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Introducing OpenLedger Datanet: Data across domains is often fragmented, unreliable, and lacks clear attribution , making it difficult to use as a trusted foundation for AI. Datanet transforms these raw contributions into structured, transparent, and attributable networks that power Specialized AI with verifiable provenance and explainability. Read more:

OpenLedger

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199,553 views • 8 months ago •via X (Twitter)

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OpenLedger is powering decentralized AI inference with DGrid AI, built on verifiable, onchain infrastructure. DGrid routes AI workloads across a distributed compute network, while OpenLedger anchors execution, attribution, and settlement fully onchain. Together, this enables AI systems that are auditable by design, transparent in cost and performance, and built for real Web3 applications.

OpenLedger is powering decentralized AI inference with DGrid AI, built on verifiable, onchain infrastructure. DGrid routes AI workloads across a distributed compute network, while OpenLedger anchors execution, attribution, and settlement fully onchain. Together, this enables AI systems that are auditable by design, transparent in cost and performance, and built for real Web3 applications.

OpenLedger

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AI runs on data. But if the data is centralized, the power stays locked with a few. OpenLedger flips that. Decentralized data means transparency, attribution, and fair rewards for every contributor🐙

AI runs on data. But if the data is centralized, the power stays locked with a few. OpenLedger flips that. Decentralized data means transparency, attribution, and fair rewards for every contributor🐙

OpenLedger

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Trusted AI begins with trusted sources. As Dr. Kim Wager of Oxford PharmaGenesis highlights, data must be properly extracted, transformed into knowledge, and made interoperable across formats and domains. That’s the foundation of trustworthy AI, powered by OriginTrail.

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OriginTrail

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Tired of generic, hallucinating LLMs? We use AI for almost everything these days, whether it’s helping with math homework or looking up remedies when we’re sick. It's become part of our daily routines. Now imagine if Einstein helped you solve that homework, or Eminem wrote the lyrics for your next rap song. What if your AI was built specifically for your world? Trained on your domain, your data, you become the master of it. Introducing OpenLedger AI Studio. A powerful platform to build and use specialized models with built-in explainability and attribution. Fine-tune using your data through our Model Factory, and deploy them seamlessly. Your models won’t just reason - With OpenLedger, you can explain every decision, trace its data, and reward contributors. Truly Open, Verified, and Explainable AI begins here.

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OpenLedger

172,497 views • 11 months ago

VAAP Highlights: Devium, built on zkPass. Devium enables private order data + AI by storing users' order data on Devium's decentralized network nodes. It categorizes the data into vertical sectors and trains specialized AI large models for these vertical domains. These large models support enterprise operations, product development, and upgrades within their respective industries. By replacing data hosting with verifiable proofs, Devium reduces platform risks and minimizes user friction. Devium empowers teams to build real-world applications on verifiable infrastructure such as zkTLS.

VAAP Highlights: Devium, built on zkPass. Devium enables private order data + AI by storing users' order data on Devium's decentralized network nodes. It categorizes the data into vertical sectors and trains specialized AI large models for these vertical domains. These large models support enterprise operations, product development, and upgrades within their respective industries. By replacing data hosting with verifiable proofs, Devium reduces platform risks and minimizes user friction. Devium empowers teams to build real-world applications on verifiable infrastructure such as zkTLS.

zkPass

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Highlights of the OpenLedger journey: OpenLedger is the AI Blockchain unlocking liquidity for data, models, and agents, backed by Polychain, Balaji Srinivasan (ex-Coinbase CTO), and more. $14.7M+ in revenue from global enterprise projects and $91M+ in investment commitments secured. Worked with global enterprises like Walmart, Sony, Meta LLaMA, Viacom, and others. Built on Stanford’s data attribution research paper, enabling verifiable, fair rewards for contributors. 40+ projects, including ex-Google DeepMind teams and top DeFi builders, are building specialized AI models. 1M+ AI nodes, 25M+ transactions, and 20K+ models, real-world usage at scale.

