Demystifying Machine Intelligence: Why the Singularity is not Coming any Time Soon And Other Meditations on the Post-Human Condition and the Future of Intelligence. A more updated version can be found at www.scaruffi.com/singular

1. Demystifying
Machine Intelligence
Why the Singularity is not Coming any Time Soon
And other Meditations on the Post-Human Condition
and the Future of Intelligence
Being a 2013 book by
piero scaruffi

2. Sociological Overture
• Schopenhauer, Nietzsche, Russell, Hilbert
Turing: the search for infinite moves from
religion to math
• The Singularity as a new god-less religion
2

3. Limits of the A.I. program
• Focus on the brain, but what is a brain
without a body?
• Do machines grow up?
• Can machines evolve?
3

4. The curse of Moore’s law
• A lot of sophisticated logic-based software had to
do with slow and expensive machines
• The motivation to come up with creative ideas in
A.I. was due to slow, big and expensive machines.
• Brute force (100s of supercomputers running in
parallel) can find solutions using fairly dumb
techniques
• Actually, you can find the answer to most
questions by simply using a search engine: no
need to think, no need for intelligence
4

5. Connectionism
•
•
•
•
1950s: Neural networks
1980s: Boltzmann machines
2000s: Bayesian belief networks
Software based on vast knowledge bases and
Bayesian networks
–
–
–
–
beat the world champion of chess (Deep Blue)
beat champions of trivia (Watson)
recognized cats in youtube videos (Google)
drive cars (Google, BMW, Audi, Volkswagen, etc)
5

6. Reality Check
• Recognizing a cat is something that any
mouse can do (it took 16,000 computers
working in parallel)
• Driving a car involves more than just
sensors and a map
• Voice recognition and handwriting
recognition still fail most of the time,
especially in everyday interactions
6

7. Reality Check
• IBM's Watson does not understand the
question (it is fed in digital format)
• IBM’s "Deep Blue" beat a chess master but
was given unfair advantages
• “What Curiosity (robot) has done in 200
days a human field researcher could do in
an easy afternoon" (NASA planetary
scientist Chris McKay, 2013)
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8. Reality Check
• Machine translation in 2013 (random
sentences from my website translated by
Google):
– "Graham Nash the content of which led nasal
harmony“
– "On that album historian who gave the blues
revival“
– "Started with a pompous hype on wave of
hippie phenomenon"
8

9. Reality Check
• A remote-controlled toy is NOT a step
toward superhuman intelligence
• Human-looking automata that mimic human
behavior have been built since ancient times
• A human being is NOT a toy (yet)
9

10. Reality Check
• The brain of the roundworm (300
neurons connected by a few thousand
synapses) is still smarter than the
smartest neural network ever built.
10

11. Reality Check
• 60 years later it is not machines that learned
to understand human language but humans
who got used to speak like machines in
order to be understood by automated
customer support (and mostly not even
speak it but simply press keys)
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12. An easy science
• Artificial Intelligence is not subjected to the
same scrutiny as other sciences
• Its success stories are largely unproven
12

13. Exponential Progress?
• The jobs that have been automated are repetitive
and trivial.
• And in most cases the automation of those jobs
has required the user/customer to accept a lower
(not higher) quality of service.
• The more automation around you, the more you
(you) are forced to behave like a machine to
interact with machines
13

14. Exponential Progress?
• "Moore's law“ has been correct, but it is
about the hardware, not the software (the
“body”, not the “brain”)
14

15. A Comparative History of
Accelerating Progress
• One century ago, within a relatively short period
of time, the world adopted:
–
–
–
–
–
the car,
the airplane,
the telephone,
the radio
the record
• while at the same time science came up with
– Quantum Mechanics
– Relativity
15

16. A Comparative History of
Accelerating Progress
• while at the same time the office was
revolutionized by
– cash registers,
– adding machines,
– typewriters
• while at the same time the home was
revolutionized by
– dishwasher,
– refrigerator,
– air conditioning
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17. A Comparative History of
Accelerating Progress
• There were only 5 radio stations in 1921 but
already 525 in 1923
• The USA produced 11,200 cars in 1903, but
already 1.5 million in 1916
• By 1917 a whopping 40% of households had a
telephone in the USA up from 5% in 1900.
• The Wright brothers flew the first plane in 1903:
during World War I (1915-18) more than 200,000
planes were built
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18. A Comparative History of
Accelerating Progress
• On the other hand today…
– 44 years after the Moon landing we still haven't
sent a human being to any planet
– The only supersonic plane (the Concorde) has
been retired
– We still drive cars, fly on planes, talk in
phones, etc…
18

