Jeff
Hawkins - On Intelligence |
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Topic |
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Hawkins -
On Intelligence |
30 |
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In an auto
associative memory you
don't have to have the entire
pattern you want to retrieve in order to retrieve it. |
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Hawkins -
On Intelligence |
30 |
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You might have only part of the pattern, or you
might have a somewhat messed up pattern |
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0 |
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Hawkins -
On Intelligence |
30 |
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The auto-associative
memory can retrieve the correct pattern, as
it was originally stored, even though you start with a messy version of it. |
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Hawkins -
On Intelligence |
30 |
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Going to a bank with a ripped and unreadable
currency bill and the banker says "I think
this is a messed up $100 bill. Give me that one, and I will give you this nice crisp $100 bill. “ |
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Hawkins -
On Intelligence |
30 |
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An auto
associative memory can be designed to store sequences of patterns. |
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0 |
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Hawkins -
On Intelligence |
30 |
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With a sequence
of patterns, similar to a portion of a melody, the auto associative memory can remember the entire melody. |
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0 |
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Hawkins -
On Intelligence |
30 |
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You might enter
the first few notes of "twinkle
twinkle little star" and the auto associative memory returns
the whole song. |
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Hawkins -
On Intelligence |
31 |
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People
learn practically everything as a sequence of patterns. |
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1 |
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Hawkins -
On Intelligence |
65 |
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Your brain is being flooded with the spatial
and temporal patterns
from all of your senses. |
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34 |
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Hawkins -
On Intelligence |
66 |
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A neuron collects inputs from its synapses, and combines these inputs together to decide when to output a spike to other neurons. |
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1 |
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Hawkins -
On Intelligence |
66 |
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A typical neuron can cycle its functions and reset itself in about 5 ms, or around 200 times per second. |
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Hawkins -
On Intelligence |
66 |
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The brain is a parallel computer. It has billions of cells all computing at the same
time. |
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0 |
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Hawkins -
On Intelligence |
68 |
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The brain does not compute the answers to problems. It retrieves the answers from memory. |
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2 |
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Hawkins -
On Intelligence |
68 |
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The essence the answers were stored
in memory a long time
ago. |
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0 |
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Hawkins -
On Intelligence |
68 |
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The entire cortex is a memory system. It is not a
computer at all. |
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0 |
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Hawkins -
On Intelligence |
69 |
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A retrieved
memory is adjusted as it is recalled to accommodate the particulars of the moment. |
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1 |
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Hawkins -
On Intelligence |
69 |
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The memory of how
to catch a ball was not programmed into your brain; it was learned over years
of repetitive practice, and it is stored, not calculated, in your neurons. |
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Hawkins -
On Intelligence |
69 |
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The neocortex is not
like a computer, parallel or otherwise. Instead of computing
answers to problems, the neocortex uses stored memories to solve problems and produce behavior. |
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Hawkins -
On Intelligence |
70 |
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Neocortex
stores sequences of
patterns. |
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1 |
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Hawkins -
On Intelligence |
70 |
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Neocortex recalls
patterns auto-associatively. |
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0 |
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Hawkins -
On Intelligence |
70 |
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Neocortex stores patterns in an invariant
form. |
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0 |
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Hawkins -
On Intelligence |
70 |
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Neocortex stores patterns in a hierarchy. |
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0 |
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Hawkins -
On Intelligence |
70 |
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A story is stored in your head in a sequential fashion and can only
be recalled in the same
sequence. |
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Hawkins -
On Intelligence |
70 |
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It's almost
impossible
to think of anything complex that isn't a series of events or thoughts. |
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0 |
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Hawkins -
On Intelligence |
70 |
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In telling
a story some people can't get to the point of it right away. They seem to ramble on with irritating
details and tangents. |
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0 |
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Hawkins -
On Intelligence |
70 |
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They are promulgating
the story
as it happened to them, through time, and cannot
tell it any other way. |
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0 |
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Hawkins -
On Intelligence |
71 |
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All memories are like this. You
have to walk through the temporal sequence of how you do things. |
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1 |
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Hawkins -
On Intelligence |
71 |
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Your memory of the alphabet is a sequence of patterns. |
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0 |
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Hawkins -
On Intelligence |
71 |
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The same thing is goals for the
days of the week for the months of the year, your phone number, your
countless other things. |
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0 |
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Hawkins -
On Intelligence |
71 |
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Your memory
for songs is a great
example of temporal
sequences and memory. |
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0 |
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Hawkins -
On Intelligence |
72 |
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You can't
recall a song
backward. |
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1 |
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Hawkins -
On Intelligence |
72 |
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Tactile memory for textures.
