kyegomez / kyegomez/Algorithm-Of-Thoughts

Compare with GPT-4 Advanced Data Analysis (integrating with Python)

Open
#6 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
100
Forks
13
PR merge metrics
No merged PRs in 30d

Description

This wasn't tested in the original paper, but I've found GPT+4 with Python (Advanced Data Analysis) is often capable of solving these kinds of problems by writing a Python program that finds the solution in the search space:

Here, GPT wrote a Python program that tries all permutations of the expression (A^B)^(C^D), where "^" are one of the four basic arithmetic operators (+,-,*,/) and A, B, C, D are a permutation of the given numbers.

It then found the solution (14 - 8) * (8 / 2) = 24, which is correct. And this is in a relatively small number of tokens (input = 112 tokens, output = 512 + prompt for Advanced Data Analysis >= 624 tokens), whereas AoT would likely require far more (the openai.logs file in this repo, for instance, is 15 306 tokens).

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Review the linked GPT-4 Advanced Data Analysis transcript and the repository's openai.logs file first. Define a reproducible comparison or Python integration scope, since the issue does not identify target files or tests. Done would require an agreed implementation and a documented comparison against the existing Algorithm of Thoughts results.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.