Gregor Schöner on DFT vs. DNN Transformers

A very informal talk about how DFT is positioned relative to the Deep Learning/Transformer work that is currently getting so much public attention. Some observers suggest that this recent work approaches the long-sought neural model of the human mind or even of a more general form of intelligence of which the human mind is an example. Some background on Deep Neural Networks and Transformers at a conceptual level is first given. This is followed by a discussion of what it may mean to have a neural theory of the mind and of the relevant properties of human (and animal) cognition that such a theory would need to address. DFT is proposed as a candidate for such a neural theory of the mind and some points of convergence and of divergence with DNN/Transformers are outline.