Epstein Secrets

p learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel EARC09] and Jeff Hawkins 11113061. The integrative diagram adopts this as the basic model of the perception and action subsystems of human intelligence. Language understand

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

ch actions will help it achieve its goals.” HOUSE_OVERSIGHT_012925 10 1 Introduction This ties in with the ideas of many other thinkers, including Jeff Hawkins’ “memory/ predic- tion” theory [B06], and it also speaks directly to the formal characterization of intelligence presented in Chapter 7: general inte

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

ep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel [ARC09] and Jeff Hawkins [HB06]. The integrative diagram adopts this as the basic model of the perception and action subsystems of human intelligence. Language understanding

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