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Become a sponsor to Jens Egholm Pedersen

Motivation

When faced with the complexity and ambiguity in the real world, contemporary algorithms fail spectacularly. There is a strong need for robust, sparse, and massively parallel algorithms to solve our everyday physical problems. I strive to fill that need.

Goal

My approach focuses on understanding and simulating neural circuits that perform meaningful functions, including vision, motor control, and self-sustenance. The explicit goal is to build autonomous systems that perform meaningful work. Most robotic systems are staggeringly incompetent compared to even the simplest members of the animal kingdom. I approach this bottom-up, tightly following the Feynman axiom “What I cannot create, I do not understand”.

Why sponsor?

This sponsorship fuels my open-source efforts to build and sustain a community for brain-inspired modelling and neuromorphic development that is open and free for all. I co-authored and maintain the popular Spiking Neural Network library, Norse, the event streaming library AEStream, I contribute to the Open Neuromorphic community and are collaborating with neuromorphic research groups and companies across the globe.

Your sponsorship permits me to dedicate time to publicize, popularize, and democratize neuromorphic technology. Something I would otherwise be strongly disincentivized to do.

About me

I'm Danish by origin and value humility and integrity highly. I try to keep a sense of humor in everything I do. I am incredibly friendly and spend a little too much of my time helping out strangers.

My inbox is open if you have any questions.

Thank you! ❤️

@Jegp

This pays 1% of my salary and translates to 1h/week of community work for Norse and the neuromorphic community: replying to issues, helping users, improving documentation, and fixing bugs.

Featured work

  1. norse/norse

    Deep learning with spiking neural networks (SNNs) in PyTorch.

    Python 669
  2. aestream/aestream

    Efficient streaming of sparse event data supporting files, network I/O, GPU peripherals (via Torch/Jax/Numpy) and neuromorphic protocols

    C++ 69
  3. neuromorphs/NIR

    Neuromorphic Intermediate Representation reference implementation

    Jupyter Notebook 77
  4. open-neuromorphic/coding

    Coding projects by the community for the community

    Python 12

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"Thank you for creating Norse and for your continued efforts to the community!"

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"Thank you for your continued efforts for the community! I know how important it is to research intelligent systems and I trust you will do great work with the time you are given. So here: go create something excellent."