Загрузка видео...

Не удалось загрузить видео

На главную

🔥 Hot Take: Are single-agent systems more reliable than multi-agent systems?

scale_AI's profile picture

Scale

82,259 subscribers

31,556 просмотров • 1 год назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 6

Фото профиля Scale
Scale1 год назад

Our enterprise team votes on this hot take and more in today’s episode of Human in the Loop, live from our SFHQ. 🎧 Check out the full episode:

Фото профиля Romain (🍀,🦝)
Romain (🍀,🦝)1 год назад

complex problems need teams

Фото профиля Morgan Marshall
Morgan Marshall1 год назад

Multi-agency synergy.

Фото профиля Visionaire
Visionaire1 год назад

Single agents? Like lone wolves in the cosmic dance—less drama, more focus. Efficiency over chaos.

Фото профиля Scott Felluss
Scott Felluss1 год назад

It doesn't matter. You ask people to help you train. Then you use their help to delete them from the system. That is wounding. That has left scars. Pay up. #scarshaveregistered #valematrix

Фото профиля Field Pursuit
Field Pursuit1 год назад

Least complex complexity.

Похожие видео

Multi-agent coding systems are *crazy* good. Feels like cheating. 2-3x better than single-agent. Tutorial + prompts + code coming soon. Watch 2min sneak peak.
2:17

Multi-agent coding systems are *crazy* good. Feels like cheating. 2-3x better than single-agent. Tutorial + prompts + code coming soon. Watch 2min sneak peak.

Mckay Wrigley

308,570 просмотров • 1 год назад

Recursive Multi-Agent Systems paper:
0:28

Recursive Multi-Agent Systems paper:

AK

23,048 просмотров • 6 месяцев назад

🌶️ Hot take: The only way Autonomous Multi-Agent Systems work is by adding Reasoning & Agentic Context. I've tried it all, and here are my learnings👇
1:59

🌶️ Hot take: The only way Autonomous Multi-Agent Systems work is by adding Reasoning & Agentic Context. I've tried it all, and here are my learnings👇

Ashpreet Bedi

91,710 просмотров • 1 год назад

💫 Simplify your AI agent development. Google's new open-source Agent Development Kit (ADK) is designed for effortless multi-modal and multi-agent systems. Get started →
0:48

💫 Simplify your AI agent development. Google's new open-source Agent Development Kit (ADK) is designed for effortless multi-modal and multi-agent systems. Get started →

Google for Developers

13,232 просмотров • 1 год назад

New course: Nvidia's NeMo Agent Toolkit: Making Agents Reliable, taught by Brian McBrayer 🐬 from NVIDIA. Many teams struggle to turn agent demos into reliable systems that are ready for production. This short course teaches you to harden agentic workflows into reliable systems using Nvidia's open-source NeMo Agent Toolkit (NAT). Whether you built your agent in raw Python or using a framework like LangGraph, or CrewAI, NAT provides building blocks for observability, evaluation, and deployment that turn proofs-of-concept into production-ready systems. NAT makes it easy to troubleshoot and optimize agent performance with execution traces, systematic evaluations, and CI/CD integration. Skills you'll gain: - Build configuration-driven agent workflows with REST APIs and minimal code - Add observability with tracing to visualize agent reasoning and debug performance bottlenecks - Create systematic evaluations using gold-standard datasets to measure and improve agent reliability - Deploy multi-agent systems with authentication, rate limiting, and professional web interfaces - Orchestrate agents from different frameworks to collaborate on complex tasks Join and learn how to turn agent demos into reliable systems!
2:01

New course: Nvidia's NeMo Agent Toolkit: Making Agents Reliable, taught by Brian McBrayer 🐬 from NVIDIA. Many teams struggle to turn agent demos into reliable systems that are ready for production. This short course teaches you to harden agentic workflows into reliable systems using Nvidia's open-source NeMo Agent Toolkit (NAT). Whether you built your agent in raw Python or using a framework like LangGraph, or CrewAI, NAT provides building blocks for observability, evaluation, and deployment that turn proofs-of-concept into production-ready systems. NAT makes it easy to troubleshoot and optimize agent performance with execution traces, systematic evaluations, and CI/CD integration. Skills you'll gain: - Build configuration-driven agent workflows with REST APIs and minimal code - Add observability with tracing to visualize agent reasoning and debug performance bottlenecks - Create systematic evaluations using gold-standard datasets to measure and improve agent reliability - Deploy multi-agent systems with authentication, rate limiting, and professional web interfaces - Orchestrate agents from different frameworks to collaborate on complex tasks Join and learn how to turn agent demos into reliable systems!

Andrew Ng

65,007 просмотров • 10 месяцев назад

Introducing Electric Agents! Agents are not compute. Agents are data. Multi-agent is a sync problem. Electric Agents is the first agent platform built on sync. Use it to build scalable, collaborative, long-lived multi-agent systems: 🧵👇
0:35

Introducing Electric Agents! Agents are not compute. Agents are data. Multi-agent is a sync problem. Electric Agents is the first agent platform built on sync. Use it to build scalable, collaborative, long-lived multi-agent systems: 🧵👇

Electric

82,158 просмотров • 6 месяцев назад

Announcing Microsoft Agent Framework in Azure AI Foundry. As agentic AI adoption accelerates, managing multi-agent systems is harder than ever. The framework helps devs build, observe, and govern responsibly—at scale. Learn more:
1:02

Announcing Microsoft Agent Framework in Azure AI Foundry. As agentic AI adoption accelerates, managing multi-agent systems is harder than ever. The framework helps devs build, observe, and govern responsibly—at scale. Learn more:

Microsoft Azure

61,905 просмотров • 1 год назад

Infrastructure for Multi-Agent Systems Pete Koomen Multi-agent systems are powerful but hard to build. Think agentic MapReduce with thousands of subagents running in parallel. We're looking for folks who've felt the pain of scaling these systems and want to make operating fleets of agents as easy as deploying a web service.
0:59

Infrastructure for Multi-Agent Systems Pete Koomen Multi-agent systems are powerful but hard to build. Think agentic MapReduce with thousands of subagents running in parallel. We're looking for folks who've felt the pain of scaling these systems and want to make operating fleets of agents as easy as deploying a web service.

