Neuromata
Project Neuromata will explore brain-inspired hardware for AGI, targeting the critical bottlenecks of recursive reasoning, probabilistic inference, attention mechanisms, and large-scale knowledge retrieval. We will survey and benchmark four non-von Neumann paradigms - temporal (race logic), asynchronous neuromorphic, analog in-memory computing, and processing-in-memory. Using Python simulations, FPGA prototypes, and remote neuromorphic boards over defined metrics such as latency, energy per operation, accuracy, scalability. Integrated with OpenCog Hyperon, Neuromata aims to demonstrate a proof-of-concept accelerator achieving 10x-50x speedups and 10x–100x energy savings on AGI workloads.
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