How do you compare the intelligence of different systems, solutions and AI configurations. Multiplying nodes and interconnects gives the wrong answer as growth is logarithmic and not linear.

1. What Do Machines Think?
Peter Cochrane
www.ca-global.org
COCHRANE
a s s o c i a t e s

2. The problem ?
* How do you compare complex man made systems ?
* How do you compare solution efficacy ?
* How do you minimise risk, maximise success ?
* Mission critical - lives at risk - we have to move fast!

3. The key questions ?
* What is intelligence ?
* Can it be quantified ?

4. The answer !
Ic ~ k log2[1 + KAS ( 1 + PM )]
S = Sensor, A = Actuator, P = Processor, M = Memory
Relative Intelligence = Ic
Flops (or machine cycles)
Observations:
With zero processor power intelligence is still possible
With zero memory power intelligence is still possible
With zero sensor and/or actuator power intelligence is impossible

5. Key conclusion:
Intelligence grows logarithmically and not linearly !
The singularity event isn’t going to happen just yet !
The assumption that is is is based on I ~ PM growth looks to be wrong
Kurzweil et al

6. Two wisdoms from my past !
“Whilst it is acceptable for the mathematicians,
physicists and theorists to declare that there is no
solution, we in engineering enjoy no such luxury. We
always have to find a solution” !
“Before you even start a problem it is worth thinking
what form the answer might be, and what would be
reasonable”

7. Where did my thinking start ?

8. Where did my thinking start ?
…in a Spanish gutter/drain!

9. Where did my thinking start ?
…in a Spanish gutter/drain!

10. Where did my thinking start ?
…in a Spanish gutter/drain!

11. Where did my thinking start ?
…in a Spanish gutter/drain!
…plus amateur robotics!

12. Where did my thinking start ?
…in a Spanish gutter/drain!
…plus amateur robotics!

13. Where did my thinking start ?
…in a Spanish gutter/drain!
…plus amateur robotics!

14. And then I got into the logistics of people,
goods and traffic...and the traveling
salesman problem...

15. ...and so I progressed to ‘wet science’ with
genetics & sexual reproduction
migrating into machines...

16. SO, I’m going to ask you to
suspend all preconceptions,
and beliefs...

17. SO, I’m going to ask you to
suspend all preconceptions,
and beliefs...
Because we have to take the wider
view, to be receptive...as we are
mostly flying blind...
...although there is a growing body
of fundamental knowledge
and evidence...

18. Science fiction & Hollywood are mostly
apocalyptic on the topic:

19. Science fiction & Hollywood are mostly
apocalyptic on the topic:

20. Science fiction & Hollywood are mostly
apocalyptic on the topic:

21. Science fiction & Hollywood are mostly
apocalyptic on the topic:

22. Science fiction & Hollywood are mostly
apocalyptic on the topic:
…but the reality is quite different..so far!

23. Azimov’s Laws or Robotics
Zeroth Law (1985):
A robot may not injure humanity, or, through inaction, allow humanity to come to
harm
First Law (1940):
A robot may not injure a human being, or, through inaction, allow a human being to
come to harm, unless this would violate the Zeroth Law of Robotics
Second Law (1940):
A robot must obey orders given it by human beings, except where such orders
would conflict with the Zeroth or First Law
Third Law (1940):
A robot must protect its own existence as long as such protection does not conflict
with the Zeroth, First, or Second Law

24. Azimov’s Laws or Robotics
Zeroth Law (1985):
A robot may not injure humanity, or, through inaction, allow humanity to come to
harm
First Law (1940):
We have chosen not to invoke these laws
A robot may not injure a human being, or, through inaction, allow a human being to
come to harm, unless this would violate the Zeroth Law of Robotics
Second Law (1940):
We have also opted to violate them
A robot must obey orders given it by human beings, except where such orders
would conflict with the Zeroth or First Law
Third Law (1940):
A robot must protect its own existence as long as such protection does not conflict
with the Zeroth, First, or Second Law

25. Some realities:
GOOD NOT SO GOOD

26. Some realities:
GOOD NOT SO GOOD

27. Some realities:
GOOD NOT SO GOOD

28. Some realities:
GOOD NOT SO GOOD

29. Some realities:
GOOD NOT SO GOOD

30. Some realities:
GOOD NOT SO GOOD

31. Some realities:
GOOD NOT SO GOOD

32. Some realities:
GOOD NOT SO GOOD

33. Some realities:
GOOD NOT SO GOOD

34. Some realities:
GOOD NOT SO GOOD

35. Some realities:
GOOD NOT SO GOOD

36. Some realities:
GOOD NOT SO GOOD
…so far we have been in control....!

37. The big question =
Is there a big upside ?
Or even a silver lining ?
YES - one BIG example
now and a few more later

38. Futures
Advance
Society
Technology
Wealth
Health
Well Being
Time

39. Futures
Advance
Society
Technology
Wealth
Health
Well Being
Oil runs out
We do nothing
Planet retaliates
Life dies
Time

