Notebooks: Tools for LLMs

Lightning talk about Notebooks for LLMs at AI Dev Day, hosted by AICamp.

This talk shows how we integrated computational notebooks, specifically Jupyter, with Large Language Models (LLMs). This talk will explore how the Noteable Plugin has been designed to enable LLMs to write literate computational notebooks, allowing models to write prose, code, and plot. An unexpected discovery, once GPT models had access to notebooks, they unlocked the ability to debug and reason in a paired interactive computing environment. Through some live demos and videos, we will walk through doing data science with our LLM partner. We will also discuss the tradeoffs and risks associated with temporary and durable computation for chat models. This session aims to inspire the audience to explore the untapped potential of LLMs and notebooks in their data analysis tasks, paving the way for a future of collaborative analysis that includes not just human peers but also artificial intelligence.

Transcript

1. Kyle Kelley at AI Dev Day, July 25th, 2023 Notebooks: Tools for LLMs ⚡ Talk at AI Dev Day
2. I'm Kyle Kelley • Chief Architect at Noteable • IPython & Jupyter Developer • Previously Notebooks Platform at Net fl ix • Containers, DevOps, and UX Hi!
3. What are Notebooks Play Build Share
5. In[1] : import openai 
 import noteable
6. https://www.youtube.com/watch?v=Xd-VPCC_WKI&t=584s Choose your own adventure Video from I versus AI Live Demo!
7. Make literate computational documents Data Driven Documents
8. How?
9. Headless Execution From Scheduled Jobs to Realtime Notebooks • Original scheduled notebook jobs: • Interactive compute with realtime updates • Both interactive and batched
10. Headless Execution Close your tabs
12. Comparisons Noteable Plugin, OpenAI Code Interpreter, and Jupyter Extensions • Ephemeral compute: Fast to spin up • Durable Compute: access to data fi les, environment variables/secrets, and databases • In all cases, ability to debug, reason about outputs, and run code
13. From: Please use the IMDb Data Source with the `imdb` schema to determine which years had the most horror fi lms. To: Which years had the most horror fi lms?
14. Conclusion Untapped Potential of LLMs and Notebooks for Data Analysis • Longer form blog post of this talk:
 
 platform.noteable.io/blog/notebook-tools-for-llms • Augment Notebooks with app.noteable.io • Try the Plugin with ChatGPT Plus!