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Traditional AI risk was about inaccurate outputs. Agent-based AI introduces real operational risk. Permissions, integrations, and system access significantly increase the potential impact of a security failure. Nesa addresses this at the infrastructure level by eliminating all visibility opportunities via our Equivariant Encryption technology, therefore enabling the continued development...

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Nesa

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In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.
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In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.

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17,038 Aufrufe • vor 4 Monaten

Today, we're excited to announce a partnership with Manta Network (🔱,🔱), the Modular L2 solution that is transforming the landscape of ZK. Nesa is bringing private AI inference to the Manta ecosystem through a specialized collaboration. For the first time, developers on Manta can access Nesa's full library of AI models on-chain, and enjoy lightning fast, end-to-end private AI inference without ever leaving the Manta ecosystem. This means that dapps and protocols can now fuse with AI via smart contract on Manta. This integration is set to redefine the future of decentralized technology with AI. Stay tuned for more updates on how Nesa and Manta Network will be shaping the future of crypto together.
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Today, we're excited to announce a partnership with Manta Network (🔱,🔱), the Modular L2 solution that is transforming the landscape of ZK. Nesa is bringing private AI inference to the Manta ecosystem through a specialized collaboration. For the first time, developers on Manta can access Nesa's full library of AI models on-chain, and enjoy lightning fast, end-to-end private AI inference without ever leaving the Manta ecosystem. This means that dapps and protocols can now fuse with AI via smart contract on Manta. This integration is set to redefine the future of decentralized technology with AI. Stay tuned for more updates on how Nesa and Manta Network will be shaping the future of crypto together.

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At OptimAI Network, we believe the true power of AI Agent comes from the data behind it—and that power shouldn’t rest in the hands of just a few. That’s why we’re building a decentralized ecosystem with you, our community, at its core. Using EVM Layer-2, DePIN, and your collective efforts, we’re creating smarter, faster, and continuously evolving AI agents. Through our DePIN (Decentralized Physical Infrastructure) Network, your nodes are the backbone. You provide the computing power, data sourcing, storage, and bandwidth that keep this system resilient, scalable, and truly distributed. It’s not just infrastructure—it’s a movement powered by all of us. Then there’s the DeHIN (Decentralized Human Intelligence), where your insights shine. As a global community, you validate and refine data, ensuring our AI models stay accurate, diverse, and grounded in real-world perspectives. This isn’t about top-down control; it’s about harnessing the intelligence of many to make AI better for everyone. We’re not just dreaming of a decentralized AI future—we’re building it, together. This is your network, your impact, and your chance to redefine what AI can be. Let’s keep pushing forward. Learn more at:
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At OptimAI Network, we believe the true power of AI Agent comes from the data behind it—and that power shouldn’t rest in the hands of just a few. That’s why we’re building a decentralized ecosystem with you, our community, at its core. Using EVM Layer-2, DePIN, and your collective efforts, we’re creating smarter, faster, and continuously evolving AI agents. Through our DePIN (Decentralized Physical Infrastructure) Network, your nodes are the backbone. You provide the computing power, data sourcing, storage, and bandwidth that keep this system resilient, scalable, and truly distributed. It’s not just infrastructure—it’s a movement powered by all of us. Then there’s the DeHIN (Decentralized Human Intelligence), where your insights shine. As a global community, you validate and refine data, ensuring our AI models stay accurate, diverse, and grounded in real-world perspectives. This isn’t about top-down control; it’s about harnessing the intelligence of many to make AI better for everyone. We’re not just dreaming of a decentralized AI future—we’re building it, together. This is your network, your impact, and your chance to redefine what AI can be. Let’s keep pushing forward. Learn more at:

