I recently had the opportunity to speak at The Commit Your Code Conference in Dallas.
The Commit Your Code Conference
The Commit Your Code Conference is one of a kind conference where 100% of proceeds go to FreeCodeCamp and St. Jude. Here’s the excerpt from their website.
100% of all ticket sales will be donated to charity.
The entire organizing team are donating their time and we will not be making a profit from the event. All Financial data will be published publicly so everyone can see where the money is going.
We will be donating the money to:
- FreeCodeCamp to keep tech accessible for all
- St. Jude to keep help saving lives.
And I volunteered my time to speak at the conference.
My Session
My session was titled Building Your Own AI Assistant with JavaScript, LLMs, and RAGs.
I had three objectives for the talk.
The first objective was to introduce the audience to how easy it is to build a personal AI assistant using Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) techniques.
As to why Javascipt and not Python, I just wanted to show that you don’t need to learn a new language to build your own AI assistant.
I struggled personally to understand the complexities of LLMs and RAGs. Hence the second objective. This session was also a way for me to help explain the core concepts and help demystify the topic. AI development is evolving at a rapid pace that it’s hard to keep up with the latest advancements. Honestly, I still don’t know what I don’t know, and I’m sure many feel the same way.
I’m at times overwhelmed by the amount of information available and the pace at which it’s changing.
And the third and final objective was a bit of a selfish nature. One of my core beliefs is this - The best ways to learn is by doing and the next best way is by teaching. So I wanted to challenge myself to speak at a conference and speak about a topic that I’m still learning about.
I’m linking the slides and the link to the repo for your reference.
Slides
Building Your Own AI Assistant with JavaScript, LLMs, and RAG
Session notes
These are the notes that I have written while preparing for the talk.
Repo
https://github.com/jerrymannel/poc-langchain
Reference Links
Tools
- Hugging Face - LLM models, embeddings, and datasets
- LangChain
- Llamaindex
- LM Studio
- Ollama
- Haystack
- CrewAI
- Aider
- ML5
Learning Resources
- Vector databases are so hot right now. WTF are they?
- A Gentle Introduction to Vector Databases
- How to Choose the Best Embedding Model for Your LLM Application
- List of Vector Stores
End credits
This post was prewritten and is scheduled to be published automatically on December 5, 2024 at 10:00 AM CST.
If you are seeing this, it means the post was published prematurely. Yikes! 😫
Update: 5th Dec 2024 - Yes, the scheduled post failed. I had to manually publish this.
./J