2025-12-05 — Initial project setup
Created the Neuromorphic Inference Lab project structure and the first public website to document future discoveries.
Vision
Neuromorphic Inference Lab is a long-term research initiative exploring how brain-inspired architectures and spiking neural networks (SNNs) can support autonomous agents that reason and act under uncertainty.
The project focuses on:
- Neuromorphic hardware and realistic simulators
- Probabilistic and active-inference–based algorithms
- Methods for using neuromorphic processors as first-class computational substrates for learning, prediction and decision-making
Research log
This section collects key insights, experiments, and references over time.
2025-12-05 — First notes on spiking neural networks
Reviewed basic neuron models and coding schemes (rate coding vs temporal coding) and planned initial experiments with SNN simulators.
High-level roadmap
- Phase 0 – Foundations: Build core understanding of SNNs, generative models, and active inference.
- Phase 1 – Simulated agents: Implement simple SNN-based agents in toy environments.
- Phase 2 – Active inference on SNNs: Prototype active-inference–style agents with spiking architectures.
- Phase 3 – Towards hardware: Explore deployment on neuromorphic platforms or realistic simulators.
- Phase 4 – Research outputs: Consolidate tools and experiments into research-grade artefacts.
Links
This site is a living research notebook. Expect it to evolve as new ideas, experiments, and references are added.