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OpenLedger

731,612 views • 10 months ago

✈️ Starting the day in Istanbul. Let's talk AI. The future of AI won't be shaped by size, but by precision. Lately I've been diving into what OpenLedger has been building, and I think we're witnessing one of the most important hard forks in AI: 👉 From giant generalist models 👉 To focused, hightrust AI agents Here's why that shift matters , and why OpenLedger's vision makes perfect sense: ✅ Specialized > Generalized General AI can do many things. But specialized AI? It does one thing extraordinarily well. Tailored models don't waste compute on irrelevant context, every parameter is purposedriven. ✅ Explainability isn't optional anymore In highstakes sectors like finance or healthcare, because the model said so won't cut it. We need transparent reasoning paths. Models must show how they reached conclusions , not just what they concluded. ✅ Trust comes from traceability With OpenLedger's Proof of Attribution, each AI decision is traceable, verifiable, and tamperproof. We're talking onchain records of who contributed what , accountability by design. ✅ Less hallucination, more signal Smaller, specialized models trained on clean, domainspecific data are far less prone to hallucinations. Clear boundaries = higher reliability. ✅ Efficiency is the real scalability Deploying one massive model for everything? Expensive, slow, and unsustainable. Specialized AI is leaner, faster, and far more costeffective. In short, OpenLedger isn't just following a trend. They're laying the rails for the infrastructure layer of verifiable, domainaware AI. And in a space flooded with blackbox models and hype, that clarity hits different.

✈️ Starting the day in Istanbul. Let's talk AI. The future of AI won't be shaped by size, but by precision. Lately I've been diving into what OpenLedger has been building, and I think we're witnessing one of the most important hard forks in AI: 👉 From giant generalist models 👉 To focused, hightrust AI agents Here's why that shift matters , and why OpenLedger's vision makes perfect sense: ✅ Specialized > Generalized General AI can do many things. But specialized AI? It does one thing extraordinarily well. Tailored models don't waste compute on irrelevant context, every parameter is purposedriven. ✅ Explainability isn't optional anymore In highstakes sectors like finance or healthcare, because the model said so won't cut it. We need transparent reasoning paths. Models must show how they reached conclusions , not just what they concluded. ✅ Trust comes from traceability With OpenLedger's Proof of Attribution, each AI decision is traceable, verifiable, and tamperproof. We're talking onchain records of who contributed what , accountability by design. ✅ Less hallucination, more signal Smaller, specialized models trained on clean, domainspecific data are far less prone to hallucinations. Clear boundaries = higher reliability. ✅ Efficiency is the real scalability Deploying one massive model for everything? Expensive, slow, and unsustainable. Specialized AI is leaner, faster, and far more costeffective. In short, OpenLedger isn't just following a trend. They're laying the rails for the infrastructure layer of verifiable, domainaware AI. And in a space flooded with blackbox models and hype, that clarity hits different.

Crypto Sinan

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Meet watsonx, our AI and data platform built for business. Leveraging the power of foundation models, generative AI and ML, #watsonx can make the most of your data and offers trusted, scalable, adaptable #AI to embed deep into your business. Learn more:

