Epstein Secrets

spatiotemporally hier- archical deep learning system is an effective way to handle representation and learning of low-level sensorimotor knowledge. DeSTIN is one example of a deep learning system of this nature that can be effective in this context. i. One effective way to handle goals is to represent

Objects, Natural Units and Natural Kinds 167 9.4.2 Events, Processes and Causality 168 9.4.3 Stuffs, States of Matter, Qualities 168 9.4.4 Surfaces, Limits, Boundaries, Media 168 9.4.5 What Kind of Physics Is Needed to Foster Human-like Intelligence? 169 9.5 Folk Psychology 170 9.5.1 Motivation, Requiredn

c, cognitive and linguistic functions. We will achieve this via the creation and real-time utilization of links between the nodes in CogPrime's and DeSTIN's internal networks (a topic to be explored in more depth Inter in this chapter). 6.4 Memory Types and Associated Cognitive Processes in CogPrime

ness, graininess, stickiness, runniness, etc. 4. Distinguishing degrees of elasticity and fragility 5. Assessing separability of aggregates 9.4.4 Surfaces, Limits, Boundaries, Media Gibson IGit)77, Gil)791 has argued that naive physics is not mainly about objects but rather mainly about surfaces. Surfaces have a variety

a spatiotemporally hier- archical deep learning system is an effective way to handle representation and learning of low-level sensorimotor knowledge. DeSTIN is one example of a deep learning system of this nature that can be effective in this context. i. One effective way to handle goals is to represent

vents, Processes and Causality ........... 00... c cece ee eee 168 9.4.3 Stuffs, States of Matter, Qualities....... 0... 0. eee eee eee eee 168 9.4.4 Surfaces, Limits, Boundaries, Media .......... 0.0.0.0 cece eee eee eee 168 9.4.5 What Kind of Physics Is Needed to Foster Human-like Intelligence?..... 169 9.5 Folk Psychology

ric, cognitive and linguistic functions. We will achieve this via the creation and real-time utilization of links between the nodes in CogPrime’s and DeSTIN’s internal networks (a topic to be explored in more depth later in this chapter). 6.4 Memory Types and Associated Cognitive Processes in CogPrime N

hness, graininess, stickiness, runniness, etc. 4, Distinguishing degrees of elasticity and fragility 5. Assessing separability of aggregates 9.4.4 Surfaces, Limits, Boundaries, Media Gibson [Gib77, Gib79] has argued that naive physics is not mainly about objects but rather mainly about surfaces. Surfaces have a variety of