Demonstrators
Experience interactive prototypes and real-world demonstrations that bring our innovations to life
Synthetic Biological Intelligence on Cortical Labs CL-1
The Cortical Labs CL-1 is a biohybrid computing system that integrates in-vitro grown neurons with silicon-based hardware, i.e., a multi-electrode array, to form a physical spiking neural network, known as synthetic biological intelligence. Therefore, the CL-1 allows real-time electrical interfacing between biological and digital components. The system enables the neurons to be trained by stimulation based on the free energy principle, such as playing the arcade game Pong. The CL-1 will be used in the gAIn project to explore synthetic biological intelligence algorithms and benchmark the system.
Security in presence of AI
This demonstrator showcases the integration of Physical Layer Security (PLS) in a real-time communication between a robot and a base station. By employing advanced techniques, we show secure data transmission while simultaneously enabling security against an eavesdropper, even in the era of AI.
SurgMentor – AI-based Surgical Skill Assessment
SurgMentor is a surgical training system that simulates laparoscopic procedures using a variety of sensor modalities to capture the actions of trainee physicians in a manner similar to real intraoperative manipulations. Advanced machine learning algorithms are used to analyze the collected sensor data. Our focus is on developing intelligent algorithms that automatically deliver constructive feedback and objective skill assessments to support the training of inexperienced medical personnel.
The Lunar Rocket Landing (The Analog Thing)
Step into the cockpit of the Apollo 11 Lunar Module and experience the tension of the first Moon landing. This interactive demo simulates the powered descent using an analog computer model of three differential equations. Control the descent engine throttle with a potentiometer, monitor altitude, velocity, and fuel, and aim for a gentle touchdown—just like Neil Armstrong and Buzz Aldrin in 1969. Can you land safely before the fuel runs out?
Neuronal Bursting with Hybrid Analog-Digital Computer
Explore how neurons process and transmit information through bursts of activity. This demo uses an analog-digital computer implementation of the Hindmarsh–Rose model (1984), a system of three differential equations capturing neuronal firing and ion transport across fast and slow channels. By adjusting inputs and parameters, you can observe how neurons integrate impulses, cross firing thresholds, and generate rhythmic bursting patterns—visualized in real time on the display system.