Epstein Secrets

11.4.4 The Reflexive Stage 202 EFTA00623772 Contents xvii 12 The Engineering and Development of Ethics 205 12.1 Introduction 205 12.2 Review of Current Thinking on the Risks of AGI 206 12.3 The Value of an Explicit Goal System 209 12.4 Ethical Synergy 210 12.4.1 Stages of Development of Declarative Ethics 211 12.4.2 S

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

receives. It's a very complex matter that is richly intermixed with all the other aspects of intelligence, and here we will treat it as such. 12.2 Review of Current Thinking on the Risks of AGI Before proceeding to outline our own perspective on AGI ethics in the context of CogPrime, we will review the main existing strains of thought on t

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

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..........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 receives. It’s a very complex matter that is richly intermixed with all the other aspects of intelligence, and here we will treat it as such. 12.2 Review of Current Thinking on the Risks of AGI Before proceeding to outline our own perspective on AGI ethics in the context of CogPrime, we will review the main existing strains of thought on th

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