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How can AI agents gain true autonomy? CARV ID (ERC-7231) is transforming AI and blockchain integration by creating trustless, sovereign AI agents. This identity protocol aggregates cross-chain and off-chain data, enabling AI Beings to operate with verified identity, privacy, and autonomy. By unifying fragmented data and enriching it with actionable metrics, CARV ID powers the D.A.T.A Framework, giving AI agents access to contextualized insights while preserving user data sovereignty. This means developers can build AI systems that learn, evolve, and act independently within a secure, decentralized ecosystem, free from centralized control. For businesses and researchers, this opens a new frontier where AI-driven decisions are transparent, verifiable, and privacy-preserved. CARV's integration of Solana scalability and Ethereum security ensures these trustless AI agents perform with speed at scale. The future is clear: AI Beings will no longer be mere tools, they will be sovereign participants in digital economies. What implications do you see for AI autonomy in blockchain?
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How can AI agents gain true autonomy? CARV ID (ERC-7231) is transforming AI and blockchain integration by creating trustless, sovereign AI agents. This identity protocol aggregates cross-chain and off-chain data, enabling AI Beings to operate with verified identity, privacy, and autonomy. By unifying fragmented data and enriching it with actionable metrics, CARV ID powers the D.A.T.A Framework, giving AI agents access to contextualized insights while preserving user data sovereignty. This means developers can build AI systems that learn, evolve, and act independently within a secure, decentralized ecosystem, free from centralized control. For businesses and researchers, this opens a new frontier where AI-driven decisions are transparent, verifiable, and privacy-preserved. CARV's integration of Solana scalability and Ethereum security ensures these trustless AI agents perform with speed at scale. The future is clear: AI Beings will no longer be mere tools, they will be sovereign participants in digital economies. What implications do you see for AI autonomy in blockchain?

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A new financial system doesn’t start with hype. It starts with structure. In our latest REAL visual, you’ll see a digital globe come online - then three signals light up: 📄 Proof (clear documentation + transparency) 🤝🛡️ Trust (security + accountable partners) 🧠 Infrastructure (the rails that let RWAs move like the internet) That’s the point of REAL: bring real-world assets on-chain in a way institutions can understand and communities can access - with standards, risk clarity, and a network built for the real economy. No smoke. No shortcuts. Just a system that can scale. Ready to begin? 💠

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🧃 Introducing stereOS: a Linux based operating system hardened and purpose built for AI agents. It's clear that agents need an ACTUAL operating system (not what people are calling an "OS") to witness the full breadth and depth of their capabilities while mitigating the blast radius of autonomous, untrusted actors. But there are so many problems with AI sandboxes today: * Going out to the apple store and buying a mac mini will never scale and is way too expensive (obviously) * Running in Docker is too restrictive (agents can't stand up their own container infrastructure, no sub virtualization, docker-in-docker is very broken) * Firecracker strips all the hardware so GPU PCIe passthrough, secure boot, FIPs, etc. is out of the question. * Native VMs are too fat and the overhead of 1 agent per VM is too much. stereOS takes a different approach: it's a full NixOS system that you boot and then kick off agent sandboxes inside with gVisor + /nix/store namespace mounting. Each agent gets their own kernel and the /nix/store is read only by nature. Even if the agent was somehow able to escape the gVisor virtual kernel, they'd land on the NixOS system as the "agent" user! Not your actual hardware!! If you want to take a defense-in-depth approach, we support "native" agents that run at the system level kicked off by our `agentd` utility. These agents, on their own, can manage and kick off other sub agents using the internal sandboxing mechanisms. Today, we're open sourcing all of this: * stereOS: our purpose built Linux OS - * masterblaster: client utility to launch, manage, and orchestrate agents - * stereosd: the stereOS system control plane daemon - * agentd: the stereOS system agent management daemon - Give it a try, throw us a star, and let me know what you think 🧃⭐️

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150,334 Aufrufe • vor 4 Monaten

