Hello, I am Eunkyum Kim (Concode), the creator of Versor.
With the release of version 1.0.0, I would like to share the story behind this project, my current journey, and an open invitation to the global research community.
1. Intuition-Driven Foundation & Call for Experts
As a 17-year-old independent researcher, I built Versor largely guided by geometric intuition. While I have strived for mathematical rigor, I recognize there may be areas that lack formal refinement or rely on unconventional logic.
This is why I am calling upon experts in Mathematics and Deep Learning. The challenges listed in docs/milestone.md are merely my own starting points; I welcome any insights, corrections, or contributions that make Versor more robust and innovative. I am here to learn from the community.
2. Radical Intuition in 'Experiments'
If you wish to explore the core philosophy, please look into the experiments/ folder. Projects like dbg_lorentz or dbg_yang_mills originated from my pure mathematical curiosity. I believe that translating radical ideas into code is how breakthroughs begin. Please feel free to share your own "explosive" intuitions or unexpected use cases where you've applied Versor.
3. Beyond Proof of Concept
The four main tasks—SR, MD17, LQA, and DEAP—serve as a Proof of Concept (PoC) for Geometric Algebra Deep Learning. Each task still has immense room for parameter tuning and logical refinement. I hope the community will engage in active discussion so we can push these architectures to their absolute limits together.
4. Personal Journey: A Season of Quiet Growth
I chose to step away from traditional high school early to dedicate my time and energy entirely to computer science and the development of this framework. I have spent the last several months completely immersed in Clifford Algebra and deep learning architectures.
Now, I am preparing for university admission. My goal is not just a degree, but to find a rigorous academic environment where I can learn from brilliant peers and mentors to further expand my horizons.
Consequently, Versor will enter a Stabilization Phase for a few months. During this period, I will focus on maintaining the core’s integrity and exploring minor experimental updates rather than aggressive feature development. I believe this phase of "quiet growth" will prepare both me and Versor for a much larger leap in the future.
5. Collaboration & Support
I am constantly learning and looking to grow this project alongside the broader scientific community. I would be honored to discuss research proposals, academic pathways, or potential collaborations.
General Discussions: For questions or technical ideas, please use GitHub Issues or Discussions.
Professional Inquiries: For institutional reach-outs, academic opportunities, or private discussions, please email me at: nemonanconcode@gmail.com
Grants & Sponsorship: Advancing an independent research project of this scale is challenging. If you find value in Versor, any form of sponsorship to help cover computational resources is deeply appreciated and directly fuels the sustainability of this research.
Hello, I am Eunkyum Kim (Concode), the creator of Versor.
With the release of version 1.0.0, I would like to share the story behind this project, my current journey, and an open invitation to the global research community.
1. Intuition-Driven Foundation & Call for Experts
As a 17-year-old independent researcher, I built Versor largely guided by geometric intuition. While I have strived for mathematical rigor, I recognize there may be areas that lack formal refinement or rely on unconventional logic.
This is why I am calling upon experts in Mathematics and Deep Learning. The challenges listed in docs/milestone.md are merely my own starting points; I welcome any insights, corrections, or contributions that make Versor more robust and innovative. I am here to learn from the community.
2. Radical Intuition in 'Experiments'
If you wish to explore the core philosophy, please look into the experiments/ folder. Projects like dbg_lorentz or dbg_yang_mills originated from my pure mathematical curiosity. I believe that translating radical ideas into code is how breakthroughs begin. Please feel free to share your own "explosive" intuitions or unexpected use cases where you've applied Versor.
3. Beyond Proof of Concept
The four main tasks—SR, MD17, LQA, and DEAP—serve as a Proof of Concept (PoC) for Geometric Algebra Deep Learning. Each task still has immense room for parameter tuning and logical refinement. I hope the community will engage in active discussion so we can push these architectures to their absolute limits together.
4. Personal Journey: A Season of Quiet Growth
I chose to step away from traditional high school early to dedicate my time and energy entirely to computer science and the development of this framework. I have spent the last several months completely immersed in Clifford Algebra and deep learning architectures.
Now, I am preparing for university admission. My goal is not just a degree, but to find a rigorous academic environment where I can learn from brilliant peers and mentors to further expand my horizons.
Consequently, Versor will enter a Stabilization Phase for a few months. During this period, I will focus on maintaining the core’s integrity and exploring minor experimental updates rather than aggressive feature development. I believe this phase of "quiet growth" will prepare both me and Versor for a much larger leap in the future.
5. Collaboration & Support
I am constantly learning and looking to grow this project alongside the broader scientific community. I would be honored to discuss research proposals, academic pathways, or potential collaborations.
General Discussions: For questions or technical ideas, please use GitHub Issues or Discussions.
Professional Inquiries: For institutional reach-outs, academic opportunities, or private discussions, please email me at: nemonanconcode@gmail.com
Grants & Sponsorship: Advancing an independent research project of this scale is challenging. If you find value in Versor, any form of sponsorship to help cover computational resources is deeply appreciated and directly fuels the sustainability of this research.