How to Create a Mind: The Secret of Human Thought Revealed

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Efficient Natural Language Response Suggestion for Smart Reply (2017, background): “In a broader context, Kurzweil’s work outlines a path to create a simulation of the human neocortex (the outer layer of the brain where we do much of our thinking) by building a hierarchy of similarly structured components that encode increasingly abstract ideas as sequences [12].”
Deep learning in neural networks: An overview (2014, background): “More recently, well-known entrepreneurs (Hawkins and George, 2006; Kurzweil, 2012) also got interested in HTMs; compare also hierarchical HMMs (e.”
Contextual LSTM (CLSTM) models for Large scale NLP tasks (2016, result): “…of sentences, each sentence has sequences of phrases that are comprised of a sequence of words, etc. Capturing this hierarchical sequential structure in a language model (LM) [30] can potentially give the model more predictive accuracy, as we have seen in previous work [12, 13, 25, 33, 48].”
Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda (2015, background): “Kurzweil (2012) foresees machines outperforming the human brain in the context of many decision tasks in the not-too-distant future.”
My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013 (2013, background): “Recently, well-known entrepreneurs also got interested [43, 52] in such hierarchical temporal memories [81, 82] (TL 1.7).”