Hello OpenAI Community.
I’m an enthusiast fascinated by the potential of artificial intelligence, and I’ve been pondering a concept related to neural networks. I’d like to share my thoughts and get feedback from this knowledgeable community, even though I have no formal expertise in the field. Please bear with me as I try to articulate my idea.
I’ve been thinking about the traditional neural network model and wondered about the possibilities of using multidimensional neurons instead of conventional weights. My understanding is based on casual exploration and discussions with chatGPT.
Here are some Key points:
- Spatial Mapping: Considering the spatial arrangement of neurons.
- Transformer-Based Training: Exploring the role of a Transformer-based Trainer in guiding network creation.
- Adaptability: How can multidimensional neurons adapt to different problem domains?
I’d love to hear your thoughts, insights, and critiques regarding this concept.