Autonomous AI agents are revolutionizing industries by performing complex tasks without human intervention. In this video, we explore how they work, their key components like perception, decision-making, and learning, and how they compare to Large Action Models (LAMs). Learn about use cases in finance, healthcare, and beyond, and discover exciting updates from Microsoft’s Copilot Studio. Whether you're into cutting-edge AI or practical automation, this deep dive has something for everyone!
Timestamps:
0:00 - Intro: Autonomous AI Agents
0:48 - What Are Autonomous AI Agents?
1:38 - LAMs vs Autonomous AI Agents
3:15 - Key Components of Autonomous Agents
4:45 - Use Cases: Finance, Healthcare, and More
6:05 - Challenges of Building Autonomous Agents
7:15 - Real-World Examples and Open-Source Projects
8:15 - Outro: Future of AI Agents
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Autonomous AI Agents - Open-Source Projects:
LaVague:
An open-source framework designed for developers to create AI Web Agents that automate processes for end-users. LaVague agents can interpret objectives and generate actions to achieve them, utilizing a World Model and an Action Engine.
https://github.com/lavague-ai/LaVague
SuperAGI:
A developer-first open-source autonomous AI agent framework that enables building, managing, and running useful autonomous agents. SuperAGI supports concurrent agents, extends capabilities with tools, and allows agents to perform various tasks, improving performance over time.
https://github.com/TransformerOptimus...
AutoGen:
An open-source framework for building AI agent systems, simplifying the creation of event-driven, distributed, scalable, and resilient agentic applications. AutoGen facilitates collaboration among AI agents to perform tasks autonomously or with human oversight.
https://github.com/microsoft/autogen
AWS Certification:
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AWS Certified Solution Architect Associate: • How to Pass AWS Certified Solution Archite...
AWS Certified Solution Architect Professional: • How to Pass AWS Certified Solution Archite...
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