Hello everyone,
For a year now, I have been sharing the progress of my work on this forum: moving artificial intelligence from a stochastic binary model (B_2, algebraic and probabilistic) to a deterministic geometric approach (B_4, Base 4).
Today, the concept is stabilized and is beginning to be integrated into cutting-edge applications (such as plasma modeling in fusion or biocomposite engineering).
But the most concrete point for the general public is the direct impact on everyday models: the removal of stochastic noise, the end of hallucinations, and the transition to a deterministic and energy-efficient operation.
To explain this transition in a simple and accessible way for everyone, I have condensed the essentials into a 5-minute video based on visual analogies:
🎬 Watch the video on YouTube:
🚂 What if AI took the wrong track? (🚄 The Base 4 revolution):
📄 For those who wish to consult the official repositories and kernels:
https://doi.org/10.5281/zenodo.19385043
I am curious to hear your feedback and discuss it with you here!
Sincerely,
Yannick