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Imagine a group of experts spend an entire hour brainstorming with AI on your own

dataset.

# Introduction

  tests, CI, security aspects, visualisations plotting, workflow engines to run models

  in a dependency graph and about semantics how we name variables and functions .

- Topics could also be extended to literature research with LLMs that ground their

  answers in existing literature such as Perplexity and to prompting techniques to avoid

  sycophancy (such as grill-me, expert panel, storm review, hostile review).

- The groups goals could be for example:

    - to create new data visualisations using parallel coding agents in the creative

      process.

    - to translate new research questions into [back of the envelope

      calculations](https://en.wikipedia.org/wiki/Back-of-the-envelope_calculation).

      From these questions, we can brainstorm about the implication for model modification

      or model linking.

    - To perform literature research with LLMs that ground their answers in existing

      literature such as Perplexity. To use context engineering (uploading relevant

      literature) and prompting techniques to avoid sycophancy (such as grill-me, expert

      panel, storm review, hostile review).

# Next Meetings:

# Participate in the hands on training camp

To participate

To participate preferably come with an open dataset already shared on Zenodo or Figshare

or a similar open platform. If you cannot share your data, then find a similar dataset

from the literature on which we can work on together so that the learning can be

transferable to your own data later on.

- Submit your sample dataset in a new issue also called a work item at:

  https://aidaho-edu.uni-hohenheim.de/gitlab/modellierung/modellierung_fitnessclub/-/work_items