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Recently, a team of researchers from MIT, Institute of Science and Technology Austria (IST Austria) and Technische Universität Wien (TU Wien) developed an AI system by combining brain-inspired neural computation principles and scalable deep learning architectures. The AI system is basically a brain-inspired intelligent agent that learns to control an autonomous vehicle directly from its camera inputs. The researchers discovered that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. One of the interesting facts of this research is that the AI agent is inspired by the neural computations known to happen in biological brains in order to achieve a remarkable degree of controllability. They took the inspiration from animals as small as the roundworms.