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IBM

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OpenLedger X Morpheus The partnership of openledger with Morpheus enables Use Morpheus to build "The Autonomous Smart Contract Engineer" on top of OpenLedger. What is Morpheus? Morpheus is a Web3-native AI coding agent that turns natural language into executable smart contracts and full-stack dApps. It is powered by a specialized Solidity model built on top of OpenLedger, tailored for the unique demands of secure and efficient onchain development. It goes beyond code generation. Using fine-tuned models, agent-based architecture, and modular plugin support, Morpheus automates the entire development pipeline-from writing and simulating contracts to deploying and maintaining them. Its mission is to reduce the barrier to dApp creation while enabling autonomous agents and individuals to participate in decentralized economies. Why OpenLedger? The rise of AI agents in Web3 raises urgent questions around transparency, attribution, explainability, and contributor incentives. 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OpenLedger supports Morpheus by: Recording which data was used in generating model outputs Enabling verifiable attribution of contributed datasets Powering reward mechanisms for contributors Offering scalable and efficient model execution via OpenLoRA Supporting transparency and traceability in model decision-making This creates an open, rewardable foundation for AI-driven coding-without relying on opaque systems. How is the system built? The Morpheus architecture has three layers: Datanet Layer OpenLedger powers Morpheus with a specialized Datanet - a decentralized data layer where developers, auditors, and contributors can share smart contract patterns, audit logs, exploit reports, and logic modules. Each submission is recorded onchain with attribution using OpenLedger’s Proof of Attribution. As the model learns and evolves from this data, contributors receive rewards proportional to their impact on future outputs. The Morpheus architecture has two layers: Intent Layer Users describe what they want to build. Example: "Create a token with tax logic that routes to a DAO." Morpheus parses the instruction, retrieves relevant contract types, and plans a modular execution flow. Agent Layer The agent generates, tests, and assembles the contract. It handles versioning, logic validation, and deployment readiness. Security checks-reentrancy protection, overflow control, gas modeling-are embedded into the generation phase. Generated outputs are mapped to their source data using OpenLedger’s Proof of Attribution, providing traceability across the pipeline. How does the AI model work? Morpheus is being powered by a specialized Solidity model built on top of OpenLedger. This model is purpose-built to handle the nuances of smart contract logic, security, and upgradeability. Unlike generalized coding agents, it is designed specifically for EVM environments and Web3 use cases, drawing from real protocol data and security best practices. Morpheus is fine-tuned on a vertical stack of smart contract data: Audited protocol code (e.g., Uniswap V4, Compound) OpenZeppelin libraries and EIP reference implementations Smart contract vulnerability reports and exploit reconstructions Edge cases from fuzz testing and adversarial examples It uses models like CodeLlama and DeepSeek-Coder, enhanced through RAG pipelines referencing standardized security patterns and emerging protocol designs. This training stack is integrated into a continuous feedback loop, enabling real-time specialization for EVM and beyond. Why a specialized model is needed? Smart contract development is uniquely high-stakes. A generalized AI model is not enough. As 'vibe coding' and natural language programming become more common, we're seeing an influx of AI-generated code in Web3 as well. But smart contracts are not frontends or prototypes-they govern real value, enforce trustless execution, and often become immutable after deployment. Billions have been lost in Web3 due to bugs and inefficiencies: In 2022 alone, over $3.8 billion was stolen due to smart contract exploits, many of which stemmed from avoidable issues like reentrancy, integer overflows, or access control failures. Inefficient contract structures lead to unnecessary gas consumption. Optimizing for gas can reduce costs by up to 40%, saving projects millions over time. Upgradeable contract patterns, like UUPS or Transparent Proxies, require strict adherence to storage layout and initialization rules. Mistakes here often go undetected by generic models and can render a contract unupgradeable or vulnerable. A specialized Solidity model is trained on real-world exploits, EIP standards, and libraries like OpenZeppelin to: Generate secure, gas-efficient code by default Recognize and correctly implement complex proxy patterns Map user intent to modular, auditable contract architectures Incorporate battle-tested logic from audited protocols and fuzz-tested edge cases Morpheus goes beyond syntax-it understands the nuances of decentralized infrastructure and deploys code that meets production-grade standards. What applications will this enable Token creation with built-in logic (tax, liquidity, governance) DeFi automations triggered by market conditions Payment contracts between agents and contributors DAO tooling with dynamic NFT-based voting Cross-chain bridging logic tied to real-world oracles Asset issuance flows through chat-based interfaces Natural language contract templates with reusable logic Each of these flows is backed by OpenLedger’s Proof of Attribution-ensuring traceability, explainability, and fair rewards across the ecosystem. This is the future of AI-native development. Open. Attributed. Explainable. Community-powered. Morpheus and OpenLedger are building the first system for autonomous coding agents where: Contributor work is recorded onchain Reuse is incentivized through attribution Model outputs are traceable and explainable Contracts evolve through human-agent collaboration Anyone can contribute prompts, logic, or flows-and get rewarded The smart contract engineer is no longer a human-only role. It is an agentic, decentralized, and transparent process-powered by OpenLedger.