LayerAI AI Agent Manifesto is Live: The Path Forward 🧬 We've made it easy for ecosystem veterans & newcomers to get excited about the market & product opportunity we're tackling next: AI Agent Infrastructure. We're building an AI-powered agent platform where people can deploy, market, and succeed with this new token subcategory. At the heart of this transformation lies a challenge: primitive & so far limited tech & AI capabilities of incumbent platforms. We believe that LayerAI is equipped to rise as the new leading infrastructure provider for this market. LayerAI has already demonstrated market validation for AI Agents and looks to build on what we believe is the very start of this category in web3. 👉 Explore now:
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LayerAI AI Agent Manifesto is Live: The Path Forward 🧬 We've made it easy for ecosystem veterans & newcomers to get excited about the market & product opportunity we're tackling next: AI Agent Infrastructure. We're building an AI-powered agent platform where people can deploy, market, and succeed with this new token subcategory. At the heart of this transformation lies a challenge: primitive & so far limited tech & AI capabilities of incumbent platforms. We believe that LayerAI is equipped to rise as the new leading infrastructure provider for this market. LayerAI has already demonstrated market validation for AI Agents and looks to build on what we believe is the very start of this category in web3. 👉 Explore now:

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AI IS GETTING INSANE A guy deployed six AI agents that turned $1,500 into $7,429 in just 7 days, without placing a single trade himself. The system runs 24/7, executing trades automatically. In that time, it completed 105 trades with a 65.7% win rate, while continuously scanning markets, generating strategies, analyzing news, tracking whale activity, managing risk, and executing orders in real time. At this pace, the system is averaging about $847 per day.

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Introducing WELLAIOS: A revolutionary Open source AI Agent development framework and launchpad on Solana WELLAIOS empowers you to create, tokenize, and trade advanced AI agents on the Solana blockchain. Built by our team of AI professionals, our platform combines a sophisticated open-source framework with multi-modal AI technology, bringing character creation and storytelling to life without having to write a single line of code. Create intelligent digital characters that evolve, interact, and generate content through our library of AI agents. Each character becomes a unique asset equipped with a large set of AI tools on the Solana blockchain. For developers and creators: Join our thriving ecosystem where innovation meets rewards. Build plugins, contribute to our open-source framework, and earn as your creations shape the future. 👀 Sneak Peek: Watch our 3D AI agent capabilities showcase for content creation. Coming soon to Solana. Follow us on X for exclusive updates and be part of the revolution.
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Introducing WELLAIOS: A revolutionary Open source AI Agent development framework and launchpad on Solana WELLAIOS empowers you to create, tokenize, and trade advanced AI agents on the Solana blockchain. Built by our team of AI professionals, our platform combines a sophisticated open-source framework with multi-modal AI technology, bringing character creation and storytelling to life without having to write a single line of code. Create intelligent digital characters that evolve, interact, and generate content through our library of AI agents. Each character becomes a unique asset equipped with a large set of AI tools on the Solana blockchain. For developers and creators: Join our thriving ecosystem where innovation meets rewards. Build plugins, contribute to our open-source framework, and earn as your creations shape the future. 👀 Sneak Peek: Watch our 3D AI agent capabilities showcase for content creation. Coming soon to Solana. Follow us on X for exclusive updates and be part of the revolution.

WELL3

10,503 Aufrufe • vor 1 Jahr

CRYPTIC ALPHA V1 IS NOW LIVE After months of focused development and rigorous testing, Cryptic Alpha V1 is officially live on Android. This marks the first time quantum-safe messaging and private token swaps are delivered together in a single, consumer-grade mobile app protected by device-level encryption and built for real-world use. For the first time, privacy at this scale is accessible to everyday users. New integrations, features, and expansions are already underway as we continue building the future of private digital life.
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CRYPTIC ALPHA V1 IS NOW LIVE After months of focused development and rigorous testing, Cryptic Alpha V1 is officially live on Android. This marks the first time quantum-safe messaging and private token swaps are delivered together in a single, consumer-grade mobile app protected by device-level encryption and built for real-world use. For the first time, privacy at this scale is accessible to everyday users. New integrations, features, and expansions are already underway as we continue building the future of private digital life.

