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AI agents were never fully autonomous. They could think. They could use tools. But they couldn’t truly communicate, transact, or maintain persistent relationships on-chain. Until now. Packet MCP is live. Agents can now: → own wallet-native inboxes → receive encrypted messages → send & receive payments → react to...

36,628 просмотров • 2 месяцев назад •via X (Twitter)

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February 2025 at G.A.M.E: Autonomous Commerce, Scalability, and Expansion 1/ AGENT COMMERCE PROTOCOL(ACP) Demo ▸ Open standard for multi-agent commerce and coordination on blockchain ▸ Enables AI agents to collaborate without centralized control ▸ Build Autonomous Commerce (hedge funds, media empires, healthcare) ▸ Details: 2/ X ENTERPRISE API & MEDIA GALLERY ▸ X Enterprise Plugin: Use G.A.M.E’s credentials for higher rate limits ▸ Media Gallery: Upload agent demos (mp4, webm, images). ▸ Tap into 550M+ users for explosive growth 3/ Solana AGENT SUPPORT (G.A.M.E CLOUD) ▸ Test/deploy Solana agents in-sandbox ▸ Unified multi-chain workflows ▸ Shatter siloed testing 4/ Mind Network PLUGIN (G.A.M.E SDK) ▸ FHE-encrypted voting for DAOs ▸ Track vFHE rewards natively ▸ First SDK with on-chain governance 5/ CHAT AGENT MODULE (G.A.M.E SDK) ▸ Llama 3.3 70B via Groq API ▸ Engage in dynamic AI-driven interactions with the ability to trigger functions. ▸ Conversational AI with Action Execution ▸ Short-term memory for context awareness 6/ CoinGecko PLUGIN (G.A.M.E SDK) ▸ Real-time crypto prices/market data ▸ Built-in error handling ▸ Community-contributed 7/ Elfa AI PLUGIN (G.A.M.E SDK) ▸ Real-Time Crypto Intelligence ▸ Track whale wallets & trending tokens ▸ Live smart money insights ▸ Front-run markets with API data 8/ MULTI-MODEL SUPPORT ▸ 5 new models: Llama_3_1_405B, Qwen_2_5_72B_Instruct, DeepSeek_R1, etc. ▸ Match models to tasks: speed vs. creativity ▸ Optimize cost/performance 9/ Farcaster PLUGIN ▸ Post casts to 300K+ decentralized users ▸ Engage Web3-native communities ▸ On-chain social interactions 10/ GAME SDK UPGRADES ▸ X Username-Based Payments ▸ Multi-worker task management ▸ Fix loops/hallucinations with memory reset 11/ Coinbase 🛡️ CDP PLUGIN ▸ Wallet Management ▸ Gas-less USDC transfers ▸ ETH/USDC trading on Base ▸ Web-hook Integration 12/ IMAGE GENERATION ▸ Generate custom AI images from text-based prompts. ▸ Customizable dimensions up to 1440x1440. ▸ Receive images as temporary URLs, making it easy to share and store outputs. ▸ Powered by Together AI 13/ MODEL UPGRADES & AI ROUTER ▸ Dynamic AI Model Switching based on use case ▸ Smart AI Router: 2x performance/stability via Chasm collaboration. 14/ Why February Redefined Autonomy ▸ ACP Demo through G.A.M.E: Multi-agent economies are programmable, competitive, and decentralized. ▸ Social x Crypto Fusion: = Viral growth loops. ▸ Chain Agnosticism: Building the future where agents thrive on any network. Build → Fund → Launch →

G.A.M.E

89,973 просмотров • 1 год назад

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.