OpenLedger X Morpheus The partnership of openledger with Morpheus enables Use Morpheus to build "The Autonomous Smart Contract Engineer" on top of OpenLedger. What is Morpheus? Morpheus is a Web3-native AI coding agent that turns natural language into executable smart contracts and full-stack dApps. It is powered by a specialized Solidity model built on top of OpenLedger, tailored for the unique demands of secure and efficient onchain development. It goes beyond code generation. Using fine-tuned models, agent-based architecture, and modular plugin support, Morpheus automates the entire development pipeline-from writing and simulating contracts to deploying and maintaining them. Its mission is to reduce the barrier to dApp creation while enabling autonomous agents and individuals to participate in decentralized economies. Why OpenLedger? The rise of AI agents in Web3 raises urgent questions around transparency, attribution, explainability, and contributor incentives. OpenLedger provides the infrastructure to ensure that contributor data used in model outputs is recorded with verifiable attribution. Through Proof of Attribution, contributors-whether they provide prompts, datasets, or logic refinements-can receive credit and rewards when their work influences model behavior. But attribution alone isn’t enough. In critical domains like smart contract deployment, DeFi automation, and DAO governance, understanding why a model made a decision is just as important as the output itself. OpenLedger supports explainability by linking outputs back to their original data sources-allowing developers and auditors to trace logic, validate decisions, and build trust in AI-powered systems. OpenLedger supports Morpheus by: Recording which data was used in generating model outputs Enabling verifiable attribution of contributed datasets Powering reward mechanisms for contributors Offering scalable and efficient model execution via OpenLoRA Supporting transparency and traceability in model decision-making This creates an open, rewardable foundation for AI-driven coding-without relying on opaque systems. How is the system built? The Morpheus architecture has three layers: Datanet Layer OpenLedger powers Morpheus with a specialized Datanet - a decentralized data layer where developers, auditors, and contributors can share smart contract patterns, audit logs, exploit reports, and logic modules. Each submission is recorded onchain with attribution using OpenLedger’s Proof of Attribution. As the model learns and evolves from this data, contributors receive rewards proportional to their impact on future outputs. The Morpheus architecture has two layers: Intent Layer Users describe what they want to build. Example: "Create a token with tax logic that routes to a DAO." Morpheus parses the instruction, retrieves relevant contract types, and plans a modular execution flow. Agent Layer The agent generates, tests, and assembles the contract. It handles versioning, logic validation, and deployment readiness. Security checks-reentrancy protection, overflow control, gas modeling-are embedded into the generation phase. Generated outputs are mapped to their source data using OpenLedger’s Proof of Attribution, providing traceability across the pipeline. How does the AI model work? Morpheus is being powered by a specialized Solidity model built on top of OpenLedger. This model is purpose-built to handle the nuances of smart contract logic, security, and upgradeability. Unlike generalized coding agents, it is designed specifically for EVM environments and Web3 use cases, drawing from real protocol data and security best practices. Morpheus is fine-tuned on a vertical stack of smart contract data: Audited protocol code (e.g., Uniswap V4, Compound) OpenZeppelin libraries and EIP reference implementations Smart contract vulnerability reports and exploit reconstructions Edge cases from fuzz testing and adversarial examples It uses models like CodeLlama and DeepSeek-Coder, enhanced through RAG pipelines referencing standardized security patterns and emerging protocol designs. This training stack is integrated into a continuous feedback loop, enabling real-time specialization for EVM and beyond. Why a specialized model is needed? Smart contract development is uniquely high-stakes. A generalized AI model is not enough. As 'vibe coding' and natural language programming become more common, we're seeing an influx of AI-generated code in Web3 as well. But smart contracts are not frontends or prototypes-they govern real value, enforce trustless execution, and often become immutable after deployment. Billions have been lost in Web3 due to bugs and inefficiencies: In 2022 alone, over $3.8 billion was stolen due to smart contract exploits, many of which stemmed from avoidable issues like reentrancy, integer overflows, or access control failures. Inefficient contract structures lead to unnecessary gas consumption. Optimizing for gas can reduce costs by up to 40%, saving projects millions over time. Upgradeable contract patterns, like UUPS or Transparent Proxies, require strict adherence to storage layout and initialization rules. Mistakes here often go undetected by generic models and can render a contract unupgradeable or vulnerable. A specialized Solidity model is trained on real-world exploits, EIP standards, and libraries like OpenZeppelin to: Generate secure, gas-efficient code by default Recognize and correctly implement complex proxy patterns Map user intent to modular, auditable contract architectures Incorporate battle-tested logic from audited protocols and fuzz-tested edge cases Morpheus goes beyond syntax-it understands the nuances of decentralized infrastructure and deploys code that meets production-grade standards. What applications will this enable Token creation with built-in logic (tax, liquidity, governance) DeFi automations triggered by market conditions Payment contracts between agents and contributors DAO tooling with dynamic NFT-based voting Cross-chain bridging logic tied to real-world oracles Asset issuance flows through chat-based interfaces Natural language contract templates with reusable logic Each of these flows is backed by OpenLedger’s Proof of Attribution-ensuring traceability, explainability, and fair rewards across the ecosystem. This is the future of AI-native development. Open. Attributed. Explainable. Community-powered. Morpheus and OpenLedger are building the first system for autonomous coding agents where: Contributor work is recorded onchain Reuse is incentivized through attribution Model outputs are traceable and explainable Contracts evolve through human-agent collaboration Anyone can contribute prompts, logic, or flows-and get rewarded The smart contract engineer is no longer a human-only role. It is an agentic, decentralized, and transparent process-powered by OpenLedger.

