In this episode, we discuss LLMs, how everything started, how they work, and how to use frameworks such as LangChain to develop intelligent applications with them.

Guests

Taha Bouhsine

Sifeddine Nahhas

Nouamane Tazi

Notes

0:00:00 - Introduction and welcoming

0:05:33 - History of LLMs

0:12:00 - The role of transformers in LLMs

0:21:00 - How LLMs differ from other AI methods

0:26:00 - Emergent Abilities of Large Language Models

0:42:00 - HaggingFace and the role or open-source in LLMs

0:47:00 - Open source LLMs.

1:04:00 - Using LLMs to build smart apps.

1:39:00 - Advices for software engineers with no AI background to start with LLMs.

1:46:00 - Conclusion and goodbye.

Links

• The Illustrated Transformer

• Transformers

• The Annotated Transformer

• State of GPT

• Sparks of AGI

• MiniGPT-4

• H2O LLM Studio

• HuggingFace

• GPT4All

• llama

• LangChain

• Embracing AI-Powered Applications: A Developer’s Journey with LangChain

• OpenAI cookbook

• Jailbreak Chat

• MathsMaroc

• Prompt Engineering

• Emergent Abilities of Large Language Models

Prepared and Presented by

• Youssouf EL Azizi