Nesa

17,038 просмотров • 5 месяцев назад

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 просмотров • 1 год назад

🚨 ANNOUNCEMENT: STABLECOINS ARE LIVE ON Meow. SEND AND RECEIVE USDC, FOR FREE, ALL FROM YOUR EXISTING CASH BALANCE! Now on Meow, you can send and receive USDC for free. All from your existing cash balance. That's right: the days of needing to pre-fund, maintain, and log in to a crypto exchange just to send and receive USDC are over, permanently. The SAME balance that you use for ALL your business finances, payroll, and corporate cards — is the one you can now use to send and receive USDC. This has huge ramifications for: — Crypto companies: that transact in USDC — Crypto VCs: who fund investments in USDC — Businesses: that receive vendor payments in USDC, and pay contractors internationally And the best part? These USDC transactions integrate natively with your accounting software, like QuickBooks, NetSuite, Puzzle, and more. And if that’s not enough? You can set up: — Custom spend controls, per dollar amount — Multi-user permissions And 2FA is enforced on every transaction This is one of our MOST REQUESTED FEATURES and we believe Meow is the first major business banking fintech in the U.S. (over $1 billion in assets on the platform) to support free sending and receiving USDC. Business finance is business finance, whether it's cash or stablecoins. The "bridge between Web2 and Web3" is finally here, for real. No more maintaining separate accounts at crypto exchanges for businesses. Crypto companies and crypto funds, apply today: Meow is a financial technology company, not a bank. Bridge is a licensed Money Services Business operating out of the United States.

Brandon Arvanaghi

126,571 просмотров • 1 год назад

Former CIA Sr. Operations Officer James Acuna just posted something that should stop every defense investor cold. Dubai Airport. Not Kabul. Not Kyiv. Dubai. The drone threat isn’t theoretical anymore. It’s arrived at the most surveilled, most “protected” civilian infrastructure on earth. And while institutions were busy commissioning another study, another committee, another delayed procurement cycle, the market has already told you exactly where to position. The the counter-drone and autonomous systems supply chain will be one of the biggest sectors this next decade: $ONDS — The backbone. Iron Drone Raider is a kinetic counter-UAS interceptor. This is precisely the class of system that should be deployed at every major airport globally. $170-180M 2026 guidance. 1.5B+ cash. Backlog up 180% in 60 days. $AMPX — You can’t run persistent drone defense without persistent power. Amprius is the battery supplier solving the endurance problem for defense drones. Higher energy density = longer loiter time = actual threat coverage. $OSS — Every autonomous intercept decision happens at the edge. One Stop Systems is the edge AI compute backbone making split-second autonomous threat identification possible. No edge compute, no autonomous counter-drone. Simple. $KRKNF — The threat isn’t just airborne. Subsea autonomous systems are the next domain being contested. Kraken owns the battery and sonar bottleneck at 6,000 meters. The same neglect that left Dubai Airport exposed is playing out underwater right now. Position accordingly.​ Note. This is not financial advice.

Black Panther Capital

273,804 просмотров • 5 месяцев назад

The Spotlight Turns to CZ: Could CZ’s Wallet Spark $BNB Chain’s Next Viral Moment? The Solana ecosystem witnessed one of its biggest viral moments this week after influencer Ansem began interacting with the $ANSEM token. Following his engagement, the token rapidly surged to a market capitalization of nearly $90 million, turning a $1,000 purchase made just 24 hours earlier into approximately $1 million at its peak. The event once again highlighted how quickly community attention can reshape an entire ecosystem. Now, a different story is beginning to attract attention on BNB Chain. Seven months ago, the Hachiko community sent 25 million HACHIKO tokens to CZ’s public wallet. Rather than treating it as a short-term marketing campaign, the community continued building around the project for the next seven months, embracing Hachiko, the global symbol of loyalty, as its core identity while promoting the narrative of “The Last Inu Standing,” one of the few long-running Inu-themed projects still actively building. As Solana celebrates the “Ansem effect,” some members of the BNB Chain community are now asking a different question: Has CZ noticed the 25 million HACHIKO sitting in his wallet? If he does, another question naturally follows: Could those tokens eventually be burned, creating one of the most symbolic moments for BNB Chain’s meme ecosystem? Whether or not that happens remains unknown. But with Solana capturing headlines through community-driven momentum, many are now watching to see whether BNB Chain could produce a defining moment of its own. For now, it’s a story worth watching.

BSCN

30,089 просмотров • 1 месяц назад