero-knowledge proofs protecting privacy.
Real-World AI Foundry: IoTeX launches decentralized AI to reward live-data contributors and secure models via blockchain. Learn how to join.
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IoTeX has launched the Real-World AI Foundry, a global initiative to build open, decentralized and blockchain-powered artificial intelligence that rewards users for contributing live data, compute and validation.
At the R3al World AI Summit during the Singapore Token2049 conference, IoTeX presented the Foundry together with founding Alignment Partners including Vodafone, the Blockchain Association, Filecoin, Theta Network and Aethir.
The R3al World AI Summit. Source: IoTeX
What is the Real-World AI Foundry and why does it matter?
The Real-World AI Foundry is designed to challenge centralized AI by creating an open ecosystem of Real-World Models (RWMs) that consume verified, live data from devices, sensors and humans and reward contributors via crypto incentives. This approach aims to increase transparency, interoperability and alignment with human values.
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🛡️ Control volatility
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⚙️ Execution you can rely on
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📒 Plan. Execute. Review.
Frameworks for consistent decision‑making.
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🧩 Choose clarity over complexity
Actionable, pro‑grade tools—no fluff.
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How do Real-World Models work?
Real-World Models are intelligent systems trained on continuous streams of verified live data. They are built to learn cause-and-effect, adapt to environmental changes and provide real-time responses for high-impact sectors such as mobility, energy, healthcare and robotics.
RWMs rely on onchain registries to track data provenance and usage, and use encryption with zero-knowledge proofs to protect data privacy. Governance begins with working groups from Alignment Partners and can evolve to token-based voting to avoid central control.
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Technical + flow + context synthesized into actionable plans.
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🧱 Consistency over hype
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🕒 Patience is an edge
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💼 Professional mentorship
Guidance from seasoned traders and structured feedback loops.
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🧮 Track • Review • Improve
Documented PnL tracking and post‑mortems to accelerate learning.
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How will contributors be rewarded?
Contributors—data providers, infrastructure partners and model builders—are rewarded based on the quality and frequency of their inputs. Each time an RWM accesses a verified data stream or compute resource, the action is recorded onchain and rewards are distributed accordingly.
This model aligns incentives for long-term participation and creates measurable metrics for contribution quality handled by onchain registries.
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📊 Make data your edge
Use depth and alerts to avoid guesswork.
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🧭 Be prepared, not reactive
Turn setups into rules before you trade.
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✍️ Plan first, then act
Entries, exits, and reviews that fit your routine.
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🧩 Consistency beats intensity
Small, repeatable steps win the long run.
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Why is decentralized identity important for the Foundry?
ioID, IoTeX’s decentralized identity protocol, verifies authenticity without exposing personal details. It allows devices and people to opt in as trusted sources while preserving privacy through encryption and zero-knowledge proofs. This ensures data reliability while respecting individual privacy.
What is the broader industry context?
Decentralized AI has gained momentum in 2025 with multiple projects raising institutional funding to build open infrastructure and verification protocols. Examples cited at the summit include decentralized verification efforts and open-source model funding rounds that highlight demand for alternatives to closed AI stacks.
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💬 Inner Circle access
See members share real‑time PnL and execution notes in chat.
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🧩 Turn theses into trades
Reusable templates for entries, risk, and review—end to end.
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💡 Long‑term mindset
Patience and discipline over noise; a process that compounds.
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📚 Education + execution
Courses, playbooks, and live market walkthroughs—learn by doing.
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🔒 Members‑only research drops
Curated analyses and private briefings—quality over quantity.
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These industry movements reinforce the Foundry’s premise: open ecosystems that combine verified live data, decentralized identity, and tokenized incentives can produce robust, trustworthy AI systems.
Frequently Asked Questions
How can an IoTeX device start contributing data?
Register the device with ioID, select permitted data streams and opt into the Foundry. Data is encrypted and submitted as verified streams; onchain registries record provenance and usage for reward allocation.
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🧱 Execute with discipline
Watchlists, alerts, and flexible order control.
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🧩 Keep your strategy simple
Clear rules and repeatable steps.
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🧠 Stay objective
Let data—not emotion—drive actions.
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⏱️ Trade when it makes sense
Your plan sets the timing—not the feed.
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🌿 A calm plan for busy markets
Set size and stops first, then execute.
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🧱 Your framework. Your rules.
Design entries/exits that fit your routine.
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Is personal data exposed when contributing?
No. ioID and zero-knowledge proofs are used to verify authenticity without revealing identifying details. Encryption protects data in transit and at rest.
Key Takeaways
Open ecosystem: The Foundry creates shared Real-World Models that use live, verified data.
Incentivized participation: Contributors earn crypto rewards recorded on onchain registries.
Privacy-first identity: ioID and zero-knowledge proofs secure contributor privacy while ensuring data authenticity.
Conclusion
The Real-World AI Foundry positions IoTeX and its Alignment Partners to build decentralized, reward-driven AI that emphasizes verified live data, privacy and collective governance. As RWMs roll out across mobility, energy, healthcare and robotics, participating organizations and individuals can expect transparent incentives and stronger model accountability.