Epstein Secrets

1 The Hopfield neural net model 256 13.4.2 Knowledge Representation via Cell Assemblies 257 13.5 Neural Foundations of Learning 258 13.5.1 Hebbian Learning 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies 258 13.5.3 Neural Darwinism 259 13.6 Glocal Memory 260 13.6.1 A Semi-Fo

hics 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 Stages of Development of Empathic Ethics 214 12.4.3 An Integrative Approa

e our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

one way of doing this. In our near-term work with CogPrime, we are using simplistic approaches, with a view toward early-stage system testing. 12.4 Ethical Synergy An explicit goal system provides an explicit way to ensure that ethical principles (as represented in system goals) play a significant role in guid

ake our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

inciple, they have the flexibility to deal with complex ethical decisions, including not only weighted “for the greater HOUSE_OVERSIGHT_013128 12.4 Ethical Synergy 213 good” dichotomous decision making, but also the ability to develop moral decision networks which do not require that all situations be solved th