OpenLedger

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Introducing Insights Hub—the transparent dashboard that brings DeFi's price data into the light. Builders and traders can now tap into clear, real-time, verifiable insights. No more guessing ⬇️

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Datanet contribution is now live for first wave of whitelisted users. You can now add data into existing Datanets, making datasets stronger and improving the models built on them. Each contribution helps AI become smarter and more accurate. This initially begins with whitelisted users in stages, expanding further in the next rollout. To get whitelisted:

Datanet contribution is now live for first wave of whitelisted users. You can now add data into existing Datanets, making datasets stronger and improving the models built on them. Each contribution helps AI become smarter and more accurate. This initially begins with whitelisted users in stages, expanding further in the next rollout. To get whitelisted:

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AI can deliver real value in healthcare only if it is trusted. In this talk, Dr. Kim Wager of Oxford PharmaGenesis explains why medical AI must rely on connected, verifiable knowledge – making healthcare AI more transparent & accountable. 🧬 01:22 – Fixing medical data foundations 05:29 – Trust gap in medical AI 11:33 – Why verifiable knowledge matters 14:03 – Neuro-symbolic AI explained 17:01 – Live demo: OriginTrail DKG enabling full data provenance

AI can deliver real value in healthcare only if it is trusted. In this talk, Dr. Kim Wager of Oxford PharmaGenesis explains why medical AI must rely on connected, verifiable knowledge – making healthcare AI more transparent & accountable. 🧬 01:22 – Fixing medical data foundations 05:29 – Trust gap in medical AI 11:33 – Why verifiable knowledge matters 14:03 – Neuro-symbolic AI explained 17:01 – Live demo: OriginTrail DKG enabling full data provenance

OriginTrail

14,974 views • 5 months ago

Explainability is a core principle of OpenLedger. It answers two key questions in AI: 1. Who should get rewarded? 2. Why is it failing-bias, drift, or poisoning? If AI can explain why it made a decision & what data influenced it, the entire system becomes more fair, traceable, and resilient.

Explainability is a core principle of OpenLedger. It answers two key questions in AI: 1. Who should get rewarded? 2. Why is it failing-bias, drift, or poisoning? If AI can explain why it made a decision & what data influenced it, the entire system becomes more fair, traceable, and resilient.

OpenLedger

17,643 views • 1 year ago

Episode 8 - OpenLedger Openledger with Ram Ram An amazing interview hosted by Jack D, this time with Ram Core Contributor at Openledger, huge moves are being made, it is a must watch episode! Enjoy! Youtube: Summary: In this episode of DEGN Talk, host Jack Degen Jack D interviews Ram Kumar Ram, a core contributor at Openledger, discussing the innovative blockchain platform designed for data contribution and AI model development. Ram explains the current focus on testing the product in its Testnet phase, the importance of specialized AI models, and the introduction of the OpenLedger Model Factory and OpenLoRA to reduce costs and democratize AI model training. The conversation also touches on the current landscape of the crypto market and the role of meme coins. Timecodes: 00:00 Introduction to OpenLedger and Web3 Journey 00:43 Current Focus and Future Roadmap of OpenLedger 03:29 Building Specialized AI Models on OpenLedger 06:10 The Role of Data Contributors and Attribution 08:46 Community Engagement and Upcoming Features 11:35 OpenLedger's Model Factory Explained 14:21 OpenLoRA: Decentralized Compute for AI Models 17:03 Support for Developers and Builders on OpenLedger 20:00 Market Insights and Future of Crypto Important Links: OpenLedger: Openledger Ram Kumar: Ram OpenLedger Website: #chain #web3 #podcast #degn #talk #blockchain #ai #gaming #focg #crypto #openledger #openLoRA