Your memory for the tactical memory of gravel is based on pattern sequences
across the pressure and vibration sensing neurons of your skin. |
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0 |
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Hawkins -
On Intelligence |
73 |
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All memories are stored in the synaptic connections between neurons. |
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1 |
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Hawkins -
On Intelligence |
73 |
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Only a limited
number of synapses and neurons in your skin are
playing an active role
in memory recall at any one
time. |
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0 |
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Hawkins -
On Intelligence |
73 |
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An adult
human neocortex has an incredibly
large memory capacity but we can only remember a few at any time and can only do so in a sequence of association. |
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0 |
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Hawkins -
On Intelligence |
73 |
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There are thousands
of detailed memories stored in the
synapses of our brains that are rarely
used. |
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Hawkins -
On Intelligence |
73 |
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Most of the
information in our brains that we know is sitting there
idly
waiting for the appropriate cues to invoke
it. |
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0 |
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Hawkins -
On Intelligence |
73 |
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Autoassociative nature of memory. |
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0 |
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Hawkins -
On Intelligence |
73 |
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Patterns associated with themselves. |
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0 |
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Hawkins -
On Intelligence |
73 |
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An autoassociative
memory
is one that can recall complete patterns when given only a partial or distorted input. |
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0 |
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Hawkins -
On Intelligence |
73 |
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Autoassociative
memory can work for both spatial and temporal patterns. |
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0 |
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Hawkins -
On Intelligence |
74 |
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If you recall
a small detail about something that happened long ago, the entire
memory sequence can come flooding back into your mind. |
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1 |
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Hawkins -
On Intelligence |
74 |
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During conversation we often can't hear all the words we are in a noisy environment. Our brains fill in what they
miss with what they expect to hear. |
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0 |
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Hawkins -
On Intelligence |
74 |
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It is well established that we don't actually hear all the sounds we perceive. |
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0 |
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Hawkins -
On Intelligence |
74 |
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Some people complete of the sentences of others
aloud,
but in our minds all of us are doing this constantly. |
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0 |
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Hawkins -
On Intelligence |
74 |
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For the most part we are not aware that we are constantly completing patterns, but it's a ubiquitous and fundamental feature of how memories
are stored in the cortex. |
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0 |
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Hawkins -
On Intelligence |
74 |
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At any time, a piece can activate the whole. This is the essence of auto associated memories. |
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0 |
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Hawkins -
On Intelligence |
74 |
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Your neocortex is a complex
biological autoassociative memory. |
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0 |
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Hawkins -
On Intelligence |
74 |
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During each
waking moment,
each functional
region of your neocortex is essentially waiting vigilantly for familiar patterns or pattern fragments. |
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0 |
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Hawkins -
On Intelligence |
74 |
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The mere appearance of your friend forces your brain to start recalling
patterns associated
with her. |
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0 |
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Hawkins -
On Intelligence |
82 |
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Memories are stored in a form that captures the essence of relationships, not the details of the moment. |
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8 |
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Hawkins -
On Intelligence |
82 |
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When you see,
feel, or hear something, the cortex takes the detailed highly specific input and converts it to an invariant
form. |
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0 |
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Hawkins -
On Intelligence |
82 |
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It is the invariant
form that is stored in memory, and it is the invariant
form of each new input pattern that it gets compared to. |
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0 |
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Hawkins -
On Intelligence |
82 |
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Memory storage, memory recall, and memory
recognition occur at the
level of invariant
forms. |
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0 |
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Hawkins -
On Intelligence |
82 |
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An important
function
of the neocortex is to use its
memory to make
predictions. |
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0 |
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Hawkins -
On Intelligence |
83 |
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When you see
your friends face, your cortex fills in and predicts the myriad details. |
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1 |
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Hawkins -
On Intelligence |
83 |
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Your cortex makes these predictions with great specificity. |
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0 |
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Hawkins -
On Intelligence |
84 |
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Your brain does this by combining a memory of the invariant structure of her face with the particulars of your immediate experience. |
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1 |
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Hawkins -
On Intelligence |
84 |
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The combining of invariant representations and current
input to
make detailed
predictions is exactly
what is happening. |
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0 |
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Hawkins -
On Intelligence |
84 |
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This combining is a ubiquitous
process
that happens in every region of cortex. |
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0 |
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Hawkins -
On Intelligence |
84 |
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We are able
to predict not only the words others will say, but also in what tone of voice they will say them. |
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0 |
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Hawkins -
On Intelligence |
84 |
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Three properties of cortical memory (storing sequences, autoassociative
recall,
and invariant representations) are necessary ingredients to predict the future based on memories of the past. |
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0 |
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Hawkins -
On Intelligence |
86 |
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Our brains use stored memories to constantly make predictions about everything we see, feel, and hear |
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2 |
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Hawkins -
On Intelligence |
86 |
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The majority
of predictions occur outside
of awareness. |
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0 |
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Hawkins -
On Intelligence |
87 |
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Brain constantly makes predictions about the very
fabric of the world
we live in. |
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1 |
