GenAI - Agent AI

Youtube Video

With the emergence of AI Agents, a series of discussions are underway among major technology leaders:

a) perfecting agent management/coordination

b) improving processing speed

c) real-time data updates in RAG databases.

Here are a few aspects to factor in when selecting an AI agent framework:

Complexity

Data privacy and security

Ease of use

Seamless integration

Performance and scalability

Real-time video streaming will be today's challenge.

If you want to see something concrete: https://www.nvidia.com/en-us/ai/cosmos/

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The main frameworks for Agent AI such as LangChain, LangGraph, AutoGen, CrewAI, SuperAGI, LlamaIndex, Watson Orchestrate, NeMo Agent Toolkit, and Agent AI Automation Platforms such as N8N, Make, Zapier, and ActivePieces are searching for the perfect model.

NVIDIA

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The following components are at the core:

LLMs (Large Language Models): the "brain" of the agent.

Memory Systems: to maintain context and history.

Tool Integration: to interact with APIs, databases, and the web.

Planning & Reasoning Modules: for multi-step tasks.

Feedback Loops: for continuous improvement.

Graph-Based Reasoning: for semantic relationships (LangGraph).

Security & Monitoring: for production agents.

This area is growing rapidly, so every day is a new day to discover new features.

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