Epstein Secrets

artificial chemistry? Another problem with this approach, of course, is that it might take a really long time. Evolution took billions of years on Earth, using a massive amount of computational power. To make the evolutionary approach to AGI effective, one would need some radical innovations to the

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

inkers, such as Francis Heylighen, believe that engineering AGI systems is at best a peripheral endeavor in the development of novel intelligence on Earth, because the real story is the developing Global Brain Illey07, Goe0IJ — the composite, self-organizing informa- tion system comprising humans, comp

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

d artificial chemistry? Another problem with this approach, of course, is that it might take a really long time. Evolution took billions of years on Earth, using a massive amount of computational power. To make the evolutionary approach to AGI effective, one would need some radical innovations to the ev

3.4.2 Knowledge Representation via Cell Assemblies .................2.05- 257 13.5 Neural Foundations of Learning ..........0 0.000 ee eee 258 13.5.1 Hebbian Learning............ 0.0.00 eee ete eee 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies .......... 258 35:38 Netital DArwitiiSitt +2; case

hinkers, such as Francis Heylighen, believe that engineering AGI systems is at best a peripheral endeavor in the development of novel intelligence on Earth, because the real story is the developing Global Brain [Iley07, Goe01] — the composite, self-organizing informa- tion system comprising humans, compu

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