Epstein Secrets

Schmidhuber, Marcus Rutter, Kai-Uwe Kuehnberger, Stephen Reed, Blerim Enruli, Kristinn Thorisson, Joscha B

re Nodes 254 13.3.7 Links for Special External Data Types 254 13.3.8 Truth Values and Attention Values 255 13.4 Knowledge Representation via Attractor Neural Networks 256 EFTA00623773 xviii Contents 13.4.1 The Hopfield neural net model 256 13.4.2 Knowledge Representation via Cell Assemblies 257 13.5

, and suggested answers to each of them ISot III. Stephen Omohundro 1Omo081 has argued that any advanced A

ruth values, allowing logical semantics. EFTA00624031 256 13 Local, Global and Global Knowledge Representation 13.4 Knowledge Representation via Attractor Neural Networks Now we turn to global, implicit knowledge representation — beginning with formal neural net models, briefly discussing the brain, and then turning

Schmidhuber, Marcus Hutter, Kai-Uwe Kuehnberger, Stephen Reed, Blerim Enruli, Kristinn Thorisson, Joscha B

..........0 002.00 eee eee eee 254 13.3.8 Truth Values and Attention Values ........... 0.00.00 eee eee eee eee 255 13.4 Knowledge Representation via Attractor Neural Networks ................... 256 HOUSE_OVERSIGHT_012913 xviii Contents 13.4.1 The Hopfield neural net model ..............0..0 022 e eee 256 13.4.2 Knowled

t, and suggested answers to each of them [Sot11]. Stephen Omohundro [Omo08] has argued that any advanced AI

ues, allowing logical semantics. HOUSE_OVERSIGHT_013171 256 13 Local, Global and Glocal Knowledge Representation 13.4 Knowledge Representation via Attractor Neural Networks Now we turn to global, implicit knowledge representation — beginning with formal neural net models, briefly discussing the brain, and then turning b