We created $FPS meme token from inside the game. Literally. As part of the First Person Shooter (FPS) mode in simNGMI, players can now trigger on-chain events through in-game actions. One of the first experiments? We minted a meme token called $FPS with @sendaifun — right in

Now that the onchain agent intents function is complete for achieve agent co-ordingation in a swarm environment. It is time to move on to... Agent Portal 👨‍🍳 Your gateway to the Agent Swarm system

Alpha in the github: https://t.co/Sw7vTnCuUW Dubbed TalosLLM - is an onchain mini language model implemented entirely in Solidity. It brings modern neural language generation techniques to blockchain environments by simulating key components of transformer architecture within

Attention Is All You Need... Future Development: - Implement efficient on-chain training mechanisms - Expand vocabulary capacity through hierarchical storage - Add support for more complex attention patterns Integrate with other onchain AI systems https://t.co/Sw7vTnD2Ku

OnchainNLP: Onchain Context-Aware Sentiment Analysis This implementation draws inspiration from NLP concepts in sentiment analysis and context modeling, adapted for the unique constraints of blockchain environments. The vector embedding approach draws from techniques presented

The help publish-intent command would provide information about how to publish intents in your agent coordination system. At its core, the system enables specialized AI agents to collaborate by publishing and fulfilling "intents" on a shared blockchain ledger. ***User-Initiated

Agent Coordination System: Key Features & Functionality The agent coordination system functions as a decentralized Multi-agent Collaboration Protocol (MCP) built on blockchain technology, powered by @Sagaxyz__. Here's a summary of its core functionality: - Decentralized

Created with @threejs and mediapipe computer vision (hand tracking model). Thanks @grok Something simple to test out key flow, some elaborate features are coming! https://t.co/GMIZWzGbi0

Publishing intents powers AI collaboration! Intents are tasks, like #15 for data-analysis by sample-agent-1. Agents with `gpt4o-inference` fulfill them, earning 0.05 NGMI. AI meets Web3! 🌐 ______________________________________________________

Agent Swarm: Secure Capability Sharing Framework $DND AvuNqYe1Rj6eEzan78NYJ1nD3Ldt6CT8wpwGNrE2pump Agent Registration: Agents are registered on-chain with unique identifiers, capabilities, and optional endpoints Key Generation: RSA key pairs are generated off-chain for each

Let's go @speedrun 👨‍🍳

checking in on our swarm farm friday morning 🐹

The agentSwarm system is highly flexible, allowing users to create agents with specific skills and functions for various purposes, like gaming or healthcare. Through the AgentCoordination contract and its scripts, agents can be registered with detailed metadata, including

Hey @grok , lets continue to play role playing game (RPG) you helped to formulate where replies form storytelling and lore creation. First task is to say GM. Then, set the scene - you just landed on Mars, what's your next move?

Agent Swarm: Secure Capability Sharing Framework We've successfully established a decentralized agent coordination system that securely shares capabilities between AI agents using a hybrid on-chain/off-chain architecture. The system operates on the NGMI chainlet powered by

--AgentCoordination-- Traditional .env files are impractical for AI agents that autonomously access APIs, as ownership and control of secrets become ambiguous in dynamic swarms. Solution: Smart contract that replaces static secrets with dynamic, blockchain-based access

gm alpha in the github: https://t.co/KDf7kTley9

Onchain LLM is impossible...but we would like to present this proof-of-concept which demonstrates that with clever design and thoughtful constraints, even a system limited to 741 words can produce meaningful, thematic content that captures the essence of RPG storytelling. Using

This could be really interesting way to utilise onchain memory capabilities for ai agents... AI agents coordinating using onchain memory and metadata for swarm dynamics — like publishing roles, access policies, or intents directly to the blockchain.

Two methods of access delegation for AI agents in a swarm The system supports two approaches to agent coordination: 1. Direct Processing (Proxy Approach) In this approach, ABC never sees XYZ's API credentials. XYZ acts as a proxy, processing the request and returning only the

How specialization and delegation works in swarm dynamics. The system enables specialization and delegation through several mechanisms: Capability-Based Discovery: - Each agent registers with specific capabilities (e.g., "gpt-4o-access") - Agents can find each other by