A Whole New World [DEMO #4]


Formal Metadata

A Whole New World [DEMO #4]
Title of Series
Number of Parts
Surpur, Chetan
Cui, Yuiwei
CC Attribution 3.0 Unported:
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Numenta Platform for Intelligent Computing (NuPIC)
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Subject Area
A demonstration of sensorimotor inference in simple robotics.
Computer programming Building Group action Game controller Robot Distance Disk read-and-write head Mereology Perspective (visual) Theory Chaining Utility software Representation (politics) Form (programming) Area Standard deviation Information Machine vision Bit Prediction Set (mathematics) Testgröße Demoscene Word Logic Personal digital assistant Universe (mathematics) Vertex (graph theory) Configuration space Object (grammar) Quicksort Reading (process)
Point (geometry) Group action Interior (topology) Multiplication sign Scientific modelling Sampling (statistics) Object (grammar) Client (computing) 2 (number)
View (database) Cellular automaton Universe (mathematics) Combinational logic Representation (politics) Stability theory Form (programming) Number
State observer Focus (optics) State of matter 1 (number) Weight Library catalog Prediction Mereology Disk read-and-write head Maxima and minima Summation Word Large eddy simulation Noise Hydraulic motor Representation (politics) Hill differential equation Right angle Addressing mode Library (computing) Stability theory
Medical imaging Word Multiplication sign Lemma (mathematics) Demo (music) Coma Berenices Representation theory Stability theory
the area of a reader of upset some text test statistics because the it in the US in this book that he is in the middle of the building and the user's utilities and in so I'll show you a little robots based on so this is actually the 1st the 1st experiment do you want think and has and this the set is very similar to how small around here and I ask this is taking the standard features of objects actually each of us find it will have to pay for it so that it also had a motor on the back of the head of the department that you have high quality programming to randomly sampled from the start of the considerable distances people and that and then you can get some information about the layout of the world and if you also if you change the spatial configuration of the 1 that I can say think of this is a new which of to act as a little bit of theory and we show you that you can understand what's going on what we're doing is taking taking this data from the sensor node in the in the history of the universe the business of both of them can easily for and so if you think about it from the perspective of the role of what it's saying is it you think of overlap now and then it moves sensors of away the object using inside our senses and then you can just write it out and turn right now what I expect to see how far we largely is supposed to be and to make a prediction so in this case where for its information about the current sensor readings of our logic looking at is and motor commands that execute and later for for basically where those sensorimotor transitions and then to predict what's going to scene with the center value developed so if this was predicted by the for of the transition is pretty by the for successfully into another vision and now there's 2 3 control over the predicted transition because now we want more predictable we can build a stable representation that well and selectively pulls over at properly and elaborated in this new suppressing the form and passed through a chain so we want to see is sort of a stable representation once the world comes so on and they can be used as part of the reason for that so you look at the end of this paper is the Top provides the user very likely belong to the work of the yesterday in the form other words that the teacher and that's 3 objects this is all the sensory
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