Automating Research Tasks with AI | LLM-Augmented Research Workflows
Sup folks! In this video I share a presentation I did recently at the Open Data Science Conference in London regarding some interesting ways you automate research tasks (like academic and non-academic research) with Large Language Models using GPT-4o and GPT-4o-mini models from OpenAI as well as structured outputs with Pydantic to build what I call semantic data structures that I think in the future could represent interesting 'cognitive primitives' that would permeate an interface for effective human-LLM interfaces for knowledge work! I hope you like it! Cheers :)
📚 Chapters:
0:00 - Introd…
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Chapters (25)
Introduction to the presentation and the channel
0:39
Discussing LLM tangibles and UI patterns
1:11
Overview of using large language models in research
1:22
Origin of the concept of augmentation
2:14
Introduction to LLM tangibles
2:48
Demonstration of Elicit, a research assistant tool
4:52
Presentation about the UI pattern in Elicit
5:04
Discussing new interesting UI patterns with LLMs
5:24
Presentation by Amelia Wattenberger on semantic zooming
6:45
Demonstration of Luminate for idea exploration
9:20
Exploration of dimensions and tone in stories using Luminate
12:00
Discussion on Atomic usage of AI with granular functionalities
12:32
Overview of machine-assisted mixed methods in research
13:39
Application of AI in various research stages
14:29
Detailed Level 0: Prompts for enhancing research
17:02
System messages as utility functions
17:22
Examples of constructing an argument using system messages
19:35
Evaluation of evidence and hypothesis generation
25:02
Real-world example of keyword and literature review tasks
27:05
Exploring how attention mechanisms work
32:31
Detailed analysis of LLM Primitives
34:31
Inspecting evidence for hypothesis
39:42
Using agents for iterative research reports
41:17
GPT Researcher demonstration
45:41
Using LLMs directly in the terminal with Simon Willison's to
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