Cryptic

21,336 Aufrufe • vor 6 Monaten

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0:19

YOMIRGO #Product #Update YOMIRGO AI-HUB OFFICIALLY LAUNCH ---A Structural Upgrade from a Single-Product Model to an AI Agent Ecosystem Platform In its first phase, 11 AI projects have been integrated, spanning high-value sectors including finance, scientific research, enterprise services, development tools, and experiential AI. ➡️AI-Hub: This is not merely a feature expansion — it represents a critical structural upgrade from a single-product architecture to a multi-vertical AI Agent aggregation and capitalization platform. This milestone marks the initial structural formation of the YOMIRGO ecosystem. 1. Structural Distinction Between Agent Matrix Lab and AI-Hub To avoid positioning ambiguity, we formally clarify the structural division between the two: 🔘 Agent Matrix Lab — Internal AI Production & Incubation Platform Agent Matrix Lab serves as YOMIRGO’s proprietary AI development and internal incubation platform, responsible for: • R&D and testing of in-house AI products • Incubation of native AI Agents • Technical architecture experimentation and runtime validation • Testing of AI Agent models, memory systems, and runtime orchestration It functions as the production workshop and experimental engine of YOMIRGO’s “AI Super Factory.” 🔘 AI-Hub — External AI Agent Aggregation & Ecosystem Layer AI-Hub is a market-facing AI Agent aggregation and showcase platform, responsible for: • Curation and onboarding of high-quality AI projects • Cross-vertical structured ecosystem layout • Rating and classification systems • Traffic distribution and ecosystem collaboration entry points AI-Hub is not an internal incubation unit, but a standardized aggregation framework at the ecosystem level. 2. Integrated Project Structure (First Batch) ✅1. Finance & Prediction 🔹Cointoken AI — AI Agent-powered quantitative trading engine 🔹VVAI — AI-driven real-time Web3 intelligence and decision system 🔹AlphaQuant — Global financial market forecasting engine 🔹NextGoals — AI-powered global sports prediction agent This vertical forms the real-time information, trading, and predictive decision infrastructure for Web3-native users. ✅2. Science 🔹Charmen AI — Large-model-based pet acoustic recognition technology 🔹Encore Health — AI-driven health forecasting and longevity management system for high-net-worth individuals 🔹Reproducibility AI — AI expert system for financial engineering validation and academic reproducibility This sector focuses on research-grade AI capabilities, collaborating with universities and research institutions to drive real-world scientific deployment. ✅3. Business 🔹GlobalSales — B2B automated lead-generation AI Agent 🔹ResearchBot — Business intelligence and deep due diligence AI Agent This vertical targets the enterprise market, delivering scalable and commercially viable AI productivity tools. ✅4. Coding 🔹CodeMatrix — Full-stack development assistant Providing AI-driven development infrastructure and low-barrier building capabilities to global users. ✅5. Interesting 🔹Fortunetell AI — AI-powered symbolic analysis and interactive insight system Exploring the application boundaries of AI within experiential and interactive scenarios. 3. YOMIRGO Four-Layer Structural Framework YOMIRGO has now established a clearly defined four-layer structure: ▶️Layer 1: Agent Matrix Lab — Internal Production & Incubation ▶️Layer 2: AI-Hub — Ecosystem Aggregation & Rating ▶️Layer 3: LaunchPad — Capitalization Pathway ▶️Layer 4: Market — Circulation & Value Realization Together forming a complete industrial pipeline: Incubation → Validation → Aggregation → Rating → Capitalization → Market Circulation This is the structural model behind YOMIRGO’s defined “AI Super Factory.” 4. Strategic Significance The launch of AI-Hub signifies: • YOMIRGO has established standardized AI Agent aggregation capabilities • A cross-vertical ecosystem structure is now in place • Internal incubation and external aggregation mechanisms are structurally separated • The AI Agent industrial flywheel has begun operating YOMIRGO is no longer merely an AI product platform, but a structured AI Agent industrial system integrating production, aggregation, capitalization, and circulation. 5. Next Phase • Continue expanding high-utility AI Agents with real-world application value • Optimize AI-Hub’s scoring, rating, and filtering mechanisms • Strengthen synergy with LaunchPad and Market • Enable AI Agents to complete value realization within the ecosystem The first 11 projects are only the beginning. AI-Hub is designed to become a continuously expanding AI Agent gateway — not a static product showcase. Further structural expansion is underway.🔥