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Hawkins -
On Intelligence |
87 |
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The predictions are made in parallel and will just as readily detect an odd
texture,
a misshapen nose, or an unusual
motion. |
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0 |
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Hawkins -
On Intelligence |
87 |
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What we perceive is a combination of what we sense and of our
brain's memory=derived predictions. |
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0 |
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Hawkins -
On Intelligence |
88 |
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All regions
of the neocortex are simultaneously trying to predict what their next experience will be. |
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1 |
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Hawkins -
On Intelligence |
88 |
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Visual
areas make predictions about edges, shapes,
objects, locations, and motions. |
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0 |
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Hawkins -
On Intelligence |
88 |
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Auditory
areas make predictions about tones, direction to source, and patterns
of sound. |
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0 |
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Hawkins -
On Intelligence |
89 |
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somatosensory
areas make predictions about touch, texture, contour, and temperature. |
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1 |
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Hawkins -
On Intelligence |
89 |
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Correct
predictions result in understanding. |
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0 |
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Hawkins -
On Intelligence |
89 |
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Prediction is the primary
function of the neocortex, and the foundation of intelligence. |
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0 |
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Hawkins -
On Intelligence |
90 |
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Rodolfo
Llinas, I of the Vortex, the capacity to predict the
outcome of future events is most likely, the ultimate and most
common of all global brain functions. |
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1 |
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Hawkins -
On Intelligence |
90 |
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There is an entire
subfield of mathematics devoted to Bayesian networks. |
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0 |
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Hawkins -
On Intelligence |
90 |
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Bayesian
networks use probability
theory to make
predictions. |
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0 |
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Hawkins -
On Intelligence |
91 |
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Prediction is pervasive and the basis for how you understand the world. |
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1 |
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Hawkins -
On Intelligence |
91 |
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When you listen
to a favorite melody, you hear the
next note in your head before it occurs. |
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0 |
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Hawkins -
On Intelligence |
92 |
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Neurons in your head will fire
when you hear that next out fire in advance of your actual hearing it, and so
you hear this song in your head. |
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1 |
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Hawkins -
On Intelligence |
92 |
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When listening
to people speak, you often know what they're going to say before they
finished speaking. |
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0 |
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Hawkins -
On Intelligence |
92 |
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People tend
to use common phrases or expressions in much of their conversation. |
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0 |
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Hawkins -
On Intelligence |
92 |
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Prediction is not always exact. Rather, our minds
work to make probabilistic predictions concerning what is about to happen. |
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0 |
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Hawkins -
On Intelligence |
92 |
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At times, our expectations are distributed among several possibilities |
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0 |
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Hawkins -
On Intelligence |
93 |
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In Western
music,
the brain automatically predicts beats, repeated
rhythms, completion of phrases, and end of songs. |
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1 |
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Hawkins -
On Intelligence |
93 |
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The basis of these mostly unconscious predictions is a set of memories that are stored
in your cortex. |
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0 |
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Hawkins -
On Intelligence |
93 |
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Your brain can't say exactly what
will happen next, but it nevertheless predicts which note patterns are likely to happen and which
aren't. |
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0 |
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Hawkins -
On Intelligence |
93 |
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We see what we expect to see. |
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0 |
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Hawkins -
On Intelligence |
97 |
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Intelligence is measured
by the capacity to remember and predict patterns in the world including language, mathematics, physical properties of objects, and social
situations. |
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4 |
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Hawkins -
On Intelligence |
97 |
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The brain receives patterns from the outside world, stores them in memories, and makes predictions by combining what it has seen before and what is happening now. |
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0 |
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Hawkins -
On Intelligence |
99 |
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The human
cortex is the same thickness and is very nearly the same structure as the cortex of
our mammal relatives. |
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2 |
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Hawkins -
On Intelligence |
99 |
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When evolution
makes something
big very quickly, as it did with the human cortex, it does so by copying
an existing structure. |
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0 |
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Hawkins -
On Intelligence |
99 |
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Humans got smart by adding many more elements of a common cortical algorithm. |
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0 |
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Hawkins -
On Intelligence |
99 |
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The human neocortex is a relatively new structure. |
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0 |
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Hawkins -
On Intelligence |
99 |
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Memory and prediction are the keys to unlocking the mystery of intelligence. |
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0 |
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Hawkins -
On Intelligence |
99 |
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Start with the reptilian brain with no cortex. |
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0 |
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Hawkins -
On Intelligence |
99 |
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If evolution tacks on a memory
system (neocortex) to the sensory path of the primitive brain, the animal
gains and ability to predict the future. |
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0 |
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Hawkins -
On Intelligence |
103 |
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The back
part of the cortex contains the
sections where the eyes, ears,
and touch inputs arrived. |
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4 |
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Hawkins -
On Intelligence |
104 |
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Reptiles with sophisticated
senses and sophisticated but relatively rigid behaviors. |
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1 |
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Hawkins -
On Intelligence |
104 |
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Nature discovered that by adding a memory system and feeding the sensory stream into it, the animal could remember past experiences. |
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0 |
