AI Agents explained: An Introduction

How to apply AI agents with LLM systems? What is important to know about the interplay of LLMs, their task specific agents and their tools? Can you code an AI Agent? A simple Introduction for beginners.

#ai
#agents

[zsi]

Great content, watched a few of your videos, and the technical discussions are great. I have been working on autonomous AI agents myself for work, and this field chamges so quickly that it is hard to keep up. Thank you very much. I particularly like how you structure the topics in such an organized and methodical way because it really helps me clean out the disorganized clutter that rxists in my mind around all this.

[Davipar]

Always with the best content. Thank you so much for your uploads! thought-provoking and valuable 🙏

[andydataguy]

I'm so excited to see your video on agent orchestration! 😍

[matten_zero]

I built something like this recently. Its like a chatbot within a chatbot. It can analyze a user prompt and within a chat session and in real-time create a command that is part of an `if` statement. When the bot issues the command the reat if the script proceeds to pull some data, print a statement...the possiblities are endless. This tech can be a more intelligent and useful version of Siri or Alexa.

Hook this up to some robotics and youve got the beginning of an android.

The prompt engineering is super important so that your internal bot only gives commands.

[horacioariash]

🎯 Key Takeaways for quick navigation:

00:13 🤖 *Los agentes de IA pueden ser de diferentes tipos, como agentes basados en reglas, agentes autónomos, agentes aumentados y sistemas multiagentes.*
01:04 📊 *En el pasado, se utilizaban agentes basados en reglas para conectar modelos de lenguaje con fuentes externas, como API de información meteorológica.*
02:26 🧠 *Los agentes necesitan memoria y datos para aprender y mejorar su rendimiento, lo que implica pasar de agentes basados en reglas a agentes más autónomos.*
03:21 📖 *La capacidad de aprendizaje y el razonamiento son elementos clave para los agentes, ya que les permiten analizar tareas y tomar decisiones.*
10:45 🤖 *La interacción entre modelos de visión, lenguaje y acción permite a los agentes realizar tareas en el mundo real, como mover robots y tomar decisiones basadas en datos visuales y de lenguaje.*

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