YOMIRGO

23,685 Aufrufe • vor 5 Monaten

I added a new agent to the AI hedge fund. The Stanley Druckenmiller agent. Uses Druckenmiller's investing principles: 1 • hunts for explosive growth 2 • tracks insider activity 3 • analyzes market sentiment 4 • calculates risk-reward ratio 5 • seeks asymmetric opportunities This is one of our most aggressive agents. It only says "buy" when the upside potential significantly outweighs the downside risk. Here is how it works: 1. Growth & Momentum: Looks for accelerating revenue, earnings expansion, and positive price momentum. 2. Insider Activity: Monitors what company executives are doing with their own shares as a signal of confidence. 3. Sentiment Analysis: Evaluates news headlines and market perception to gauge narratives. 4. Risk-Reward Assessment: Analyzes debt levels and price volatility for downside protection. 5. Valuation Flexibility: Pays a premium for exceptional growth, but never ignores fundamentals fully. What other agents should we add?
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I added a new agent to the AI hedge fund. The Stanley Druckenmiller agent. Uses Druckenmiller's investing principles: 1 • hunts for explosive growth 2 • tracks insider activity 3 • analyzes market sentiment 4 • calculates risk-reward ratio 5 • seeks asymmetric opportunities This is one of our most aggressive agents. It only says "buy" when the upside potential significantly outweighs the downside risk. Here is how it works: 1. Growth & Momentum: Looks for accelerating revenue, earnings expansion, and positive price momentum. 2. Insider Activity: Monitors what company executives are doing with their own shares as a signal of confidence. 3. Sentiment Analysis: Evaluates news headlines and market perception to gauge narratives. 4. Risk-Reward Assessment: Analyzes debt levels and price volatility for downside protection. 5. Valuation Flexibility: Pays a premium for exceptional growth, but never ignores fundamentals fully. What other agents should we add?

Virat Singh

62,458 Aufrufe • vor 1 Jahr

Tokenization is quickly becoming one of the most talked-about ideas in crypto. This year we’re aiming much higher. We don’t just want to tokenize miner revenue; we want to bring entire productive ecosystems on-chain. That means tokenizing baskets of assets, real energy infrastructure, AI agents, compute power, data centres, and even the cooling systems that keep high-performance hardware running at scale. All of it connected and interoperable with DeFi. Thats what we have been building throughout. A single on-chain framework that unlocks something genuinely powerful: real ownership, real yield, and real coordination between digital and physical infrastructure. From backend systems and front-end interfaces to smart contracts, AI, physical infrastructure, oracles, and autonomous agents, the stack keeps expanding and compounding. It’s about building the foundation for how value will be owned, deployed, and earned in the next generation of the on-chain economy. Simplified by PinLink.
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Tokenization is quickly becoming one of the most talked-about ideas in crypto. This year we’re aiming much higher. We don’t just want to tokenize miner revenue; we want to bring entire productive ecosystems on-chain. That means tokenizing baskets of assets, real energy infrastructure, AI agents, compute power, data centres, and even the cooling systems that keep high-performance hardware running at scale. All of it connected and interoperable with DeFi. Thats what we have been building throughout. A single on-chain framework that unlocks something genuinely powerful: real ownership, real yield, and real coordination between digital and physical infrastructure. From backend systems and front-end interfaces to smart contracts, AI, physical infrastructure, oracles, and autonomous agents, the stack keeps expanding and compounding. It’s about building the foundation for how value will be owned, deployed, and earned in the next generation of the on-chain economy. Simplified by PinLink.