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Hawkins -
On Intelligence |
104 |
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When the animal found itself in
the same or similar situation, the memory will be recall, leading to a
prediction of what was likely to happen next. |
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0 |
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Hawkins -
On Intelligence |
104 |
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Intelligence and understanding started as a memory system that fed predictions into the sensory stream. |
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0 |
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Hawkins -
On Intelligence |
104 |
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To know
something means that you
can make predictions about it. |
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0 |
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Hawkins -
On Intelligence |
104 |
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With humans, the cortex has taken over most of the motor behavior. |
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0 |
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Hawkins -
On Intelligence |
104 |
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Instead of just making predictions based on behavior of the old brain. The human
neocortex
directs behavior to satisfy
the prediction. |
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0 |
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Hawkins -
On Intelligence |
105 |
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To make predictions of future events, the neocortex must store sequences of patterns. |
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1 |
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Hawkins -
On Intelligence |
105 |
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To recall the appropriate memories, the brain has to retrieve patterns by their similarity
to past patterns (auto associative recall). |
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0 |
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Hawkins -
On Intelligence |
105 |
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Memories
have to be stored in an invariant form so that the knowledge of past events can be applied to new situations that are similar but not identical to the past. |
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0 |
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Hawkins -
On Intelligence |
113 |
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Information also flows from higher to lower regions via a network of feedback connections. |
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8 |
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Hawkins -
On Intelligence |
113 |
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As many if not more feedback connections in visual cortex as there are feedforward connections. |
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0 |
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Hawkins -
On Intelligence |
113 |
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The cortex's
core function is to make
predictions. |
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0 |
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Hawkins -
On Intelligence |
113 |
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Prediction requires a comparison between what is
happening
and what you expect to happen. |
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0 |
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Hawkins -
On Intelligence |
113 |
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What is actually
happening flows up,
and what you expect to happen flows down. |
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0 |
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Hawkins -
On Intelligence |
113 |
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The same feedforward=feedback process is occurring in all your cortical areas involving all your senses. |
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0 |
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Hawkins -
On Intelligence |
114 |
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The transformation from fast-changing to slow changing and from spatially specific to spatially
invariant,
is well documented for vision. |
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1 |
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Hawkins -
On Intelligence |
115 |
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For hearing, when someone speaks
to you, the changes in sound pressure occur very rapidly; the patterns
entering the primary auditory area change just as rapidly. |
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1 |
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Hawkins -
On Intelligence |
115 |
|
Patterns received by the first auditory
area can
vary widely. A word can be spoken with different accents, and different pitches, or at different
speeds. |
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0 |
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Hawkins -
On Intelligence |
115 |
|
Higher up in the cortex, those low level features don't matter; a word is a word regardless of the acoustic details. |
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0 |
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Hawkins -
On Intelligence |
115 |
|
We see the same
kind of feedback, prediction, and invariant
recall in auditory
cortex
as we see in the visual system. |
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0 |
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Hawkins -
On Intelligence |
116 |
|
There are very different inputs
arriving at different locations in the primary battle centers somatosensory
cortex. Again we would find selves and regions several steps removed from the
primary input that respond to an object. |
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1 |
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Hawkins -
On Intelligence |
117 |
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Information flows up
and down sensory areas
of the cortex. |
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1 |
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Hawkins -
On Intelligence |
117 |
|
The downward
flow fills in the current input and makes predictions about what we will experience next. |
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0 |
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Hawkins -
On Intelligence |
117 |
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Something I
hear can lead to a prediction of what I should see or feel. |
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0 |
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Hawkins -
On Intelligence |
117 |
|
Information
flows up the auditory
hierarchy to an association area that connects
vision with hearing. |
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0 |
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Hawkins -
On Intelligence |
117 |
|
The representation then flows back down the auditory and visual
hierarchies, leading to both
auditory and visual predictions. |
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0 |
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Hawkins -
On Intelligence |
117 |
|
This kind of multisensory
prediction is occurring all the time. |
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0 |
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Hawkins -
On Intelligence |
118 |
|
Information simultaneously flows
up and down the sensory hierarchies to create a unified sensory
experience involving prediction in all senses. |
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1 |
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Hawkins -
On Intelligence |
119 |
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All the little
sensations
are fully integrated into our perceptual predictions. |
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1 |
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Hawkins -
On Intelligence |
119 |
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These predictions can only come about by massive coordination of patterns streaming up and down the cortical hierarchy. |
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0 |
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Hawkins -
On Intelligence |
119 |
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The entire neocortex, all the sensory
and association areas, act as one. |
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0 |
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Hawkins -
On Intelligence |
119 |
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We have an overarching
sensory system,
sights,
sounds, touch, and more combined, all flowing
up and down a single multi-branched hierarchy. |
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0 |
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Hawkins -
On Intelligence |
119 |
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All predictions are learned by experience. |
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0 |
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Hawkins -
On Intelligence |
119 |
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You are not
born with
any of this knowledge; you learned it through the incredibly large capacity of your cortex to remember patterns. |
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0 |
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|
Hawkins -
On Intelligence |
120 |
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If there are consistent
patterns among the inputs
flowing into your brain, your cortex will use them to predict future events. |
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1 |
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Hawkins -
On Intelligence |
120 |
