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Multi Agentic System Simulator built w/ Google DeepMind Gemini 2.5 Pro Canvas. Absolutely stunning to watch how multi-agents are making progress towards the goal achievement! Maybe next step would be auto-porting this into the real framework based impl. such as .

chansung

5,198 subscribers

43,962 views • 1 year ago •via X (Twitter)

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11 Comments

chansung1 year ago

@LangChainAI maybe this is a fun example too @ankitdp_

MightyBot1 year ago

🧠 Unified Search. Smarter Meetings. Effortless CRM. MightyBot is your AI agent platform for seamless workflows—record meetings, automate CRM updates, and find answers across apps in seconds. 🌟 Focus on what matters. We'll handle the grind.

Aish Rajamani1 year ago

@GoogleDeepMind @LangChainAI 😮

aiaje com1 year ago

@GoogleDeepMind @LangChainAI 정말 멋지네요 ^^

Samuel Ekpe1 year ago

@GoogleDeepMind @LangChainAI This is so cool

Kye Gomez (swarms)1 year ago

@GoogleDeepMind @LangChainAI Should integrate this into @swarms_corp, this looks incredible.

Samuel Ekpe1 year ago

@GoogleDeepMind @LangChainAI This is really cool! We cooked this ! @algo_diver let’s chat!

chansung1 year ago

@GoogleDeepMind @LangChainAI looks cool!!

Git Maxd1 year ago

@GoogleDeepMind @LangChainAI Whoa, this is rly cool

BadTechBandit1 year ago

@GoogleDeepMind @LangChainAI Looks great! Just tried it, but it gets stuck as soon as it assign each agent to the task and does not continue from there

chansung1 year ago

@GoogleDeepMind @LangChainAI Yeah sometime buggy but it worked for me most of time

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Virtuals Protocol

216,105 views • 1 year ago

BREAKING 🚨: Google is working on multi-agent systems to help you refine ideas with tournament-like evaluation. Each run takes around 40 minutes and brings you 100 detailed ideas on a given research topic. 2 new multi-agents are being developed for Gemini Enterprise: - Idea Generation - "Create a multi-agent innovation session" - Co-Scientist - "Drive novel scientific discovery with Co-Scientist" Co-Scientist 3-step workflow 👀 - Tell Co-Scientist what you plan to research, point it to relevant data, and set your evaluation criteria. - A team of agents will generate ideas on your topic using their available data - The agents will evaluate the ideas against your criteria and rank them, tournament-style Google is not only automating research but also preparing a product that will enable others to do so. This is the next level 🤯

BREAKING 🚨: Google is working on multi-agent systems to help you refine ideas with tournament-like evaluation. Each run takes around 40 minutes and brings you 100 detailed ideas on a given research topic. 2 new multi-agents are being developed for Gemini Enterprise: - Idea Generation - "Create a multi-agent innovation session" - Co-Scientist - "Drive novel scientific discovery with Co-Scientist" Co-Scientist 3-step workflow 👀 - Tell Co-Scientist what you plan to research, point it to relevant data, and set your evaluation criteria. - A team of agents will generate ideas on your topic using their available data - The agents will evaluate the ideas against your criteria and rank them, tournament-style Google is not only automating research but also preparing a product that will enable others to do so. This is the next level 🤯

🚨 AI News | TestingCatalog

569,702 views • 8 months ago

Built this in 2 hours … lol 🫣 You can load your 3D architecture model, drop it anywhere on Google Maps, and render it at real locations…from any perspective you want. Day and night. All browser-based. Shoutout to Google AI Studio and Logan Kilpatrick Gemini 3.1 pro Preview is finally back on track after 3 rough weeks 🦾 Totally worth the wait though. My clients are gonna love this one. And I’m only 2 hours into the project. Wild Google Gemini Three.js Elon Musk Google Maps el.cine Kris Kashtanova

Built this in 2 hours … lol 🫣 You can load your 3D architecture model, drop it anywhere on Google Maps, and render it at real locations…from any perspective you want. Day and night. All browser-based. Shoutout to Google AI Studio and Logan Kilpatrick Gemini 3.1 pro Preview is finally back on track after 3 rough weeks 🦾 Totally worth the wait though. My clients are gonna love this one. And I’m only 2 hours into the project. Wild Google Gemini Three.js Elon Musk Google Maps el.cine Kris Kashtanova

Miles Dyson

94,339 views • 4 months ago

🚨 Anthropic pays $750K a year to understand how AI actually works A Stanford lecture on Agentic AI that teaches you more about how AI automation actually works than 6 months of copying Make and n8n tutorials. watch the lecture. bookmark it. Tool calling. Multi-step workflows. Planning. Reflection. The foundations behind every automation system that actually works. Most people learn this by copying tutorials blindly. Stanford teaches you WHY agents work the way they do. Then read the guide below.

🚨 Anthropic pays $750K a year to understand how AI actually works A Stanford lecture on Agentic AI that teaches you more about how AI automation actually works than 6 months of copying Make and n8n tutorials. watch the lecture. bookmark it. Tool calling. Multi-step workflows. Planning. Reflection. The foundations behind every automation system that actually works. Most people learn this by copying tutorials blindly. Stanford teaches you WHY agents work the way they do. Then read the guide below.

Khairallah AL-Awady

31,973 views • 3 months ago