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Prof. Ido Kanter
From theoretical Physics to experimental Neuroscience: The new neuron and new type of learning
Can Physics assist with key challenges in Neuroscience and Artificial Intelligence? Let us swim against the stream when scientific evidence tells you something is wrong.
Century-old assumptions regarding neurons and brain learning are disproved. We present several types of experiments, indicating that each neuron functions as a collection of independent threshold units, where the neuron is anisotropically activated. In addition, experimental and theoretical results reveal a new underlying non-local mechanism for the fast brain learning process, dendritic learning, as opposed to learning which is based solely on slow synaptic plasticity. We demonstrate that a single neuron can realize deep learning algorithms and propose efficient shallow learning as an alternative to deep learning. Though the brain is a very slow machine, its capabilities exceed typical state-of-the-art ultrafast artificial intelligence algorithms; hence, a revolution in deep learning must emerge.
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