Explore the datasets and resources used by the Swiss AI Initiative for developing Apertus. While the model focuses on linguistic diversity, consider as a team how to truly meet the needs of global communities by enhancing specific cultural capabilities - accessing untapped datasets, or advocating for data contributions.

In this challenge, the search for partners will be simplified for users by means of a pre-matching algorithm running on Apertus. This algorithm generates three components that make dating easier:

1. Simulated conversation between the dating profiles of User A and User B
2. Benevolent short summary of this simulated conversation
3. Compatibility score from 1–10 by comparing both dating profiles

At AI Mates, before matching, only components 2 & 3 are visible instead of the full profiles.

Since the short summary is benevolent, it creates incentives for longer and more genuine content. Furthermore, small talk can be skipped more easily, as concrete topics become apparent.

The compatibility score provides an additional simplification and efficiency gain in the search. The challenge now is to develop a prototype based on the existing logic & designs.The core of this is the pre-matching algorithm, which reliably delivers the above components.

Supporting documentation

https://swissai.dribdat.cc/project/40

• Trello Board

• Apertus chat on design specs

• Wer hat den Fokus auch auf innere Werte? (PDF)

• What the AI Must Be Able To Do - Core Requirements (PDF)

• Build-ready specification for AI Mates (PDF)

• Product Requirement Document