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An input in a sensory area can flow
to an association area which can lead to a pattern
flowing down the motor
cortex resulting in behavior. |
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0 |
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Hawkins -
On Intelligence |
120 |
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We interpret these downward flowing patterns as predictions. |
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0 |
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Hawkins -
On Intelligence |
120 |
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In the motor
cortex we interpret the downward flowing patterns as motor commands. |
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0 |
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Hawkins -
On Intelligence |
120 |
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As Mountcastle pointed out, the motor cortex looks
like the sensory
cortex. |
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0 |
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|
Hawkins -
On Intelligence |
120 |
|
The way the cortex
processes
downward-flowing sensory predictions is similar to how it processes downward-flowing
motor commands. |
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0 |
|
|
Hawkins -
On Intelligence |
120 |
|
There are no pure sensory or pure motor areas in the cortex. |
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0 |
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|
Hawkins -
On Intelligence |
120 |
|
Sensory patterns simultaneously flow in anywhere and everywhere, and then flow back down in any area of the hierarchy, leading to predictions or motor behavior. |
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0 |
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|
Hawkins -
On Intelligence |
120 |
|
Although the motor
cortex has some special attributes, it is correct to think of it as just part
of one large hierarchical memory-prediction
system. |
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0 |
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|
Hawkins -
On Intelligence |
120 |
|
Seeing, hearing, touching, and acting are profoundly intertwined. |
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0 |
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Hawkins -
On Intelligence |
122 |
|
V1,V2, and V4, each is a collection of many smaller subregions. |
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2 |
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|
Hawkins -
On Intelligence |
122 |
|
The largest
region by far
is V1, the primary
visual area. |
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0 |
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|
Hawkins -
On Intelligence |
122 |
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Next would be V2. They are large compared to most regions. |
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V1 is made
up of numerous separate
little cortical areas that are only connected to their neighbors indirectly, through regions higher up in the hierarchy. |
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V1 would have the largest number of small subregions of any visual
area. |
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V2 would be composed of fewer, slightly
larger subregions. |
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The same
would be true for V4. |
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The top
region IT would have only
a single region, which has a birds eye view of the entire
visual world. |
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The cortex now looks similar everywhere. |
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1 |
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Pick any region and you will find many lower regions providing converging
sensory input. |
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The receiving
region sends projections back to the input regions, telling them what
patterns they
should expect to see next. |
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Higher association areas unite
information from multiple
senses
such as vision
and touch. |
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A lower
region
like a subregion of V2
unites the information from separate
subregions
within V1. |
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A region doesn't know – indeed it can't know – what any of those inputs mean. |
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An association area doesn't need
to know that it is handling
visual input from multiple
pairs of V1. |
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An association area doesn't need to know that it is handling
input from vision and hearing. |
|
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The job of any cortical
region is to find out how its inputs are
related, to memorize the sequence of correlations between them, and to use its memory to predict how the inputs will behave in the future. |
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The same
process
is happening everywhere: a common cortical algorithm. |
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This hierarchical depiction helps us understand the process of creating invariant representations. |
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The most
important result of this
depiction of cortical
hierarchy is that every
region of cortex forms
invariant representations. |
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Now we can say that invariant representations are ubiquitous. Invariant
representations are
formed in every cortical region. |
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Every
region
forms invariant representations drawn from the input areas hierarchically
below it. |
|
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|
Thus the subregions of V4, V2, and V1 create invariant
representations
based on what flows into them. |
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|
Association regions above IT form invariant
representations
of patterns
from multiple senses. |
|
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|
All regions of the cortex form invariant representations of the world beneath them in the hierarchy. |
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Why is the neocortex built as a hierarchy? Because the cortex has built a model of the world. |
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The cortex's
hierarchical structure stores a model of the hierarchical structure of the real world. |
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|
The real
world's nested structure is mirrored by the nested
structure of the cortex. |
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|
Patterns from the retina entering your primary visual cortex are being combined to form components of visual objects. |
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1 |
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|
The function of the cortex and
the method by which it learns naturally discover the hierarchical
relationships in the world. |
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You are not
born with
knowledge of language,
houses, or music. |
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|
The cortex has a clever learning algorithm that
naturally finds
whatever hierarchical structure exists and captures
it. |
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|
Higher
regions of the cortex are keeping track of the big picture while lower
areas are actively
dealing with the fast-changing small details. |
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|
Since we can only
touch, hear, and see a very small part of the world any moment in time, information flowing into the brain naturally
arise as a sequence
of patterns. |
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|
The cortex functions to learn those sequences that occur over and
over again. |
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|
Each region
of cortex sees a stream
of patterns. |
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|
If the patterns
are related in such a way that the region can learn to predict what pattern will occur next, the cortical region forms a persistent
representation,
or memory, for the sequence. |
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|
Learning
sequences
is
the most basic ingredient for forming invariant representations of real-world objects. |
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|
Predictability is the very
definition of reality. |
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|
The brain can be said to store sequences of
sequences.
Each region of the cortex learns the
sequences, develops what Hawkins calls “names” for the sequences it
knows,
and passes these names to the next regions higher in the cortical hierarchy. |
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|
As information
moves up
from primary sensory regions to higher levels, we see fewer and fewer changes over time. |
|
0 |
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|
In primary
visual areas like V1, the set of active cells is changing rapidly as new
patterns fall on the retina several times each
second. |
|
0 |
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|
In visual
area IT, self firing
patterns
are more stable. |
|
0 |
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|
Each region of cortex has a repertoire of sequences
it knows. |
|
0 |
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|
Regions store these sequences about anything and everything. |
|
0 |
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|
Each cortical region has a name for each sequence it knows. |
|
0 |
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|
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|
The "name" is a group of cells whose collected
firing
represents the set of objects in the sequence. |
|
0 |