40. Futures
Advance
Society
Technology
Wealth Our green effort works
Health & status quo just holds
Well Being
Oil runs out
We do nothing
Planet retaliates
Life dies
Time

41. Cold Fusion
Futures Climatic Control
Advance Earth Management
Nano - Bio Tech
Society AI + AL +++
Technology
Wealth Our green effort works
Health & status quo just holds
Well Being
Oil runs out
We do nothing
Planet retaliates
Life dies
Time

42. Cold Fusion
Futures Climatic Control
Advance Earth Management
Nano - Bio Tech
Society AI + AL +++
Technology
Our climate and planet models are
Wealth Our green effort works
so crude that we have&no real clue
Health status quo just holds
about which trajectory we are on
Well Being
…..and if we can influence itout
Oil runs anyway!
We do nothing
Planet retaliates
Life dies
Time

43. Everything in the universe is
governed by non-linearity and
chaotic actions….

44. Everything in the universe is
governed by non-linearity and
chaotic actions….
…but we are linear and
limited thinkers devoid
of tools & techniques to
help us comprehend…

45. Everything in the universe is
governed by non-linearity and
chaotic actions….
…but we are linear and
limited thinkers devoid
of tools & techniques to
help us comprehend…
If we have a long-term future it lies with our
technology and machines and their ability to
extend our knowledge & understanding.

46. If we switched off our
machines today….

47. If we switched off our
machines today….
…this lonely isolated
planet would support
< 1 Bn people

48. If we switched off our
machines today….
…this lonely isolated
planet would support
< 1 Bn people
Our total dependence on technology for the
survival of our species is long established &
will not go away, in fact, it continues to grow!

49. No human leader, past and present, future has
the wisdom & ability to govern a chaotic planet!

50. No human scientist, past and present, future has
the wisdom & ability to understand a chaotic planet!

51. Hypothesis
The combined
intelligence of
all humanity is
also insufficient

52. Hypothesis
Our only hope is
The combined
the combined
intelligence of
intelligence
all humanity is
of also insufficient
our machines

53. Definition - Think?

54. Definition - Think?
• Judge or regard
• Imagine or visualise
• Mental preoccupation
• Expect, believe, suppose
• Have in mind as a purpose
• Make inferences, decisions
• Reflect on, or reason about
• Decide by reasoning/reflecting
• Exercise one's power of reason
• Recall knowledge from memory
• Arrive at a solution or judgments
• Be capable of conscious thought
• Dispose the mind in a certain way
• Bring into a given mental condition

55. Definition - Think?
• Judge or regard
• Imagine or visualise
• Mental preoccupation
• Expect, believe, suppose
• Have in mind as a purpose
• Make inferences, decisions
• Reflect on, or reason about
• Decide by reasoning/reflecting
• Exercise one's power of reason
• Recall knowledge from memory
• Arrive at a solution or judgments
• Be capable of conscious thought
• Dispose the mind in a certain way
• Bring into a given mental condition

56. Definition - Think?
• Judge or regard
• Imagine or visualise ??
• Mental preoccupation
• Expect, believe, suppose ??
• Have in mind as a purpose
• Make inferences, decisions
• Reflect on, or reason about
• Decide by reasoning/reflecting
• Exercise one's power of reason
• Recall knowledge from memory
• Arrive at a solution or judgments
• Be capable of conscious thought ??
• Dispose the mind in a certain way ??
• Bring into a given mental condition

57. What do we know?
Thinking is an electro-chemical
process...
...influenced by experience and
memory, emotions, external and
internal conditions, plus sensory
system, actions and inaction
Other ‘thinking life forms’ are
considerably simpler!

58. Words that lack any full
or adequate description,
definition, quantification,
measure or meaning...

59. Words that lack any full
or adequate description,
definition, quantification,
measure or meaning...
• Life
• Intelligence
• Complexity
• Scaleability
• Value
• Think(ing)

60. Without adequate description,
definition, quantification, then
meaningful discussion is very
limited & we soon descend
into the realms of belief and
folk law + superstition...
So far our only successful
route to understanding has
been the application of the
scientific method

61. Not fully understanding
something doesn’t imply
we cannot exploit it!

62. Not fully understanding
something doesn’t imply
we cannot exploit it!
Ballistics
Newton Einstein
Linear Non-Linear

63. The scientific method is the most powerful tool
of understanding we have developed so far…
..but it never does, and will never do this!

