Page 331 - Artificial Intelligence in the Age of Neural Networks and Brain Computing

324 Index

Theory of brain and mind, 191. See also vector associative maps for spatial representation
Brain-mind-computer trichotomy; Unified and action, 40
mind-brain theory Unified theory of mind and brain. See Unified
early history of neural networks, 192e193 mind-brain theory
emergence of neural network principles, Unsupervised deep learning (UDL), 60, 63e64,
193e194 66, 127e128
neural networks entering mainstream science, Unsupervised learning (UL), 18, 221e222
194e195 with Adaline, 5e6
Thermodynamic equilibrium, 60e61 rule, 70e74
Third Gen AI, 56e70 Unsupervised LMS, 16
FMF and data basis, 67e70 Urgent Unmet Challenge, 184e187
inverse is convolution neural networks, 63e67 US National Highway Traffic Safety Administra-
MaxwelleBoltzmann homeostasis, 61e63 tion (NHTSA), 55e56
3D LAMINART model, 44 US National Science Foundation (NSF), 162
“Threshold Logic Unit” model, 169 vision of NSF COPN research initiative
Time-Lagged Recurrent Network (TLRN), (2008), 163f
172, 173f
TNF. See True negative fraction (TNF) V
TPF. See True positive fraction (TPF) Vector associative maps, 40
TPU. See Tensor Processing Units (TPU) Vertebrates, 99
Traffic Safety Administration (TSA), 57e58 evolution of vertebrate brains, 99f
Trainable neural network incorporating VLSI chip, 45
Hebbian-LMS learning, 27e29 Vocal tract, 101e102
Transductive weighted NFI (TWNFI), 119 Voltage/frequency scaling, 249e250
True negative fraction (TNF), 150 Volume conduction effect, 226e227
True positive fraction (TPF), 150
TSA. See Traffic Safety Administration (TSA) W
“Turk” chess machine, 205e206
WCCI. See World Congress in Computational
TWNFI. See Transductive weighted NFI (TWNFI) Intelligence (WCCI)
2D pole-balancing problem, 285e286
Wearable personal assistants, 105e108
Werbos’ backpropagation, 208e210
U Wide Sense Analyticity, 65
UCI Machine Learning Repository, 21 Wide Sense Causality, 65
UDL. See Unsupervised deep learning (UDL) Wide Sense-Spatial Average (WSSA), 62
UL. See Unsupervised learning (UL) Wide Sense-Temporal Average (WSTA), 62
Unbalanced data, 256 Wide-Sense Ergodicity Principle (WSEP), 61, 66,
Unified mind-brain theory, 32e33, 45, 191. 69e70
See also Brain-mind-computer trichotomy Wiener’s cybernetics, 208e210
adaptive resonance theory, 37e40 Working memory, 284
autonomous adaptive intelligent agents and clin- World Congress in Computational Intelligence
ical therapies, 48e49 (WCCI), 162
conscious states, 46 WSEP. See Wide-Sense Ergodicity Principle
cortical streams, 36e37 (WSEP)
equations, modules, and architectures, 45e46 WSSA. See Wide Sense-Spatial Average
homologous laminar cortical circuits, 40e45 (WSSA)
resonance trigger consciousness, 47 WSTA. See Wide Sense-Temporal Average
revolutionary brain paradigms, 35 (WSTA)
theoretical method for linking brain to mind,
33e34 X
varieties of brain resonances and conscious
XAI. See Explainable AI (XAI)
experiences, 46e47