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This lecture introduces NEMO, a neural model with recurrently connected brain areas and plastic synapses. It explores the concept of assemblies of neurons, their behaviors, and the role of long-range interneurons in brain computation. The lecture also delves into NEMO's software-implemented neuromorphic computation, including a parser of English sentences using spiking neurons. Furthermore, it discusses biologically plausible language acquisition experiments, testing the device's ability to learn and generate language. The presentation concludes by comparing artificial intelligence with brain capabilities and posing questions about the future of neuromorphic intelligent systems.