64. Do machines think good
or bad thoughts?
We have empowered them
to do both
We are responsible for their
initiation - their starting point
Evolution will take care of history

65. Our view of technology…

66. Our view of technology…
My Grandfather: Man will never fly

67. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon

68. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:

69. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess

70. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative

71. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us

72. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us
- become intelligent

73. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us
- become intelligent
- become self aware

74. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us
- become intelligent
- become self aware
- live, etc

75. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us
- become intelligent
- become self aware
- live, etc
My View: These are all worthless & irrelevant statements

76. Our view of technology…
My Grandfather: Man will never fly
My Father: Man will never walk on the moon
My Generation: Computers will never:
- win at chess
- be creative
- smarter than us
- become intelligent
- become self aware
- live, etc
My View: These are all worthless & irrelevant statements
mainly born of fear and ignorance

77. Garry Kasporov...1997
Machines (IBM Big Blue)
don’t play chess like us....

78. Garry Kasporov...1997
Machines (IBM Big Blue)
don’t play chess like us....
...and this is precisely why
machines can add so much
value....and understanding!

79. We now live in a world of the infinitely complex…
… how do you solve problems & make decisions?

80. We now live in a world of the infinite…
… how do you find and how do you choose?

81. No one knows anything anymore...
highly specialised
becoming all knowledge
the fount
specialised through
of all
knowledge technology
1800 1900 TODAY 2000 +

82. We have come to the end(ish) of the road… …
and we aint going to get any smarter!

83. Viagra & chips for the brain

84. The only solutions on the horizon:
A symbiotic relationship with our machines?
A new intelligence/s and/or life form/s?

85. Some of us see the route to AI & AL through the
direct imitation of mother nature & her already
solved problems…

86. Some of us see the route to AI & AL through the
direct imitation of mother nature & her already
solved problems…

87. And then there are…
…the hybrid solutions
.…combining man and machine

88. Why do we see see technology as a threat…
…and remain complacent about this stuff?

89. After 1.8Bn years
we still can’t…
…adequately describe,
define, quantify or
understand intelligence

90. And despite the dire warnings
about the limitations of his
test and the way it can be
applied it is still used today as
if it were actually useful!

91. Today ! IQ = Solving problems
Power = Connectivity +
neuron count
Speed = Task completion

92. Today ! IQ = Solving problems
Power = Connectivity +
neuron count
Speed = Task completion

93. Sometimes we have to
make giant conceptual,
and questionable leaps to
get to a solution...
...and better to get a
good approximation, or
even the wrong
answer, than no answer
at all !

94. A valuable engineering precept: If there is
no theor y and proof, or no
understanding - any solution will do - so
long as we make a start...

95. Approach

96. I start by doing a Dr Johnson
and define intelligence!
“And intelligence is the way I
define it and no one else”
Samuel Johnson (1709-1784)
Johnson was an English writer and critic, and
My misquote!
one of the most famous literary figures of the
18th century. His best-known work is his
'Dictionary of the English Language

97. And I don’t mean wordy descriptions of
the form...
“The faculty of rational behaviour”
“An ability to create order out of chaos”

98. Also, recognise that we often have difficulty
discerning what is intelligent and what isn’t!
Random scatter Wind action Wind action ? Very unlikely ?
for sure ? or a Intelligent action most likely
leaf blower ?

99. Also, recognise that we often have difficulty
discerning what is intelligent and what isn’t!
Observation: Intelligent intervention can prevent or even
reverse the natural process of entropy within a system.
All natural systems seek to find the lowest energy
state - ie they migrate from order to disorder - the
universe started as a point function and then expanded
Random scatter Wind action Wind action ? Very unlikely ?
for sure ? is the celestial ratchet - it only ever gets
Entropy or a Intelligent action most likely
bigger - and is leaf blower ?
the mechanism by which we die!

100. This could never occur by random action,
it definitely involves intelligence!

101. We are actually dealing the transformation of
information ...
Intelligence can thus be taken (Because I say so!) as
the efficiency and efficacy by which that process is
completed.
This automatically infers an entropic quality:
Intelligence = Entropy of Input - Entropy of Output
& Efficacy of Course

102. This would not be a good answer !
Answer to the Ultimate Question of Life, the Universe, and Everything from the supercomputer,
Deep Thought, specially built for this purpose. It takes Deep Thought 7½ million years to compute
and check the answer, which turns out to be 42. Unfortunately, The Ultimate Question itself is
unknown.
Douglas Adams: The Hitchhikers Guide to The Universe

103. Because intelligent systems can both increase or
decrease the total Information/Entropy, we
define...

104. Because intelligent systems can both increase or
decrease the total Information/Entropy, we
define...
Intelligence = I = MOD { Ei - Eo } = I Ei - Eo I

105. Because intelligent systems can both increase or
decrease the total Information/Entropy, we
define...
Intelligence = I = MOD { Ei - Eo } = I Ei - Eo I
Where the Entropy E = The amount of information
required to exactly define
the state of a system