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|
These cells remain
active as long as the sequences playing, and it is this “name” that is passed
up to the next region in the hierarchy. |
|
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|
As long as the input patterns are part of a predictable sequence, the region presents a constant “name” to the next higher region. |
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|
We can imagine region IT at the top of
the visual hierarchy relaying to an association area above it, "I am seeing a face." |
|
0 |
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|
In this way, a predictable sequence of
events
gets identified with a "name." |
|
0 |
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|
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|
This happens
over and over again as we go up in the hierarchical
pyramid. |
|
0 |
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|
One region might recognize a sequence of sounds that comprise
phonograms. |
|
0 |
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|
The next
higher region recognizes sequences the phonems to create words. |
|
0 |
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|
The next
higher region
recognizes sequences
of words
to create phrases, and so on. |
|
0 |
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|
By collapsing
predictable sequences into named objects at each region in the hierarchy, we achieve more
and more stability the higher we go. |
|
0 |
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|
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|
This creates invariant
representation. |
|
0 |
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|
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|
The opposite
effect happens
as a pattern moves
back down the
hierarchy:
stable patterns get unfolded into sequences. |
|
0 |
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|
At this point the unfolding pattern splits and travels down both the auditory
section of
cortex and the motor section of cortex. |
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|
Following the motor path, each word is unfolded into a memorized sequence of phonems. |
|
0 |
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|
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|
In the final
bottom region,
each phonem is
unfolded into a sequence
of muscle commands to make
sounds. |
|
0 |
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|
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|
The lower you look in the hierarchy, the faster the patterns are changing. |
|
0 |
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|
A single constant pattern at the top of the motor hierarchy eventually leads to a complex and
lengthy sequence of speech
sounds. |
|
0 |
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|
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|
If you want to type the Gettysburg address you start with the same pattern at the top of the hierarchy. |
|
0 |
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|
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|
Words are unfolded into letters, and the letters are unfolded into muscle commands to your fingers for typing. |
|
0 |
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|
Hawkins -
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|
A single
memory of the speech can take various
behavioral forms. |
|
0 |
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|
Hawkins -
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|
At any
region,
an invariant pattern can bifurcate and follow a different path down. |
|
0 |
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|
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|
Representations of simple objects at the bottom of the hierarchy can be reused over and over for different high-level sequences. |
|
0 |
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|
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|
A hierarchy
of nested sequences allows the sharing and reuse of lower-level objects – words, phonems, and letters being but a few examples. |
|
0 |
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|
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|
It is a remarkably
efficient way
to store
information about the
world and its structure and very
different
from how computers work. |
|
1 |
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|
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|
The same unfolding of sequences occurs in the sensory as well as the motor regions. |
|
0 |
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|
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|
The unfolding
of sequences
allows you to perceive and understand objects from different
views. |
|
0 |
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|
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|
The way you memorize
sequences
and represent
them by name as information goes up and down the cortical hierarchy may remind
you of the hierarchy
of military command. |
|
0 |
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|
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|
If something goes wrong that
cannot be handled by subordinates down the chain of command, then the issue
rises up the hierarchy until someone knows
what to do next. |
|
1 |
|
|
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|
What was an unanticipated
problem to subordinates is just the expected next task for the officer in
charge. |
|
0 |
|
|
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|
If lower
regions of cortex failed to predict what
patterns they are
seeing,
they consider that an error and pass the error up
the hierarchy. This is repeated until some region does anticipate the pattern. |
|
0 |
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|
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|
Every
cortical region attempts to store and recall sequences. |
|
0 |
|
|
Hawkins -
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|
The bottom-up
inputs to a region of
cortex
are input patterns carried on thousands or millions of axons. |
|
0 |
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|
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|
These axons come from different regions and contain all sorts of patterns. |
|
0 |
|
|
Hawkins -
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|
The number
of possible patterns that can exist on even 1000 axons is larger than
the number of molecules in the universe. |
|
0 |
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|
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|
A region will only see a tiny
fraction of these possible patterns in a lifetime. |
|
0 |
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|
Hawkins -
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|
The brain must classify patterns. |
|
1 |
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|
Hawkins -
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|
You are going to look at all the
input patterns coming in from lower cortical regions, classify them, and then look
for sequences. |
|
0 |
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|
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|
Both steps, classification and sequence
formation,
are necessary to create invariant representations, and each region of cortex does them. |
|
0 |
|
|
Hawkins -
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|
If you know the most likely sequence for a series of inputs, you will use
this knowledge
to decide how to classify the ambiguous input. |
|
1 |
|
|
Hawkins -
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135 |
|
You use the context of known sequences to resolve ambiguity |
|
0 |
|
|
Hawkins -
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135 |
|
When people
speak
their individual words very often cannot be understood out of context. |
|
0 |
|
|
Hawkins -
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135 |
|
Most of the time you are aware that you are filling in ambiguous or incomplete information from your memories or sequence |
|
0 |
|
|
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|
You hear what you expect to hear
and see what you expect to see – at least when what you hear and see fits
into past experience. |
|
0 |
|
|
Hawkins -
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|
Memory of sequences allows you
not only to resolve ambiguity and current input, but also to predict which
input should happen next. |
|
0 |
|
|
Hawkins -
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|
By recognizing a sequence of patterns, a cortical region will predict its next input pattern and tell the region below what to expect. |
|
0 |
|
|
Hawkins -
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135 |
|
A region of
cortex
not only learns
familiar sequences, it also learns
how to modify its classifications. |
|
0 |
|
|
Hawkins -
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|
In cortical
regions,
bottom-up classifications and top-down
sequences
are constantly
interacting, changing
throughout your life. |
|
1 |
|
|
Hawkins -
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|
This is the essence
of learning. |
|
0 |
|
|
Hawkins -
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|
Forming new
classifications and new
sequences is how you remember the world. |
|
0 |
|
|
Hawkins -
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|
Another part of the cortical job is to relay
the name of the sequence you are seeing to the next level up. |
|
0 |
|
|
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|
The hierarchy of the cortex ensures that memories of objects are distributed over the hierarchy; they aren't
located in a single
spot. |
|
1 |
|
|
Hawkins -
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|
Because each
region of the hierarchy forms invariant
memories,
what a typical region of cortex learns is sequences
of invariant.
