Indra's net reflects a connectome of cosmic proportions, both macrocosmic and microcosmic.https://twitter.com/NoaidiX/status/1209165934851584000?s=20 …
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"Self Reflected offers an unprecedented insight of the brain into itself, revealing through…reflective microetching the enormous scope of beautiful & delicately balanced neural choreographies designed to reflect what is occurring in our own minds as we observe this work of art."pic.twitter.com/dJb2uiJp0e
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"Thought is not arborescent, and the brain is not a rooted or ramified matter. What are wrongly called 'dendrites' do not assure the connection of neurons in a continuous fabric." Deleuze & Guattaripic.twitter.com/ODdyMosVP6
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Discontinuity between cells Axons Functioning of synapses Existence of synaptic microfissures Leap each message makes across these fissures Make the brain a multiplicity immersed in its plane of consistency or neuroglia—a whole uncertain, probabilistic system. Deleuze & Guattaripic.twitter.com/1Inf94cELz
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"Many people have a tree growing in their heads, but the brain itself is much more a grass than a tree. 'The axon and the dendrite twist around each other like bindweed around brambles, with synapses at each of the thorns.'" Deleuze & Guattaripic.twitter.com/R3ExuLQYK2
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"Its branches pierce the highest heaven; its roots reach through to the bowels of the earth. Above, the hanging moss reaches for a hundred feet; below, the fungus that grows only after the tree has lived a thousand years clings to the roots." Hakuin Ekakuhttps://twitter.com/NoaidiX/status/1254878677243883521?s=20 …
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Reminiscent of both Indra's net as well as Deleuze and Guattari's rhizome, neural networks consist of hidden layers whose function is to perform non-linear transformations on information from an input layer, yielding new information to be passed on to an output layer.pic.twitter.com/iawwqHC9Tx
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Each node in the net is an eyelet wherein information undergoes transformation via dream-like recursive cycles. https://twitter.com/NoaidiX/status/1258176137450016768?s=20 …pic.twitter.com/HwElmEyrpH
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Recursive neural networks are capable of remembering the past and parsing inputs in non-sequential fashion, transmitting information from input nodes by combining child nodes into parent nodes, which are further merged with other child/parent nodes in the net.pic.twitter.com/1AA8v7qXHf
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Metaphor. None of it is sentient. Just a model.
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