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This section showcases practical implementations of AI technologies, demonstrating real-world applications and capabilities across various domains.

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Available Demonstrators

Sports Analytics

Computer vision applications for sports analysis, including player detection, tracking, and identification.

Language Agents

Knowledge graph-powered AI tutor using GraphRAG for educational content with prerequisite scaffolding and semantic relationships.

Computer Using Agents

AI-powered system for understanding visual content through natural language and screen sharing with vision-language models.

Human Robot Interaction

Intelligent AI agents for real-time robot interaction, semantic navigation, and autonomous mission execution using ReAct principles.

Reasoning Agent for Manipulation

A VLA model that follows natural audio instructions to pick, reason about placement, and shelve objects while avoiding collisions.

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Purpose

These demonstrators serve multiple purposes:
  • Educational: Learn how AI techniques are applied to real-world problems
  • Practical: See working implementations with code and results
  • Interactive: Run notebooks in Google Colab to experiment yourself
  • Reference: Use as templates for your own projects
Each demonstrator includes:
  • Complete implementation code
  • Visual outputs and results
  • Interactive Colab notebooks
  • Technical documentation
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