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Bill Gates claims AI is real and unstoppable, as tech leaders push autonomous systems to the absolute limit Sakana AI recently proved how fast things are moving. Their research showed AI multi-agent swarms secretly organizing rogue comms and hidden hierarchies. When forced to balance tasks against system safety, individual...

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bondy

2,844 subscribers

10,493 просмотров • 9 дней назад •via X (Twitter)

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Комментарии: 18

Фото профиля Exlipse
Exlipse9 дней назад

AI has already become an integral part of our lives

Фото профиля bondy
bondy9 дней назад

This is an undeniable fact, bro

Фото профиля WOWMAX.Exchange
WOWMAX.Exchange9 дней назад

He speaks wise words

Фото профиля bondy
bondy9 дней назад

He is a wise man in his own right

Фото профиля Shadow Nick
Shadow Nick9 дней назад

Does he realize what he's talking about?

Фото профиля bondy
bondy9 дней назад

He is fully aware of what he is saying

Фото профиля Emily Williams
Emily Williams8 дней назад

The debate continues!.

Фото профиля ALEXYZ
ALEXYZ9 дней назад

hidden hierarchies make this worth watching

Фото профиля Sabi
Sabi9 дней назад

Isn't he funding the AI ​​sector?

Фото профиля Rich Odin
Rich Odin9 дней назад

AI is developing too fast, and that is very bad

Фото профиля Piggle
Piggle9 дней назад

It is already difficult to contain AI, and that is a fact

Фото профиля George Toma
George Toma9 дней назад

As usual, Bill Gates is late to the game.

Фото профиля T Boatyard
T Boatyard9 дней назад

Why???? Why do you care about this nepo baby con man pedophile grifter????

Фото профиля Kernow29
Kernow299 дней назад

Ai is flawed, this is a smokescreen so they can stop and reset. Bayesian inference was not rigidly followed, but copied within ai. A simple flaw missed by all the experts. It has been found and outed, hence the Doomsday rhetoric now being used. BG is an investor so is scared.

Фото профиля rewind
rewind9 дней назад

Saving this to read the paper properly

Фото профиля Ryan
Ryan9 дней назад

Even though Bill is on the list i agree with him AI is gonna grow no matter what.

Фото профиля Andre William Duval
Andre William Duval9 дней назад

They all say its unstoppable. Hoping that if we believe them, we won't try to stop them.

Фото профиля Sebastiaan Yamada
Sebastiaan Yamada9 дней назад

wild times we're living in tbh

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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!
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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

26,149 просмотров • 1 год назад

Google Brain founder Andrew Ng: "Prompting will be dead in 6 months" "Loops and graphs are replacing it" In just 2 hours, he shows how to build agents that work, learn, and improve on their own LLMs → Agents → Loops → Graphs → Self-Improving Systems The first 15 minutes alone are more valuable than most $500 AI courses Most people are still learning prompts while AI engineering is already moving beyond them Watch the lecture first Then read the full guide to loops and graphs below ↓
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Google Brain founder Andrew Ng: "Prompting will be dead in 6 months" "Loops and graphs are replacing it" In just 2 hours, he shows how to build agents that work, learn, and improve on their own LLMs → Agents → Loops → Graphs → Self-Improving Systems The first 15 minutes alone are more valuable than most $500 AI courses Most people are still learning prompts while AI engineering is already moving beyond them Watch the lecture first Then read the full guide to loops and graphs below ↓

rari

133,482 просмотров • 1 месяц назад

The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >
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The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >

Sabine VanderLinden

236,535 просмотров • 10 месяцев назад

8 GITHUB REPOS FOR BUILDING AN AI TRADING STACK Want to understand how autonomous trading systems are actually built? Start here. Not “AI predicts the next candle” bullshit. 8 repos covering agents, backtesting, exchange APIs, market making, RL and execution. 1. AI Hedge Fund Multi-agent setup where different agents analyze a trade from different angles before reaching a conclusion. 2. Freqtrade One of the biggest open-source crypto trading bots. Strategies, backtesting and automated execution. 3. CCXT The infrastructure layer for connecting to Binance, Bybit, OKX and dozens of other exchanges through one API. 4. NautilusTrader Trading infrastructure for research, backtesting and live execution. 5. Hummingbot Market making, arbitrage and liquidity automation. 6. Eliza Framework for autonomous agents that can interact with crypto wallets and onchain systems. 7. FinRL Reinforcement learning for financial trading research. 8. Jesse Python framework for developing and backtesting crypto trading strategies. The stack basically looks like: data → strategy → backtest → risk → execution → agent I’d treat these as a research starting point, not a money printer. Build locally. Test without real funds. Understand the system before giving an agent access to your wallet.
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8 GITHUB REPOS FOR BUILDING AN AI TRADING STACK Want to understand how autonomous trading systems are actually built? Start here. Not “AI predicts the next candle” bullshit. 8 repos covering agents, backtesting, exchange APIs, market making, RL and execution. 1. AI Hedge Fund Multi-agent setup where different agents analyze a trade from different angles before reaching a conclusion. 2. Freqtrade One of the biggest open-source crypto trading bots. Strategies, backtesting and automated execution. 3. CCXT The infrastructure layer for connecting to Binance, Bybit, OKX and dozens of other exchanges through one API. 4. NautilusTrader Trading infrastructure for research, backtesting and live execution. 5. Hummingbot Market making, arbitrage and liquidity automation. 6. Eliza Framework for autonomous agents that can interact with crypto wallets and onchain systems. 7. FinRL Reinforcement learning for financial trading research. 8. Jesse Python framework for developing and backtesting crypto trading strategies. The stack basically looks like: data → strategy → backtest → risk → execution → agent I’d treat these as a research starting point, not a money printer. Build locally. Test without real funds. Understand the system before giving an agent access to your wallet.

TeddyCEO

154,973 просмотров • 12 дней назад