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add ChatGPT data analysis tool notes
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jglazar committed Dec 2, 2023
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Expand Up @@ -137,3 +137,54 @@ Tail generation reminds the LLM of previously established rules
Semantic filters removes/retains info in original text
* E.g., remove all dates and condense this text

# ChatGPT data analysis

Advanced data analysis tool (formerly Code Interpreter, hereafter ADAT)
can read documents and summarize using statistics and graphs

Can start with just data, and iterate through visualization, analysis,
explanations, and extensions
* E.g., upload recipe to create grocery list, estimate calories/macros, ...

Have ADAT ask you questions about your goals

ADAT has no internet access and limited toolkit. Has short memory and needs
everything specified in single conversation
* Break projects into chunks and provide feedback

Can treat documents as objects (to be acted upon) or knowledge (to be
analyzed and interpreted)
* ADAT will handle interpretation tasks. Will generate Python for others

ADAT can solve rule-heavy tasks ChatGPT would fail, like Wordle
* ChatGPT can even hallucinate new data

ADAT can read document, identify missing details and re-read, break down
questions contained within, follow instructions within, and explore
hypotheticals

ADAT can figure out data structure, verify consistency

Can analyze media like videos, audio, and images
* Find and display specific video frames, resize and transform images, create
gifs, create powerpoints, generate metadata

Pipelines offer straightforward ways to accomplish complex tasks
* E.g., turn video into blog post by loading transcript, identifying tone and
concepts, drafting post outline, and filling in and polishing
* Can iterate through plan ideas

Split large documents into chunks. Can implement a search method

Handle large outputs step-by-step. Save and combine incremental outputs

10 best practices
* Save intermediate files to prevent loss of progress
* Plan step-by-step to enhance repeatability
* Use mementos where ADAT lists out the plan, current step, and progress
* Have ADAT read and explain all documents and data in several ways
* Implement error detection to prevent hallucinations going unnoticed
* Have ADAT try alternate approaches
* Be explicit about goals, requirements, and constraints
* Edit the conversation when errors occur to avoid error propagation
* Tell ADAT to analyze without Python when needed

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