19. A Comparative History of
Accelerating Progress
We chronically underestimate progress in
previous centuries because most of us are
ignorant about those eras
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20. A Comparative History of
Accelerating Progress
• 3rd of april 1988 the Los Angeles Times
Magazine ran a piece titled "L.A. 2013“
– two robots per family (including cooking
and washing)
– Intelligent kitchen appliances widespread
– self-driving cars widespread
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21. A Comparative History of
Accelerating Progress
• Today there is a lot of change
• But change is not necessarily progress
• It is mostly fashion created by marketing
and/or planned obsolescence (progress for
whom?)
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22. Superhuman intelligence
• Possible: Colin McGinn’s cognitive closure
(there are things we will never understand)
• Impossible: David Deutsch’s endless
explanation (we are as intelligent as it gets)
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23. Decelerating Intelligence
• You are the tools you use
• Tools shape the brain
• What might be accelerating is the loss of
human skills
23

24. Decelerating Intelligence
1.
• The Turing Test was asking “when can machines be said
to be as intelligent as humans?”
• This “Turing point” can be achieved by
1. Making machines smarter, or
2. Making humans dumber
2. IQ
IQ
HOMO
MACHINE
HOMO
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MACHINE

25. Semantics
• It is not intelligent to talk about intelligent
machines: whatever they do is not what we
do, and, therefore, is neither "intelligent" nor
"stupid" (attributes invented to define human
behavior)
• We apply to machines many words invented
for humans simply because we don't have a
vocabulary for the states of machines
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26. Semantics
• Memory is reconstructive
• Data storage is not “memory”
• Exponentially increasing data storage does not mean better
memory
• What is “computer speed”?
• Who is faster at picking a cherry from a tree, the fastest
computer in the world or you?
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27. Non-human Intelligence
• Bats can avoid objects in absolute darkness at
impressive speeds
• Migratory animals can navigate vast territories
• Birds are equipped with a sixth sense for the
Earth's magnetic field
• Some animals have the ability to camouflage
• The best color vision is in birds, fish and insects
• Many animals have night vision
• Animals can see, sniff and hear things that we
cannot
27

28. Non-human Intelligence
• And don't underestimate the brain of an
insect either: how many people can fly and
land upside down on a ceiling?
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29. Non-human Intelligence
• Many animals have powers we don't have
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30. Non-human Intelligence
• We already built machines that can do
things that are impossible for humans:
– Telescopes and microscopes can see things that
humans cannot see
– We cannot do what light bulbs do
– We cannot touch the groove of a rotating vinyl
record and produce the sound of an entire
philharmonic orchestra
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31. Non-human Intelligence
• What is the difference between non-human
intelligence (which is already here and has
always existed) and super-human
intelligence?
31

32. Artificial General Intelligence
• Task-specific vs General-purpose
Intelligence
• Originally, A.I. was looking for generalpurpose intelligence
• Today’s A.I. is looking for task-specific
intelligence (recognizing a cat, driving a
car)
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33. Artificial General Intelligence
• How to simulate an average human (not just one
human task) - the “logic theorist” solution
(1960s): create a system that can perform
reasoning on knowledge and infer the correct
behavior for any situation
• How to simulate an average human (not just one
human task) - the brute force solution (2000s):
create one specific program/robot for each of the
millions of possible situations, and then millions
of their variants
33

34. Artificial General Intelligence
• Intelligent Behavior from Structured
Environments
• We structure the chaos of nature because it makes
it easier to survive and thrive in it
• The more we structure the environment, the easier
for extremely dumb people and machines to
survive and thrive in it.
• It is easy to build a machine that has to operate in
a highly structured environment
• What really "does it" is not the machine: it's the
structured environment
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35. Artificial General Intelligence
• The Multiplication of Appliances and Artificial
Intelligence by Enumeration
• We have machines that dispense money (ATMs),
machines that wash clothes (washing machines),
machines that control the temperature of a room
(thermostats), and machines that control the speed
of a car (cruise controls).
• We can build machines for all the other tasks and
then collectively call them “equal” to humans
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36. Artificial General Intelligence
• The enumeration problem: which human functions
qualify as "intelligent"?
• There are very human functions that people don't
normally associate with "intelligence". They just
happen to be things that human bodies do.
• Do we really want machines that fall asleep or
urinate?
• We swing arms when we walk, but we don't
consider "swinging arms while walking" a
necessary feature of intelligent beings.
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37. Tips for better A.I.
• IBM's Watson of 2013 consumes 85,000
Watts compared with the human brain's 20
Watts.
• The brain is an analog device, not digital
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38. Tips for better A.I.
• What we need: a machine that has only a
limited knowledge of all the chess games
ever played and is allowed to run only so
many logical steps before making a move
and can still consistently beat the world
champion of chess.
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39. Tips for better A.I.
• What conditions may foster a breakthrough:
it is not the abundance of a resource (such
as computing power or information) that
triggers a major paradigm shift but the
scarcity of a resource.
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40. Dangers of machine intelligence
• Who's Responsible for a Machine's Action?
• We believe machines more than we believe
humans
• Should there be speed limits for machines?
• We are criminalizing Common Sense
• You Are a Budget
• The dangers of clouding - Wikipedia as a
force for evil
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