# K"unstliche Intelligenz, quo vadis?

arXiv: https://arxiv.org/abs/2104.11067 · HTML: https://mlsanity.com/paper/2104.11067/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 13 references that are in the map.
- First posted on arXiv 21 Apr 2021.

## Builds on (most cited first, 3 of 3)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation](https://mlsanity.com/paper/2101.11718/) (2021)
- [A Review of Winograd Schema Challenge Datasets and Approaches](https://mlsanity.com/paper/2004.13831/) (2020)

## Abstract (arXiv)

This paper outlines the state of the art in AI. It then describes basic machine learning and knowledge processing techniques. Based on this, some possibilities and limitations of future AI developments are discussed.