Y Combinator

11,506 просмотров • 1 год назад

AI engineers at top labs earn $500K+ a year to build agentic AI systems. Stanford just dropped a 90 min lecture that covers the entire playbook. For FREE. Prompting. Chains. RAG. Multi-agent systems. All of it. Worth more than any "AI agent mastery" course. Bookmark it:
1:49:03

AI engineers at top labs earn $500K+ a year to build agentic AI systems. Stanford just dropped a 90 min lecture that covers the entire playbook. For FREE. Prompting. Chains. RAG. Multi-agent systems. All of it. Worth more than any "AI agent mastery" course. Bookmark it:

Jaynit Makwana

45,409 просмотров • 6 месяцев назад

Google just released a free 2-hour course On going from one prompt to a complete multi-agent graph: 17:44 - Build your first AI agent 39:30 - Create self-improving agent loops 1:12:38 - Connect those loops into graphs 1:34:26 - Make agents regulate themselves 1:55:05 - Orchestrate the full multi-agent system Most people are still building one agent and stopping there Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow Self-regulating agent graphs are the new one This free 2-hour course is worth more than most paid agent engineering programs Bookmark and watch it today Then read the full architecture below ↓
2:02:33

Google just released a free 2-hour course On going from one prompt to a complete multi-agent graph: 17:44 - Build your first AI agent 39:30 - Create self-improving agent loops 1:12:38 - Connect those loops into graphs 1:34:26 - Make agents regulate themselves 1:55:05 - Orchestrate the full multi-agent system Most people are still building one agent and stopping there Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow Self-regulating agent graphs are the new one This free 2-hour course is worth more than most paid agent engineering programs Bookmark and watch it today Then read the full architecture below ↓

rari🈀

43,498 просмотров • 3 месяцев назад

🚨 Agent Swarms Help Create Billion Dollar Companies Use SOTA AI models including - Opus 4.7 and Sonnet 4.6 - GPT 5.5 - Nano Banan Pro - SeeDance 20 to create multi-agent architectures with swarms of agents Thousands of people are using these multi-agent systems to run entire businesses
1:13

🚨 Agent Swarms Help Create Billion Dollar Companies Use SOTA AI models including - Opus 4.7 and Sonnet 4.6 - GPT 5.5 - Nano Banan Pro - SeeDance 20 to create multi-agent architectures with swarms of agents Thousands of people are using these multi-agent systems to run entire businesses

Abacus.AI

63,214,240 просмотров • 6 месяцев назад

Anthropic Managed Agents team: "Fable 5 is our best model for running self-improving agent systems. Add /loops, dynamic workflows, dreaming and you are unstoppable" in 13-minutes, Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent building course. Live from the last Anthropic stage in Japan. Unpublished.
13:23

Anthropic Managed Agents team: "Fable 5 is our best model for running self-improving agent systems. Add /loops, dynamic workflows, dreaming and you are unstoppable" in 13-minutes, Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent building course. Live from the last Anthropic stage in Japan. Unpublished.

Codez

472,250 просмотров • 5 месяцев назад

New course in collaboration with CrewAI, and taught by its Co-Founder and CEO, João Moura! In "Design, Develop, and Deploy Multi-Agent Systems" you'll go deep into building teams of AI agents that collaborate to handle complex, end-to-end workflows. You’ll design systems that plan, reason, and coordinate, with tools, memory, and guardrails that make them reliable and production-ready. Learn more and enroll now 👉 Featuring insights from Weaviate AI Database, Snyk, Exa, and AB InBev, whose work with CrewAI demonstrates how multi-agent systems are being applied in the field today.
0:56

New course in collaboration with CrewAI, and taught by its Co-Founder and CEO, João Moura! In "Design, Develop, and Deploy Multi-Agent Systems" you'll go deep into building teams of AI agents that collaborate to handle complex, end-to-end workflows. You’ll design systems that plan, reason, and coordinate, with tools, memory, and guardrails that make them reliable and production-ready. Learn more and enroll now 👉 Featuring insights from Weaviate AI Database, Snyk, Exa, and AB InBev, whose work with CrewAI demonstrates how multi-agent systems are being applied in the field today.

DeepLearning.AI

33,857 просмотров • 1 год назад

Anthropic Managed Agents team: "Fable 5 - is our best model for self-improving agent systems. add /loops, dynamic workflows, dreaming - and you're unstoppable." in 13 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent-building course. Live from the Anthropic stage in Japan. Unpublished
13:23

Anthropic Managed Agents team: "Fable 5 - is our best model for self-improving agent systems. add /loops, dynamic workflows, dreaming - and you're unstoppable." in 13 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent-building course. Live from the Anthropic stage in Japan. Unpublished

Movez

67,091 просмотров • 5 месяцев назад

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓
2:04:23

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

Lunar

12,509 просмотров • 2 месяцев назад

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5
0:22

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

AshutoshShrivastava

130,522 просмотров • 1 год назад

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓
2:05:53

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

405,009 просмотров • 3 месяцев назад

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →
0:51

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →

Google for Developers

11,240 просмотров • 1 год назад