representations, which are themselves sequences of invariant memories |
|
0 |
|
|
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|
When you think about the world
you are recalling sequences of patterns that correspond to the way the
objects of the world are and how they behave. |
|
0 |
|
|
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|
The order in which you
experience parts of the world is determined by the world structure. |
|
0 |
|
|
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|
An invariant representation in
any region of the cortex can be turned into a detailed prediction of how it
will appear on yours senses by propagating the pattern down the hierarchy. |
|
0 |
|
|
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|
Similarly, an invariant
representation in the motor cortex can be turned into detailed and situation
specific motor commands by propagating the pattern down the motor hierarchy. |
|
0 |
|
|
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|
We will start with a description
of what a cortical region looks like. |
|
1 |
|
|
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|
Cortical
regions vary greatly in size, the largest being the primary sensory areas. |
|
0 |
|
|
Hawkins -
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138 |
|
Let's assume that a typical cortical area is the size of a
small coin. |
|
0 |
|
|
Hawkins -
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139 |
|
The density and shape of the cells in the cortex vary as you move from top to bottom. |
|
1 |
|
|
Hawkins -
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139 |
|
These differences define the layers. |
|
0 |
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|
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|
Layer 1,
the top layer is the most distinct of the six layers. It has very few cells consisting
primarily of a mat of axons running parallel to the cortical
surface |
|
0 |
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|
Layers 2 and 3
looks similar. They contain many, tightly
packed. pyramidal cells. |
|
0 |
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|
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|
Layer 4 has a type
of star-shaped cell. |
|
0 |
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|
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|
Layer 5 has regular pyramidal cells as well as a class of extra big pyramidal-shaped cells. |
|
0 |
|
|
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|
Layers 6, the bottom layer also has several
types of unique
neurons. |
|
0 |
|
|
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|
Columns of
cells
run perpendicular to the layers. You can think of columns as being vertical units of cells that work together. |
|
0 |
|
|
Hawkins -
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139 |
|
The layers within each column are connected by axons that run up
and down, making synapses along the way. |
|
0 |
|
|
Hawkins -
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|
Columns do not have clear boundaries but their existence can be inferred from several
lines of evidence. |
|
0 |
|
|
Hawkins -
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139 |
|
One reason is that it vertically aligned cells in each
column
tend to become active for the same stimulus. |
|
0 |
|
|
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|
The cells within each column are strongly connected. |
|
0 |
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|
Hawkins -
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|
Activity spreads up and down within a column
of cells. |
|
1 |
|
|
Hawkins -
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140 |
|
In an embryo, single precursor cells migrate from an inner brain cavity to where the cortex takes take shape. |
|
0 |
|
|
Hawkins -
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|
Each of these cells divides to create about 100 neurons, called a microcolumn. |
|
0 |
|
|
Hawkins -
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140 |
|
The human cortex has an estimated several hundred
million microcolumns. |
|
0 |
|
|
Hawkins -
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140 |
|
Imagine a single
microcolumn is the width of a human hair. |
|
0 |
|
|
Hawkins -
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140 |
|
The brush
like mat is a simplistic
model of
the coin size
cortical region. |
|
0 |
|
|
Hawkins -
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140 |
|
And information
flows
mostly in the direction of the hairs: horizontally in layer 1 and vertically in layers 2 through 6 |
|
0 |
|
|
Hawkins -
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|
At least 90%
of the synapses on cells
within each column come from places outside the column itself. |
|
0 |
|
|
Hawkins -
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140 |
|
Some
connections
arrived from neighboring column. |
|
0 |
|
|
Hawkins -
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140 |
|
Other
connections
come from halfway across the brain. |
|
0 |
|
|
Hawkins -
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140 |
|
Vernon
Mountcastle argued there is a single cortical algorithm, he also proposed a cortical column is the basic unit of computation in the cortex. |
|
0 |
|
|
Hawkins -
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|
It is believed that the column is the basic unit of prediction. |
|
1 |
|
|
Hawkins -
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141 |
|
Converging
inputs from lower
regions always arrive
at layer 4, the main input layer. |
|
0 |
|
|
Hawkins -
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141 |
|
Layer 4
cells then send
projections up to cells
in layer 2 and layer 3 within their
column. |
|
0 |
|
|
Hawkins -
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141 |
|
Layer 6 cells
are the downward
projecting output cells from a cortical column and project to layer 1 in the region hierarchically below. |
|
0 |
|
|
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|
The sum of
all these mechanisms allows the cortex to learn
sequences,
make predictions, and form
constant representations, or "names," for
sequences. |
|
12 |
|
|
Hawkins -
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153 |
|
How does a region
of the cortex make specific predictions from invariant
memories? |
|
0 |
|
|
Hawkins -
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153 |
|
We have to combine feedforward information (actual input) with feedback information (a prediction in an invariant form). |
|
0 |
|
|
Hawkins -
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156 |
|
Every moment of your waking
life, each
region of the cortex is comparing a set of expected columns driven from above with the set of observed columns driven from below. |
|
3 |
|
|
Hawkins -
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|
Where the
two sets intersect is what we perceive. |
|
0 |
|
|
Hawkins -
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156 |
|
If we had perfect
input from below and perfect
predictions,
then the set of perceived
columns would always be contained in the set of predicted columns. |
|
0 |
|
|
Hawkins -
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156 |
|
We often don't have such
agreement. The method of combining partial prediction with partial input resolves ambiguous input, it fills in
missing pieces of information, and it decides between alternate views. |
|
0 |
|
|
Hawkins -
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156 |
|
It is how we decide
whether a picture is of a vase or two
faces. |
|
0 |
|
|
Hawkins -
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156 |
|
In addition to projecting to lower cortical
regions,
layer 6 cells can send their outputs back into layer 4
cells of their own column. |
|
0 |
|
|
Hawkins -
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156 |
|
When they do, our predictions become the input. |
|
0 |
|
|
Hawkins -
On Intelligence |
156 |
|
This is what we do when daydreaming or thinking. |
|
0 |
|
|
Hawkins -
On Intelligence |
156 |
|
It allows us to the consequences
of our own predictions. |
|
0 |
|
|
Hawkins -
On Intelligence |
156 |
|
We do this many hours a day as
we plan the future, worry about events to come, or just
"imagining." |
|
0 |
|
|
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|
Confusion occurs when the cortex can't find any memory that matches with the input. |
|
4 |
|
|
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|
Your eyes scan everywhere on the
picture. |
|
0 |
|
|
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160 |
|
New inputs race all the way up
the cortical hierarchy. |
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0 |
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Hawkins -
On Intelligence |
160 |
|
High-level cortex tries lots of