Episode 8 - OpenLedger Openledger with Ram Ram An amazing interview hosted by Jack D, this time with Ram Core Contributor at Openledger, huge moves are being made, it is a must watch episode! Enjoy! Youtube: Summary: In this episode of DEGN Talk, host Jack Degen Jack D interviews Ram Kumar Ram, a core contributor at Openledger, discussing the innovative blockchain platform designed for data contribution and AI model development. Ram explains the current focus on testing the product in its Testnet phase, the importance of specialized AI models, and the introduction of the OpenLedger Model Factory and OpenLoRA to reduce costs and democratize AI model training. The conversation also touches on the current landscape of the crypto market and the role of meme coins. Timecodes: 00:00 Introduction to OpenLedger and Web3 Journey 00:43 Current Focus and Future Roadmap of OpenLedger 03:29 Building Specialized AI Models on OpenLedger 06:10 The Role of Data Contributors and Attribution 08:46 Community Engagement and Upcoming Features 11:35 OpenLedger's Model Factory Explained 14:21 OpenLoRA: Decentralized Compute for AI Models 17:03 Support for Developers and Builders on OpenLedger 20:00 Market Insights and Future of Crypto Important Links: OpenLedger: Openledger Ram Kumar: Ram OpenLedger Website: #chain #web3 #podcast #degn #talk #blockchain #ai #gaming #focg #crypto #openledger #openLoRA

DEGN Talk

29,914 views • 1 year ago

Big AI eats your data, gives nothing back. Ram explains why this extraction model is broken. OpenLedger flips the script. Transparent data. Verifiable contribution. Rewards that flow back to the source. The AI future isn’t privately owned. It’s collaborative 🐙

Big AI eats your data, gives nothing back. Ram explains why this extraction model is broken. OpenLedger flips the script. Transparent data. Verifiable contribution. Rewards that flow back to the source. The AI future isn’t privately owned. It’s collaborative 🐙

OpenLedger

57,853 views • 11 months ago

Introducing the Social Oracle: a system that transforms your fragmented digital identity into a unified asset you control. Achievements, reputation, and influence - verified, private, and valuable. A new foundation for consumer crypto. (((+)))

Introducing the Social Oracle: a system that transforms your fragmented digital identity into a unified asset you control. Achievements, reputation, and influence - verified, private, and valuable. A new foundation for consumer crypto. (((+)))

Sophon

143,032 views • 1 year ago

Hedera’s governance and consensus mechanism enhance data integrity, crucial for accurate decision-making and operational efficiency - making the #Hedera network the reliable data foundation for trusted, sustainable, and responsible #AI. ✨ What AI will you build? #HelloFuture

Hedera’s governance and consensus mechanism enhance data integrity, crucial for accurate decision-making and operational efficiency - making the #Hedera network the reliable data foundation for trusted, sustainable, and responsible #AI. ✨ What AI will you build? #HelloFuture

Hedera

44,176 views • 1 year ago

As the #AI supercycle drives complexity in IP networks, telecommunication providers need trusted AI. Nokia’s new NSP agentic AI enables guided, explainable operations, advancing #connectivity and accelerating the path to autonomous networks. Read more:

As the #AI supercycle drives complexity in IP networks, telecommunication providers need trusted AI. Nokia’s new NSP agentic AI enables guided, explainable operations, advancing #connectivity and accelerating the path to autonomous networks. Read more:

Nokia

10,242 views • 16 days ago

🚀 Introducing the AI Alliance: Shaping the Future of AI and Data Security We’re proud to unveil the AI Alliance, a collaboration of expert teams from ARC, DMAIL.AI and XAlpha AI Agent to name a few, who are working together to drive innovation in AI and data security. By leveraging the power of LLMs (Large Language Models), we’re building the foundation for future AI applications. 🌐✨ 💡 This is just the beginning! Stay tuned for more insights and updates from this recently held AI Alliance AMA. We’ll dive deeper into how these teams are helping to shape the future of AI.

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ARC

20,658 views • 1 year ago