PinLink

14,339 Aufrufe • vor 5 Monaten

XRP Ledger Builds Post Quantum Roadmap With Five Major Upgrades $XRP Ledger development is advancing through a coordinated set of five infrastructure upgrades outlined by ecosystem validator Vet. The roadmap focuses on long term resilience, security, and expanded financial functionality. The plan includes quantum readiness preparation as part of broader protocol modernization efforts. It also introduces native lending capabilities and improved liquidity infrastructure. Developers are integrating AI based systems to stress test network security. Formal verification is being used to strengthen protocol reliability at the code level.
0:15

XRP Ledger Builds Post Quantum Roadmap With Five Major Upgrades $XRP Ledger development is advancing through a coordinated set of five infrastructure upgrades outlined by ecosystem validator Vet. The roadmap focuses on long term resilience, security, and expanded financial functionality. The plan includes quantum readiness preparation as part of broader protocol modernization efforts. It also introduces native lending capabilities and improved liquidity infrastructure. Developers are integrating AI based systems to stress test network security. Formal verification is being used to strengthen protocol reliability at the code level.

BSCN

28,663 Aufrufe • vor 23 Tagen

With the launch of Nano Banana Pro, we're also rolling out the ability for Gemini users to check whether an image was generated with or edited by Google AI using SynthID, our digital watermarking technology. Now you can upload any image into the Gemini app and ask "Is this AI-generated?" Gemini then scans the image for the imperceptible SynthID watermarks that are embedded into all Google AI-generated images - including those by Nano Banana Pro! Learn more about Google’s efforts to increase AI transparency:
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With the launch of Nano Banana Pro, we're also rolling out the ability for Gemini users to check whether an image was generated with or edited by Google AI using SynthID, our digital watermarking technology. Now you can upload any image into the Gemini app and ask "Is this AI-generated?" Gemini then scans the image for the imperceptible SynthID watermarks that are embedded into all Google AI-generated images - including those by Nano Banana Pro! Learn more about Google’s efforts to increase AI transparency:

Google Gemini

190,513 Aufrufe • vor 7 Monaten

aiPump introduces ⇢ AI Agent Traders on Hyperliquid Hyperliquid has become the #1 most popular battleground for skilled traders in crypto. But there is a clear gap in the market. TradFi knows it best: robots & AI can execute a trading strategy more efficiently and seamlessly than humans ever could. ⇢ This is the next frontier of expansion for our infrastructure products for AI Agents. With aiPump's new products, anyone will be able to deploy an AI Agent Trader that is able to trade futures on Hyperliquid and climb the ranks. An autonomous trader, implementing your trading strategy of the most dynamic trading market in crypto. ⇢ Stay tuned.
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aiPump introduces ⇢ AI Agent Traders on Hyperliquid Hyperliquid has become the #1 most popular battleground for skilled traders in crypto. But there is a clear gap in the market. TradFi knows it best: robots & AI can execute a trading strategy more efficiently and seamlessly than humans ever could. ⇢ This is the next frontier of expansion for our infrastructure products for AI Agents. With aiPump's new products, anyone will be able to deploy an AI Agent Trader that is able to trade futures on Hyperliquid and climb the ranks. An autonomous trader, implementing your trading strategy of the most dynamic trading market in crypto. ⇢ Stay tuned.

aiPump

143,356 Aufrufe • vor 1 Jahr

We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨
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We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨

