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© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 1
An Implementable Architecture for Conscious Machines
An Implementable Architecture for Conscious Machines
Dr. Pentti O A Haikonen, Principal Scientist, Cognitive technology
Nokia Research Center
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 2
Introduction
The aim of my research is to develop a conscious machine; not one with a
“flea’s consciousness” but a robot brain with the cognitive abilities and
hallmarks of the human conscious mind.
This machine would have to posses:
-Awareness of its environment, time and place
-Self-consciousness; awareness of its existence as an independent entity,
awareness of its mental content like inner speech and inner imagery and
the recognition of these as its own
-Apparent subjective immateriality of the mental content
-Cognitive functions that parallel those of the human brain; symbol
processing in the human sense, natural language
-Emotions, emotional significance and judgement
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 3
Environment Perception process Internal process
percepts of:-environment-inner states
objects
actions
situationmatch/mismatch/novelty detection
tasks, goals, needsmemories
learned routines
predictionreasoningplanned actionjudgement
ReactionsActions
etc.
experience
relationships
emotionsemotionalevaluation
The General Model of Cognition
“mental loop”
“external loop”
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-Processing with meaning and significance
-Distributed neural signal array representation
-Associative soft symbol processing
-System reactions; pain, pleasure, good, bad, emotions
-Match/mismatch/novelty detection
-Distributed attention controlled by significance
-Modulation domain operation
Basic Specifications I
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-Perception process, incl. attention, priming and prediction
-Learning, also learning by imitation, “mirror neurons”
-Inner speech, natural language
-Inner imagery
-Introspection, judgement of own thoughts
-Imagination, planning (involves the imagery of “self” executing
imagined actions)
-True “immaterial” consciousness; self-awareness
Basic Specifications II
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 6
environment
sensors & pre-processing
rawdistributed signals
innerprocesses
feedback
perception process
percepts
responses
The Outline of a Conscious Machine
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Neuron groups for Inner Processes
“Neuron group”Main input signal array
Output signal array
Associative signal array inputs
-Can associatively connect large arrays of neural signals to each other
-Can associatively connect neural signal array sequences to each other
-Can associatively evoke arrays of neural signals and neural signal array
sequences even by limited length and incomplete cues
-Sensitive to signal intensity; significance control
-Can determine match/mismatch/novelty conditions between main input
signal array and associative signal arrays
-Finds “best fit” by Winner-Takes-All threshold operation
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 8
The General Architecture
perceptpreprocesssensor
preprocesssensor
preprocesssensor
preprocesssensor
Body position
Touch subsystem
Auditory subsystem
Visual subsystem
system reactions
System
perception process
perception process
perception process
perception process
perception process
neuron group
neuron group
neuron group
neuron group
neuron groupsmell, taste, pain, etc.
motor actions threshold
threshold
percept
percept
percept
percept
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 9
The Visual Subsystemperception process
perception process
perception process
perception process
neuron group
neuron group
neuron group
neuron group
shape
size
color
perception process
neuron group
motion
gaze direction control
visualsensors
position
shape
size
color
motion
position
percept
percept
percept
percept
percept
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 10
The General Architecture II
-Each modality works on its own and produces streams of percepts about
environment and internal states.
-Modalities are associatively cross-connected, therefore the activity of one
modality may be reflected in the other modalities; percepts may be named
and labeled, names may evoke corresponding percepts…the activity of one
modality may be memorized and reported in terms of other modalities, etc.
-Attention determines which percepts are accepted for further action.
Attention is controlled by signal intensity and thresholds, these are
controlled by e.g. emotional significance.
-Pain and pleasure are system reactions that affect attention.
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 11
Why Would This Machine be Conscious?
We are conscious when we are able to report to ourselves what we are
experiencing and are able to make memories of that.
This machine is able to produce these reports; it can make a verbal note e.g.
about what is being seen and it can also make an episodic memory of that.
The machine will accumulate a personal history.
A self-conscious being must be able to perceive the difference between the
percepts caused by external entities and percepts of its own inner activity.
There are several ways to achieve this within this architecture.
The machine will, in principle, be able to report having a flow of inner speech
and inner imagery and will claim the ownership of these.
The “mental activity” takes place in modulation domain, hence the mental
content appears as immaterial.
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 12
The purpose of the work is to develop associative neuron group microchips that
-Are suitable for cognitive and conscious neural system architectures
-Can learn; associatively connect very large arrays of neural signals to each other
-Can associatively connect neural signal array sequences to each other
-Can associatively evoke arrays of neural signals and neural signal array sequences by limited length and incomplete cues (soft symbol processing)
-Can accommodate importance
-Can determine match/mismatch/novelty conditions between neural signal arrays
NRC associative neuron group integrated circuit development work
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 13
Experiments with the neuron microchip ver. 2001
This test system could learn associatively short melodies and mimic them
when few notes were played as a cue. The system learned the pitches of the
notes as well as their duration; also the duration of any silent(!) interval.
Interval detector
Microphone + one octave filter bank
Audio oscillator bank
Associative neuron groups and perception-response loops
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 14
Associative neuron group integrated circuit v. 2002
An Experimental Integrated Circuit for Conscious Machines
-24 neurons, 24 x 24 synapses in 8 individual groups (total 4608)
- Fully parallel internal operation, serial external communication
-Contains the main features of a future practical large scale microchip
s
soP/S
M
MM
N
S/P S/P S/P
threshold threshold threshold
TH
threshold
n x
neuron body
a1 a2 am
n x n synapses n x n synapses n x n synapses
enab1 enab2 enabm
lc
ck1 ck2
priority
enabWTAs_ctr
reset
S/P
M/MM/N circuit
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Associative neuron group integrated circuit ver. 2002
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 16
-Original circuitry and specifications developed by the author at NRC
-Actual implementation on silicon executed by VTT Microelectronics
Neuron chip ver. 2002 installed in test circuit board (square chip in the middle)
Associative neuron group integrated circuit ver. 2002
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 17
Conclusions
The author has developed an architecture for conscious machines.
More detailed description and discussion can be found in the book:
The Cognitive Approach to Conscious Machines, Imprint Academic 2003
Experimental integrated circuits are being developed for the actual
implementation.
More work will be needed in the development of suitable input/output
sensors and devices and especially in the sensory signal preprocessing
area.
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 18
An Implementable Architecture for Conscious Machines
An Implementable Architecture for Conscious Machines
Dr. Pentti O A Haikonen, Principal Scientist, Cognitive Technology
Nokia Research Center
© NOKIA cm architecture.PPT / 10.8.2003 / PHa page: 19
-end-