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Join Cedric Clyburn as he explores the differences and use cases of Retrieval Augmented Generation (RAG) and fine-tuning in enhancing large language models. This video covers the strengths, weaknesses, and common applications of both techniques, and provides insights on how to choose between them using machine learning and natural language processing principles

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#AI #LargeLanguageModels #FineTuning #RAG #ReinforcementLearning #MachineLearning #NaturalLanguageProcessing

The KL divergence of distributions P and Q is a measure of how similar P and Q are.
However, the KL Divergence of P and Q is not the same as the KL Divergence of Q and P.
Why?
Learn the intuition behind this in this friendly video.

More about the KL Divergence formula:
https://www.youtube.com/watch?v=sjgZxuCm_8Q

🖥️ Download the free AI Agents PDFs: https://clickhubspot.com/f865c2

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Summary:
AI Agents seem overwhelming, but in 2026, we've gotten to the point that any non-technical person can create and manage their own AI agents to accomplish tasks. I cover everything simply: what an agent actually is, what to automate, how to start, and build two agents step by step using two of the leading platforms. Then dive into common pitfalls and how to avoid them. This is everything you need to get started with building AI agents in 2026, no coding required.

Chapters
0:00 Intro
0:50 What is an agent?
1:37 Where we're at right now
2:08 What to automate first
4:58 How to start
7:01 Time to build
7:24 Build 1
14:04 Build 2
20:43 More complex agents
22:03 Zapier vs n8n
22:40 Common Pitfalls (and how to avoid them)
24:44 The real skill

Agents are everywhere these days, but with so much information available, it’s easy to feel overwhelmed. Most tutorials and videos focus on specific frameworks without covering the fundamental principles behind these systems.

This course takes a different approach. Over four modules, you'll learn to implement the four core agentic patterns from scratch, using just Python and Groq LLMs:

* Reflection Pattern
* Tool Use Pattern
* Planning Pattern
* Multi-Agent Pattern

Explore the written lessons on my Substack blog:

https://theneuralmaze.substack.com/

Check out the code here:

https://github.com/neural-maze/agentic_patterns

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If you like this content, you can also follow me here:

📩 Substack - https://theneuralmaze.substack.com/
💼 LinkedIn - https://www.linkedin.com/in/migueloteropedrido/
💻 GitHub - https://github.com/MichaelisTrofficus
🐦 Twitter - https://x.com/moteropedrido

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0:00 Introduction
2:48 Module 1 - Reflection Pattern
20:40 Module 2 - Tool Pattern
44:22 Module 3 - Planning Pattern
1:13:16 Module 4 - MultiAgent Pattern
1:41:00 Conclusion

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Creative Commons — Attribution 3.0 Unported — CC BY 3.0
Free Download / Stream: https://bit.ly/3wVnIXs
Music promoted by Audio Library https://bit.ly/3TDW3TT
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Carefree by Kevin MacLeod http://incompetech.com
Creative Commons — Attribution 4.0 International — CC BY 4.0
Free Download / Stream: https://bit.ly/_carefree
Music promoted by Audio Library • Carefree – Kevin MacLeod (No Copyrigh...
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Music ⓒ - Kevin MacLeod

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Track: Morocco — Amine Maxwell [Audio Library Release]
Music provided by Audio Library Plus
Watch:

• Morocco — Amine Maxwell | Free Backgr...
Free Download / Stream: https://alplus.io/morocco
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MIT 8.04 Quantum Physics I, Spring 2013
View the complete course: http://ocw.mit.edu/8-04S13
Instructor: Allan Adams

In this lecture, Prof. Adams gives a panoramic view on various experimental evidence that indicates the inadequacy of pre-quantum physics. He concludes the lecture with a short discussion on Bell's inequality.

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

November 18, 2025
This lecture covers career advice and a guest speaker.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/

View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Guest Speaker
Laurence Moroney
Best-selling AI author and award-winning researcher

Andrew Ng
Founder of DeepLearning.AI
Adjunct Professor, Stanford University’s Computer Science Department

Kian Katanforoosh
CEO and Founder of Workera
Adjunct Lecturer, Stanford University’s Computer Science Department