Mukhamed Satybaev
System Architect | Founder of ARA
Building adaptive AI systems beyond neural networks
I am a system architect and founder working on alternative AI architectures.
My work focuses on signal-based adaptive systems that learn, predict, and evolve through internal structure — without neural networks, datasets, or retraining loops.
Currently building ARA and STB-DEMO — a working prototype that demonstrates error-driven adaptation, prediction, and long-lived intelligence.
- Signal-based AI architectures (STB — Signal Theory of Being)
- Adaptive systems and prediction without inference pipelines
- Error-driven learning and structural self-modification
- Long-lived autonomous AI systems
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STB-DEMO
A working prototype demonstrating signal-based learning, prediction, structural adaptation, competition of hypotheses, and forgetting — without datasets or retraining. -
ARA
A long-lived personal AI architecture built on STB principles, designed as a continuous adaptive system rather than a static model.
I explore how intelligence can emerge from reactive signal structures, inspired by neurobiology, physics, and distributed systems.
The goal is to build AI as a controllable, economically viable system, not as a static model or API-based service.
Email: s.m.kamilovich@gmail.com
Location: Bishkek, Kyrgyzstan