106. At a very basic level an intelligent
system could take the form...
Sensors Processor
S P1
System Memory
Environs M
Actuator Processor
A P2

107. But recognise that they can often be
a whole lot more complex...
Processor
Sensors
S1 P1 Memory
Mlong
Memory
System
Environs
M
Memory short
Mlocal
Actuator Processor
A1 P1
A

108. Eyes of all kinds often do
a lot of pre processing

109. And you don’t put all the brains in the
head of a dog or a human!

110. Back to the plot!

111. This is a tough enough problem for now!
Sensors Processor
S P1
System Memory
Environs M
Actuator Processor
A P2

112. Assuming the following nomenclature....
si p1 si
Sensors . Processor
P1 .
i S
System Memory
Environs M
Actuator Processor (1 + m) p1 si
o A P2
a(1 + m + p1 p2 + p2 m p1 ) si
(1 + m + p1 p2 + p2 m p1 ) si
Where: s, p ,m, a are complex operators

113. And with our very simplistic model we
deduce that...

114. And with our very simplistic model we
deduce that...
Ic = I Ei - Eo I = I Ei - E( a[(1 + m + p1 p2 + p2 m p1 ) si I

115. And with our very simplistic model we
deduce that...
Ic = I Ei - Eo I = I Ei - E( a[(1 + m + p1 p2 + p2 m p1 ) si I
Where: a, p ,m, s are all complex operators

116. And for a very simplistic model where
normalise complex operators, and
combine processing and memory types
we deduce that...

117. And for a very simplistic model where
normalise complex operators, and
combine processing and memory types
we deduce that...
Ic = I Ei - Eo I = I Ei - E[a.s ( 1 + m + p + mp ) ] I

118. And for a very simplistic model where
normalise complex operators, and
combine processing and memory types
we deduce that...
Ic = I Ei - Eo I = I Ei - E[a.s ( 1 + m + p + mp ) ] I
Where: a, p ,m, s are all complex operators

119. After some mathematical
juggling and normalisation,
liberties, crimes, & of course
engineering licence...
Processor Memory
∝ log [1 + S. A (1 + P + M + P.M ) ]
I 2
Sensor Actuator

120. And finally, something we can work with:
Ic = k log2 [1 + K.S.A (1 + P + M + P.M ) ]
System Constants
For P.M >> (P + M)
Ic ~ k log2 [1 + K.S.A (1 + P.M ) ]
Relative Intelligence k log2 [1 + K.S.A (1 + P.M ) ]
=
of different systems Flops (or machine cycles)

121. Key Implication !
If I am correct:
We are not racing toward a
singularity as fast as people
have projected

122. Key Implication !
If I am correct:
We are not racing toward a
singularity as fast as people
have projected
Increasing S. P. M. A by a
factor of 1000 would only
see intelligence grow 10
fold !

123. log2 Intelligence growth
Intelligence
40
multiple
30
20
10
S. P. M. A
1
1 103 106 109 1012 1015 1018

124. log2 Intelligence growth
Intelligence
40
multiple
30
20
10
S. P. M. A
1
1 103 106 109 1012 1015 1018

125. Remember - many systems are far far
more complex than I have assumed
Processor Memory
Sensors
1 ShortTerm
System
Environs
Processor Memory
Actuator
2 LongTerm
...and this may defeat a full mathematical development &
leave us with nothing more than a mere ‘rule of thumb’
understanding of the influencers of intelligence!

126. So why isn’t my laptop intelligent?

127. So why isn’t my laptop intelligent?
How about:
- sensors?
- adaptability?

128. But we are rolling out intelligent sensors!

129. But we are rolling out intelligent sensors!
And our machines will see, hear, smell….
…detect and communicate in a way and
at a rate we cannot!

130. Life today!
Processing
Carbon = Silicon
Memory
Carbon = Silicon
Comms
Carbon < Silicon
Sensors
Carbon >> Silicon

131. What can we do with AI & AL now?

132. What can we do with AI & AL now?

133. Genetically ~99.4% human

134. Genetically ~99.4% human
If ~0.6%
matters
so much…
no wonder
IT systems
are so dumb!

135. In conclusion!
Understanding non-linear systems
presents us with our biggest & most
important challenge & opportunity

136. In conclusion!
Understanding non-linear systems
presents us with our biggest & most
important challenge & opportunity
Whatever advance and advantage we
have enjoyed through linear models,
thinking, and endeavours, will be totally
eclipsed by a move into the realm of non-
linearity
P Cochrane 1995

137. A world of great challenges and even
greater opportunities….
Thank you,
cochrane.org.uk
ca-global.org
COCHRANE
a s s o c i a t e s