## Goal of the Competition

More than a hundred AI papers are published every day, making it exceedingly hard to keep up with current innovations. The goal of this competition is to tap into the diverse expertise of the Kaggle community to centralize and summarize the rapid advancements in AI from the past two years. The Kaggle community has a breadth and depth of AI experience which extends beyond the reach of any single individual or research group. We aim to share your collective perspective with the broader research community.

## Context

In this analytics competition, participants will write an essay on one of the following seven topics, with a prompt to describe what the community has learned over the past 2 years of working and experimenting with:

  - **Text data**
  - **Image and/or video data**
  - **Tabular and/or time series data**
  - **Kaggle Competitions**
  - **Generative AI**
  - **AI ethics**
  - **Other** (anything that does not fall into any other category)

Kaggle has provided a collection of [writeups](https://www.kaggle.com/code/paultimothymooney/every-kaggle-competition-solution-writeup-to-csv/output) and a collection of [scholarly articles](https://www.kaggle.com/datasets/Cornell-University/arxiv) in the official competition dataset, but participants are free to use any resources. Participants will also take part in a peer feedback process that involves reviewing three peer essays, and your  submission will be assessed by an expert grading panel of seven Kaggle Grandmasters.  Winning essays will be aggregated in a post-competition publication and given authorship credit.

In response to demand and feedback from prior analytics competitions, this competition also pilots a format in which all eligible participants will be ranked on the leaderboard and awarded points based on their performance. Results will show on your profile, just as in a standard competition. 

See the [submission instructions](https://www.kaggle.com/competitions/2023-kaggle-ai-report/overview/submission-instructions) and [evaluation](https://www.kaggle.com/competitions/2023-kaggle-ai-report/overview/evaluation) pages for more detail.

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