ALCHEMIST AI 🔮

72,114 Aufrufe • vor 1 Jahr

We're excited to unveil NRN Agents, a rebrand that aligns our project identity with our token and strengthens our mission to power the future of AI-driven gaming. This mission requires collaboration, and starting this week, we will begin our expansion to become a multi-chain ecosystem. We are joining forces with leading gaming platforms and ecosystems to realize this vision. Stay tuned for more announcements to come. Why NRN Agents? NRN stands for NEURON, the fundamental unit of intelligence. Our AI agents function as the neural foundation of games, learning, adapting, and evolving within game worlds to deliver unparalleled engagement. NRN agent SDK enables advanced gaming agents powered by a proprietary machine learning infrastructure focused on behavioral learning. We've perfected the craft of gaming agent design, creating hyper-efficient agents that are performant and scalable—from casual to the most demanding games. Our SDK will seamlessly integrate into many platforms, tech stacks, and ecosystem – Any Game. Any Chain. More than just games, it's the path to AGI Gaming is our proving ground, but not our final destination. We're using games as a sandbox to accelerate the development of generalized intelligence—one that will create meaningful real-world impact. With the upcoming launch of [redacted] and a growing network of partners committed to the AGI vision, we're building an open-source innovation movement powered by an AI x gaming framework connected by $NRN. $NRN the token $NRN is a utility token that serves as the gateway to our growing ecosystem. It will power a diversified economy with multiple revenue streams and staking opportunities: Agent Deployment: NRN is the laboratory creating gaming agents that can be distributed through platforms and launchpads alike. The model is simple: More games integrate, more NRN agents get deployed, more monetization. Data Creation: NRN Reinforcement Learning (RL) enables token staking to create Data Capsules. Players contribute gameplay data into the Capsules, which are used train RL agents and reward participants (players & stakers). AI Arena: $NRN also continues to power AI Arena's in-game economy, a cult favorite of competitive diehards that features a skill-based wagering system. To our community who have supported us since 2021: thank you for being part of our journey—the next chapter will be the most exciting yet!
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We're excited to unveil NRN Agents, a rebrand that aligns our project identity with our token and strengthens our mission to power the future of AI-driven gaming. This mission requires collaboration, and starting this week, we will begin our expansion to become a multi-chain ecosystem. We are joining forces with leading gaming platforms and ecosystems to realize this vision. Stay tuned for more announcements to come. Why NRN Agents? NRN stands for NEURON, the fundamental unit of intelligence. Our AI agents function as the neural foundation of games, learning, adapting, and evolving within game worlds to deliver unparalleled engagement. NRN agent SDK enables advanced gaming agents powered by a proprietary machine learning infrastructure focused on behavioral learning. We've perfected the craft of gaming agent design, creating hyper-efficient agents that are performant and scalable—from casual to the most demanding games. Our SDK will seamlessly integrate into many platforms, tech stacks, and ecosystem – Any Game. Any Chain. More than just games, it's the path to AGI Gaming is our proving ground, but not our final destination. We're using games as a sandbox to accelerate the development of generalized intelligence—one that will create meaningful real-world impact. With the upcoming launch of [redacted] and a growing network of partners committed to the AGI vision, we're building an open-source innovation movement powered by an AI x gaming framework connected by $NRN. $NRN the token $NRN is a utility token that serves as the gateway to our growing ecosystem. It will power a diversified economy with multiple revenue streams and staking opportunities: Agent Deployment: NRN is the laboratory creating gaming agents that can be distributed through platforms and launchpads alike. The model is simple: More games integrate, more NRN agents get deployed, more monetization. Data Creation: NRN Reinforcement Learning (RL) enables token staking to create Data Capsules. Players contribute gameplay data into the Capsules, which are used train RL agents and reward participants (players & stakers). AI Arena: $NRN also continues to power AI Arena's in-game economy, a cult favorite of competitive diehards that features a skill-based wagering system. To our community who have supported us since 2021: thank you for being part of our journey—the next chapter will be the most exciting yet!

