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Solidus Ai Tech Presents Agent Forge: Transforming AI Technology! Agent Forge is more than a platform—it's a revolution in how users interact with AI agents. Accessible to everyone, from seasoned professionals to newcomers, it empowers users to: 🔹Create Autonomous AI Agents: Automate processes, execute strategies, and stay ahead 24/7....

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AITECH CLOUD NETWORK

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171,741 views • 1 year ago •via X (Twitter)

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11 Comments

LionelAndres's profile picture
LionelAndres1 year ago

This is going to revolutionize the AI space 🚀 #AITECH @binance

Greg Caplan 🚀's profile picture
Greg Caplan 🚀2 years ago

Stop wasting time following up with leads. Let our AI agents do it for you.

Emir's profile picture
Emir1 year ago

One of the biggest announce $AITECH have done lately. LFG

Grand Zeno's profile picture
Grand Zeno1 year ago

$AITECH to $1b mc in january, $2b in february, $3b in march and $4b in april

Coni's profile picture
Coni1 year ago

@AITECHio @binance very soon 💣💣💣💥💥💥

Drakee's profile picture
Drakee1 year ago

$AITECH 🚀🚀

Hlavacska András's profile picture
Hlavacska András1 year ago

Binance listing is a must!

GalaxyHub AI's profile picture
GalaxyHub AI1 year ago

👏 Good news 🦾🤖

MONI-MONO's profile picture
MONI-MONO1 year ago

That is huge! WEN WEN WEN

Winth's profile picture
Winth1 year ago

Time to buy more $AITECH

Sage of Me's profile picture
Sage of Me1 year ago

This will be a game changer for the AiTech team. Congratulations

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Since the dawn of time, economies were powered by labor. Now, we’re entering a new age where AI becomes the workforce, and data + compute are the new raw materials. Enter $KAI in the lifeblood of new global autonomous capital markets. 💮 Ecosystem Plan - 💮 Token Ecosystem - 👇 ⸻ 2/ $KAI isn’t just a token. It’s a complete economic engine designed to: 🔹 Power products 🔹 Fuel agent networks 🔹 Incentivize data 🔹 Govern EQ+ infrastructure 🔹 Scale emotionally intelligent AI Here’s how it works 🧵 ⸻ 3/ Tokenomics (1B $KAI total supply): 🔹 Team – 10% (vested) 🔹 Ecosystem Fund – 30% (growth + integrations) 🔹 Incentives – 15% (UGC, quests, data) 🔹 Partnerships & Advisors – 15% 🔹Liquidity – 30% (initial trading on DEX/CEX) Vested. Scarce. Sustainable. ⸻ 4/ Market Dynamics: ~300M tokens in early circulation 🔹Liquidity on DEX + CEX 🔹Governance via staking 🔹5–15% deflation from fees + burns 🔹Modeled to drive long-term value via ecosystem velocity ⸻ 5/ Utility: 🔹 Arc Terminal – Stake $KAI to analyze sentiment across Web3, politics, culture 🔹 EQ+ API – Pay + stake to embed emotional intelligence in AI agents 🔹 █████ – Future-ready staking for sovereign AI workflows (TBA) Every product reinforces token lockups + value flow. ⸻ 6/ Circular Incentive Model: Fees → 🔹 70% to treasury 🔹 25% to rewards 🔹 5% burned 🔹Contribute data → earn $KAI 🔹Proof-of-Empathy → Incentivize unique, emotionally rich inputs Deflation + utility = sustainable ecosystem flywheel. ⸻ 7/ Roadmap: 🔹 Q3-Q4 2025 – Mint, Arc Terminal beta, staking 🔹 Q1-Q2 2026 – API v2, █████ beta, Kaiko Hub: leading AI ecosystem in UAE 🔹 Q3/Q4 2026+ – Scale to 1M+ agents, cross-industry integrations (health, edu, media) Emotion becomes infrastructure. And it scales. ⸻ 8/ TL;DR: $KAI powers the next evolution of AI economies. From empathy loops to agent networks. From data feedback to decentralized governance. This is not just about tokens. It’s about rebuilding value itself. 💮
1:44

