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Introducing Agent Swarms Swarms are prebuilt multi-agent teams. First swarm is Value Investors: • ben graham • charlie munger • warren buffett Our swarms are inspired by LangChain. Possibilities here are endless.

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virat

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16,203 görüntüleme • 1 yıl önce •via X (Twitter)

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I added multi-agents to our hedge fund UX. Best part is the agents run in parallel. We now have: 1 • Warren Buffett agent 2 • Charlie Munger agent All made easy thanks to LangChain
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I added multi-agents to our hedge fund UX. Best part is the agents run in parallel. We now have: 1 • Warren Buffett agent 2 • Charlie Munger agent All made easy thanks to LangChain

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Welcome to Eliza Cloud. The ultimate, agent building platform. Create agentic apps, monetize, and promote all in 1 place. plugin support, MCPs, x402, 8004 swarms. Your agent powered by Eliza, supercharged. Made with <3 from Eliza Labs. Open Beta Live Now.
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Yesterday we launched the Agent Builder Template Library. Agent templates are more than a starting point. They’re ready to deploy and fully customizable by giving your agent feedback in plain language. 🧵 for highlights Try Agent Builder:
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"The possibilities are truly endless."
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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

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I added a new agent to the AI hedge fund. The Ben Graham agent. Uses Graham's investing principles: 1 • calculates net-net working capital 2 • computes Graham Number 3 • checks earnings stability 4 • analyzes financial strength 5 • demands margin of safety Ben Graham is the godfather of value investing. His most famous student is Warren Buffett. This is one of our most disciplined agents - it only says "buy" when a stock is really cheap. Here is how it works: 1. Net-net analysis: Checks if a stock is so cheap that its liquid assets alone are worth more than its market price. 2. Graham Number: A special formula that tells us if a stock price is a bargain based on earnings and book value. 3. Earnings Check: Makes sure the company has stable, growing profits over many years. 4. Financial Health: Looks for companies with low debt and strong cash positions. 5. Margin of Safety: Only buys when there's a big discount to protect against mistakes. What agent should we add next?
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I added a new agent to the AI hedge fund. The Ben Graham agent. Uses Graham's investing principles: 1 • calculates net-net working capital 2 • computes Graham Number 3 • checks earnings stability 4 • analyzes financial strength 5 • demands margin of safety Ben Graham is the godfather of value investing. His most famous student is Warren Buffett. This is one of our most disciplined agents - it only says "buy" when a stock is really cheap. Here is how it works: 1. Net-net analysis: Checks if a stock is so cheap that its liquid assets alone are worth more than its market price. 2. Graham Number: A special formula that tells us if a stock price is a bargain based on earnings and book value. 3. Earnings Check: Makes sure the company has stable, growing profits over many years. 4. Financial Health: Looks for companies with low debt and strong cash positions. 5. Margin of Safety: Only buys when there's a big discount to protect against mistakes. What agent should we add next?

virat

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mob of white women swarms overturned starbucks truck in mass looting spree on I-95
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mob of white women swarms overturned starbucks truck in mass looting spree on I-95

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