Title:
Open Collaboration Proposal: Developing a Developmental AI Model Inspired by Human Cognitive Growth
The Idea:
I’m initiating an open collaboration to build a prototype of a developmental AI system—one that learns and evolves more like a human child than a statistical machine.
Instead of relying on massive datasets and static pattern recognition, the model would:
Start with a small set of basic cognitive principles (like instinct-level rules).
Use “idea generators” to simulate thought experiments or possibilities.
Employ a probabilistic decision engine to evaluate and evolve its understanding over time.
The goal: Simulate real, internalized learning—from instinct to reasoning.
Why This Matters:
Most modern AI systems are impressive in performance but lack internal growth or developmental learning.
I propose a new track: Start from almost nothing—just the mental “instincts”—and build up through interaction, simulation, and trial-and-error understanding. Not imitation, but true cognitive emergence.
What I’m Looking For:
I’m seeking collaborators who are:
Interested in AGI, developmental learning, or cognitive modeling.
Capable of helping build a small experimental system (even in Python).
Open to creative, theory-driven exploration outside mainstream deep learning.
This is open-source in spirit. I’m not representing a company or institution. Just a strong conceptual foundation that deserves a real experiment.
Who I Am:
I’m an independent thinker passionate about the intersection of AI, cognitive development, and philosophy of mind.
I’m looking for researchers, developers, or research mentors who believe in long-term thinking and are curious about building AI that learns from within.
Contact:
[email protected]
Starter Question:
Do you believe an AI could develop internal understanding starting from simple principles and self-generated ideas?
What would the very first prototype of that look like?