different hypotheses but, as these predictions raced down the hierarchy, each
and every one conflicts with the input and the cortex is forced to try again. |
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0 |
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Hawkins -
On Intelligence |
160 |
|
During this time of confusion
your brain is totally occupied with understanding the picture. |
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0 |
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Hawkins -
On Intelligence |
160 |
|
Finally, you make a high-level
prediction that is the right one. |
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0 |
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Hawkins -
On Intelligence |
161 |
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The prediction starts at the top of the
cortical hierarchy and succeeds in propagating all the way to the bottom. |
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1 |
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Hawkins -
On Intelligence |
161 |
|
In less
than a second,
each region is
given a sequence that fits the data. |
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0 |
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Hawkins -
On Intelligence |
161 |
|
No more
errors rise to the top. You understand the picture, you see a Dalmatian dog. |
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Hawkins -
On Intelligence |
168 |
|
Hippocampus on top of it all |
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7 |
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Hawkins -
On Intelligence |
168 |
|
Three large brain structures lie under the
neocortical sheet and communicate with it. They are the basal ganglia, cerebellum, and the hippocampus. |
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Hawkins -
On Intelligence |
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All three existed prior to the neocortex. |
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0 |
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Hawkins -
On Intelligence |
168 |
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The basal
ganglia were the primitive motor system, the cerebellum learned precise timing relationships of events, and the hippocampus stored memories of specific events and places. |
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0 |
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Hawkins -
On Intelligence |
168 |
|
The neocortex is responsible for all complex
motor sequences
and can directly control your limbs. |
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0 |
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Hawkins -
On Intelligence |
170 |
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Connections between the hippocampus and the neocortex suggest that the hippocampus is the top region of the neocortex. |
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2 |
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Hawkins -
On Intelligence |
170 |
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The hippocampus occupies the peak of the neocortical pyramid. |
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0 |
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Hawkins -
On Intelligence |
170 |
|
The hippocampus not only sits at the top of the
cortical pyramid, but it still connects
directly to many older parts of the brain. |
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0 |
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Hawkins -
On Intelligence |
170 |
|
Think about the information flowing from your eyes, ears, and skin into the neocortex. |
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0 |
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Hawkins -
On Intelligence |
170 |
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Each region of the neocortex tries to understand the input in the in terms of the sequences it knows. |
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0 |
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Hawkins -
On Intelligence |
170 |
|
If it does
understand the input it does not pass on the details to higher levels of the hierarchy. |
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0 |
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Hawkins -
On Intelligence |
170 |
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If a region
does not understand the current input, it passes it up the hierarchy until some
higher region
does understand
it. |
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0 |
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Hawkins -
On Intelligence |
170 |
|
A pattern that is truly novel will escalate further and further up the hierarchy until some
higher region
does understand
it. |
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0 |
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Hawkins -
On Intelligence |
170 |
|
The net
effect is that when you get to the top of the cortical pyramid, what you have left
is information that can't be understood by prior experience. |
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0 |
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Hawkins -
On Intelligence |
171 |
|
You are left
with the part of the input that is truly new and unexpected. |
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1 |
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Hawkins -
On Intelligence |
171 |
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It is these unexplained and unanticipated remainders, the new stuff, that enters
the hippocampus and is stored
there. |
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0 |
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Hawkins -
On Intelligence |
171 |
|
This new,
fresh information won't be
stored forever.
Either it will be transferred into the
cortex or it will eventually be lost. |
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0 |
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Hawkins -
On Intelligence |
171 |
|
The hippocampus has a heterogeneous structure with several specialized regions. It's good at the unique task of quickly storing whatever
pattern it sees. |
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Hawkins -
On Intelligence |
171 |
|
You can instantly
remember a novel event in the hippocampus, but you will permanently remember something in the cortex only if you experience it over and over, either in
reality or by thinking
of it. |
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0 |
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Hawkins -
On Intelligence |
171 |
|
Alternate
Path up the Hierarchy. |
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0 |
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Hawkins -
On Intelligence |
171 |
|
The cortex has a second major pathway for passing information from region
to region,
up the hierarchy. |
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Hawkins -
On Intelligence |
172 |
|
The alternate
path starts with cells in layer 5 which project to the thalamus and then up to the next higher region of cortex. |
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Hawkins -
On Intelligence |
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|
As we move
up the cortical
hierarchy,
there is a direct path between two regions and an indirect
path through the thalamus. |
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Hawkins -
On Intelligence |
173 |
|
The alternate
pathway through the thalamus is likely the mechanism by which we attend to details that normally we would not notice. |
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Hawkins -
On Intelligence |
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It bypasses the grouping of sequences in layer 2, sending the raw
data to the next
higher region
of cortex. |
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Hawkins -
On Intelligence |
174 |
|
In this way unusual
events quickly rise to your attention. |
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Hawkins -
On Intelligence |
174 |
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This is why we can't avoid
focusing on deformities and other unusual patterns. |
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Hawkins -
On Intelligence |
174 |
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Often
however, errors aren't
strong enough
to open the alternate
pathway.
This is why we sometimes don't notice if a word is misspelled as we read
it. |
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Hawkins -
On Intelligence |
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Hawkins -
On Intelligence |
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On Intelligence |
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On Intelligence |
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