SynSense is a Nueromorphic startup founded in 2018 with offices in Zurich and China. We have two family of SNN processors: Xylo for low dimensional signal processing and Speck for vision processing. Both HWs come with open source and user friendly python-based librarys: Rockpool and sinabs that have been co …
Event-based learning of delays in SNNs
In a collaboration between Melika Payvand's EIS Lab and Mihai Petrovici's NeuroTMA group, we've been developing a fully event-driven training algorithm for learning delays and weights in SNNs. In the established Fast&Deep algorithm, spike times are treated as the quantity central for information propagation. …
The ability for learning models to be deployed in new and challenging conditions is a long-standing aspiration of modern AI. Models computing at the edge should be capable of both adaptation and knowledge-transfer, leveraging extensive (offline) pre-training while remaining nimble and avoiding catastrophic forgetting.
In this workshop we …
The goal of this workshop is to investigate how to make the best use of the unique properties of neuromorphic processing solutions to enable natural interactions with social humanoid robots. We would like to collaborate with workshop participants in order to find the most suitable applications for neuromorphic substrate to …
We have a fully implemented baseline pipeline for Human Pose Estimation with Event Cameras in Real time that, then, feeds into a full body Fruit Ninja application. The system is ANN based and implemented modularly. A webpage will be made available shortly. If you would like to try seeing …
How can robots continually learn in complex environments from limited amounts of data, both with and without supervision, similar to the way animals learn?
At Intel Neuromorphic Computing Lab, we have been developing the Continually Learning Prototypes (CLP) algorithm and its Loihi implementation to address this question [1,2]. We investigate …
We bring along multiple BrainScales-2 systems and invite everyone to try some of our demos or implement their own neuromorphic experiments.
The most recent generation of BrainScaleS-2 ASICs features 512 analog multi-compartment neuron circuits with 256 plastic synapses each.
The analog circuits are tightly coupled to on-chip digital event routing …
This workgroup is about robotics with accelerated neuromorphic hardware. In particular, we will provide multiple BrainScaleS-2 systems that feature emulated neurons with dynamics 1000 times faster than those found in biology.
All systems are equipped with multiple digital and analog real-time interfaces for robotic applications. We can inject and extract …
In this workgroup we will investigate the computational capabilities of DYNAP-SE heterogeneous neurons for compressing time series data. Our focus is on exploring how these neurons can efficiently compress both periodic and aperiodic signals using few spikes per neuron, enabling low-latency pattern detection. We will optimize the DYNAP-SE neuromorphic chip …
Fancy running your SNNs 10x faster? Our GPU enhanced Neuronal Networks (GeNN) library is freely available from https://genn-team.github.io/ and provides an environment for GPU accelerated spiking neural network simulations. GeNN is capable of simulating large spiking neural network (SNN) models at competitive speeds on commodity and even embedded GPUs. In …
Humans and animals seamlessly control their complex bodies, use new tools, and adapt to injuries.
A highly adaptive body model of some sort (body schema/body image, forward and inverse models, etc.) seems indispensable.
Using the Mujoco simulator we simulate infant-like full-body tactile agents such as iCub and MIMo environment. We …
We will bring a Neuromorphic Drummer to Capo Caccia and launch a neuromorphic drumming control problem, as a low-cost and reproducible toy model for neuromorphic locomotion control.
The problem consists in controlling the tempo and velocity of swinging pendulum + drum-pad system through a fully neuromorphic sensing-control-acting sensori-motor loop.
The …
Tutorials on available hardware, software, resources....
The physical implementation of today's technologies (very much including neuromorphic electronics) depends almost entirely on external (to the instantiated object) factories. By contrast, biological systems construct, repair, and evolve, themselves.
This discussion will consider issues such as:
This is a 'fession session' open discussion - whose aim is share experience with the workshop.
No presentations, no company pitches. Just the lessons learned, for good and/or for bad.
Exact company affiiliations may (for reasons of NDAs) need to remain anonymous - this is a discussant's choice.
Walking meditation is an old meditative practice in which one focuses all their attention on the act of walking at extremely slow paces.
This simple practice can make us discover and become aware of the mechanisms that make us move in a direct, experential way.
Besides its recreational value, walking …
Meet your fellow partiipants