Research projects and other activities
ArNI – Artificial NeuroIntelligence
Project Goal
The ArNI project is aimed at development of the wide range of AI technologies based on spiking neural networks (SNN) – the most biologically plausible models of artificial neural networks. It includes several goals:
- Development of the SNN theory – methods for analysis and prognosis of SNN behavior, their learning (especially – reinforcement learning), implementation of various memory mechanisms in SNNs, creation of standard neural structures for SNN solving typical problems, optimization of network hyperparameters.
- Development of neuroprocessor architectures for simulation of large SNNs, creation of algorithmic foundations for practical tasks from robotics, intelligent sensors, IoT, security etc.
- Development of methodology for creation of very large SNNs targeted at building the intelligent systems comparable with the human intelligence or outclassing it, simulating human brain’s cognitive functions, creation of a constructive theory of higher mental functions.
The project content.
The project is based on computer simulation of large SNNs.
The current stage of the project includes the following tasks:
- Development of the ArNI-X SNN simulator for CPU and GPU.
- Design of novel models of spiking neurons and synaptic plasticity optimized for various classes of problems.
- Design of novel SNN learning algorithms (unsupervised learning, supervised learning, reinforcement learning).
- Study of memory mechanism of various levels in SNNs.
- Development of algorithms for SNN hyperparameter optimization.
- Analysis of efficiency of the SNN models developed from point of view of implementing them on existing and future neurochips (Loihi, AltAI). Creation of hardware-friendly models of neurons. Determination of functional specifications for neuroprocessors for implementing the necessary SNN features.
- Determination of practical application areas where usage of software/hardware SNN simulators would be most efficient.
Membership in research communities
I am a Principal Investigator in the Intel Neuromorphic Research Community (INRC). I am a member of the Russian Neural Network Society, and of Program Comittees of several conferences on neural networks (IJCNN, NEUROINFORMATICS).