Since the dawn of time, economies were powered by labor. Now, we’re entering a new age where AI becomes the workforce, and data + compute are the new raw materials. Enter $KAI in the lifeblood of new global autonomous capital markets. 💮 Ecosystem Plan - 💮 Token Ecosystem - 👇 ⸻ 2/ $KAI isn’t just a token. It’s a complete economic engine designed to: 🔹 Power products 🔹 Fuel agent networks 🔹 Incentivize data 🔹 Govern EQ+ infrastructure 🔹 Scale emotionally intelligent AI Here’s how it works 🧵 ⸻ 3/ Tokenomics (1B $KAI total supply): 🔹 Team – 10% (vested) 🔹 Ecosystem Fund – 30% (growth + integrations) 🔹 Incentives – 15% (UGC, quests, data) 🔹 Partnerships & Advisors – 15% 🔹Liquidity – 30% (initial trading on DEX/CEX) Vested. Scarce. Sustainable. ⸻ 4/ Market Dynamics: ~300M tokens in early circulation 🔹Liquidity on DEX + CEX 🔹Governance via staking 🔹5–15% deflation from fees + burns 🔹Modeled to drive long-term value via ecosystem velocity ⸻ 5/ Utility: 🔹 Arc Terminal – Stake $KAI to analyze sentiment across Web3, politics, culture 🔹 EQ+ API – Pay + stake to embed emotional intelligence in AI agents 🔹 █████ – Future-ready staking for sovereign AI workflows (TBA) Every product reinforces token lockups + value flow. ⸻ 6/ Circular Incentive Model: Fees → 🔹 70% to treasury 🔹 25% to rewards 🔹 5% burned 🔹Contribute data → earn $KAI 🔹Proof-of-Empathy → Incentivize unique, emotionally rich inputs Deflation + utility = sustainable ecosystem flywheel. ⸻ 7/ Roadmap: 🔹 Q3-Q4 2025 – Mint, Arc Terminal beta, staking 🔹 Q1-Q2 2026 – API v2, █████ beta, Kaiko Hub: leading AI ecosystem in UAE 🔹 Q3/Q4 2026+ – Scale to 1M+ agents, cross-industry integrations (health, edu, media) Emotion becomes infrastructure. And it scales. ⸻ 8/ TL;DR: $KAI powers the next evolution of AI economies. From empathy loops to agent networks. From data feedback to decentralized governance. This is not just about tokens. It’s about rebuilding value itself. 💮

KAIKO

37,495 views • 1 year ago

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):
15:38

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):

Matt Dancho (Business Science)

35,452 views • 1 year ago

New course: Building Coding Agents with Tool Execution, taught by Tereza Tizkova and Fra from E2B. Most AI agents are limited to predefined function calls. This short course teaches you to build agents that write and execute code to accomplish tasks, accessing entire programming language ecosystems instead of being restricted to a fixed set of tools. You'll learn to run agent-generated code safely in sandboxed cloud environments that protect your systems from harmful operations. Skills you'll gain: - Build agents that write and execute code, manage files, and handle errors autonomously through feedback loops - Run agent code safely in E2B cloud sandboxes and understand tradeoffs between local, containerized, and cloud execution - Create a data analyst agent that explores visualizes data with Pandas - Create a full-stack agent that builds complete Next.js web applications Join and build agents that code their way through complex tasks:
2:23

New course: Building Coding Agents with Tool Execution, taught by Tereza Tizkova and Fra from E2B. Most AI agents are limited to predefined function calls. This short course teaches you to build agents that write and execute code to accomplish tasks, accessing entire programming language ecosystems instead of being restricted to a fixed set of tools. You'll learn to run agent-generated code safely in sandboxed cloud environments that protect your systems from harmful operations. Skills you'll gain: - Build agents that write and execute code, manage files, and handle errors autonomously through feedback loops - Run agent code safely in E2B cloud sandboxes and understand tradeoffs between local, containerized, and cloud execution - Create a data analyst agent that explores visualizes data with Pandas - Create a full-stack agent that builds complete Next.js web applications Join and build agents that code their way through complex tasks:

Andrew Ng

203,595 views • 7 months ago

🚀 A powerful financial advisor agent is about to join the ChainOpera AI Agent Network! With NVIDIA becoming the world’s first $5T company (congrats NVIDIA 👏), everyone’s wondering: what’s next? This upcoming AI Financial Advisor Agent gives you a glimpse of that future. Whether you’re exploring NVIDIA, Tesla, or any other stock, it can gather and analyze financial data, visualize market trends, track news and analyst ratings, and even assist with risk management. All in one intelligent, collaborative agent. 🎥 Check out this short demo to see it in action. 🌐 Stay tuned ... it’s joining the ChainOpera AI Agent Network very soon! #AIagents #DeFi #CryptoAI #FinTech #ChainOperaAI
2:20

🚀 A powerful financial advisor agent is about to join the ChainOpera AI Agent Network! With NVIDIA becoming the world’s first $5T company (congrats NVIDIA 👏), everyone’s wondering: what’s next? This upcoming AI Financial Advisor Agent gives you a glimpse of that future. Whether you’re exploring NVIDIA, Tesla, or any other stock, it can gather and analyze financial data, visualize market trends, track news and analyst ratings, and even assist with risk management. All in one intelligent, collaborative agent. 🎥 Check out this short demo to see it in action. 🌐 Stay tuned ... it’s joining the ChainOpera AI Agent Network very soon! #AIagents #DeFi #CryptoAI #FinTech #ChainOperaAI

ChainOpera AI

56,231 views • 8 months ago

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!
0:20

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!

Loomlay

26,140 views • 1 year ago