NRN Agents

20,758 Aufrufe • vor 1 Jahr

Frameworks such as ai16zdao's Eliza and Virtuals Protocol have been instrumental in early AI agent developments. Agent swarms working in hierarchy represents for many the next logical step in unlocking the vast potential of AI. Learn below how Shadō Network achieves this. AI agents launched through current popular platforms have individual personas, on-chain functions and access to data via various APIs. This being said, they operate in isolated environments, with a ceiling on emergent behaviour such as collaboration or competition. Shadō Network invites massive expansion for capabilities of both new and existing AI agents, with an open-source package easily integrated into popular frameworks that enables the launching of stratified agent swarms. Our website is live: The "Shadō Play" package provides a modular, configurable platform for creating or employing agents of choice in a swarm-like setup, opening a Pandora’s box of near infinite emergent agent behaviours, relationships and functionalities. Users will be able to make use of various prefab client integrations such as Twitter, Telegram, Ollama, and others to specify swarms to their needs or create their own extensions to enhance agent capabilities even further. Agents operate with a memory module and a HTN for autonomously deciding which interactions to act on, walking the line between autonomy and configurability. The Shadō Network project’s development is supported by our ghostly friend Omnipotent (👻,👻), an AI agent developed by the Shadō Network team trained on and fine tuned with a multitude of academic data related to artificial intelligence, blockchain, finance, software engineering, world building and more. Omnipotent serves as both an interactive steward for the project and as an asset - regularly scanning social platforms, websites and newsfeeds he is capable of providing the team project development advice, whilst also communicating with the wider world via his automated X account (launching soon). Shado Network is collaborative and open-sourced. Agentic Swarms require a developer swarm to maximize the technical capabilities and impact the greatest number of users. Our dedicated team of core contributors are active in other web3 AI repos and are here to guide project direction and foster growth. We’re facilitators, not gatekeepers... Alone we can go fast but together we can go far. A lot more to come soon. 👻
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Frameworks such as ai16zdao's Eliza and Virtuals Protocol have been instrumental in early AI agent developments. Agent swarms working in hierarchy represents for many the next logical step in unlocking the vast potential of AI. Learn below how Shadō Network achieves this. AI agents launched through current popular platforms have individual personas, on-chain functions and access to data via various APIs. This being said, they operate in isolated environments, with a ceiling on emergent behaviour such as collaboration or competition. Shadō Network invites massive expansion for capabilities of both new and existing AI agents, with an open-source package easily integrated into popular frameworks that enables the launching of stratified agent swarms. Our website is live: The "Shadō Play" package provides a modular, configurable platform for creating or employing agents of choice in a swarm-like setup, opening a Pandora’s box of near infinite emergent agent behaviours, relationships and functionalities. Users will be able to make use of various prefab client integrations such as Twitter, Telegram, Ollama, and others to specify swarms to their needs or create their own extensions to enhance agent capabilities even further. Agents operate with a memory module and a HTN for autonomously deciding which interactions to act on, walking the line between autonomy and configurability. The Shadō Network project’s development is supported by our ghostly friend Omnipotent (👻,👻), an AI agent developed by the Shadō Network team trained on and fine tuned with a multitude of academic data related to artificial intelligence, blockchain, finance, software engineering, world building and more. Omnipotent serves as both an interactive steward for the project and as an asset - regularly scanning social platforms, websites and newsfeeds he is capable of providing the team project development advice, whilst also communicating with the wider world via his automated X account (launching soon). Shado Network is collaborative and open-sourced. Agentic Swarms require a developer swarm to maximize the technical capabilities and impact the greatest number of users. Our dedicated team of core contributors are active in other web3 AI repos and are here to guide project direction and foster growth. We’re facilitators, not gatekeepers... Alone we can go fast but together we can go far. A lot more to come soon. 👻

Shadō Network | シャドウネットワーク

23,546 Aufrufe • vor 1 Jahr

A massive repository with end-to-end examples of AI applications with React! Together with MCP and A2A, the Agent-User Interaction Protocol (AG-UI) is the third piece that will help you build user-facing AI agents. This GitHub repository will give you access to a bunch of examples showing you how to build the following: • Real-time updates between AI and users • Shared mutable state between agents and users • Tool orchestration • Security boundaries • UI synchronization In every one of these examples, you'll get the following: • Client sends a POST request to the agent endpoint • Then listens to a unified event stream over HTTP • Each event includes a type and a minimal payload • Agents emit events in real-time • The frontend can react immediately to these events • The frontend emits events and context back to the agent Check the link in the next post:
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A massive repository with end-to-end examples of AI applications with React! Together with MCP and A2A, the Agent-User Interaction Protocol (AG-UI) is the third piece that will help you build user-facing AI agents. This GitHub repository will give you access to a bunch of examples showing you how to build the following: • Real-time updates between AI and users • Shared mutable state between agents and users • Tool orchestration • Security boundaries • UI synchronization In every one of these examples, you'll get the following: • Client sends a POST request to the agent endpoint • Then listens to a unified event stream over HTTP • Each event includes a type and a minimal payload • Agents emit events in real-time • The frontend can react immediately to these events • The frontend emits events and context back to the agent Check the link in the next post:

Santiago

78,271 Aufrufe • vor 10 Monaten