Demystifying
Machine Intelligence
Why the Singularity is not Coming any Time Soon
And other Meditations on the Post-Human ...
Sociological Overture
• Schopenhauer, Nietzsche, Russell, Hilbert
Turing: the search for infinite moves from
religion to m...
Limits of the A.I. program
• Focus on the brain, but what is a brain
without a body?
• Do machines grow up?
• Can machines...
The curse of Moore’s law
• A lot of sophisticated logic-based software had to
do with slow and expensive machines
• The mo...
Connectionism
•
•
•
•

1950s: Neural networks
1980s: Boltzmann machines
2000s: Bayesian belief networks
Software based on ...
Reality Check
• Recognizing a cat is something that any
mouse can do (it took 16,000 computers
working in parallel)
• Driv...
Reality Check
• IBM's Watson does not understand the
question (it is fed in digital format)
• IBM’s "Deep Blue" beat a che...
Reality Check
• Machine translation in 2013 (random
sentences from my website translated by
Google):
– "Graham Nash the co...
Reality Check
• A remote-controlled toy is NOT a step
toward superhuman intelligence
• Human-looking automata that mimic h...
Reality Check
• The brain of the roundworm (300
neurons connected by a few thousand
synapses) is still smarter than the
sm...
Reality Check
• 60 years later it is not machines that learned
to understand human language but humans
who got used to spe...
An easy science
• Artificial Intelligence is not subjected to the
same scrutiny as other sciences
• Its success stories ar...
Exponential Progress?
• The jobs that have been automated are repetitive
and trivial.
• And in most cases the automation o...
Exponential Progress?
• "Moore's law“ has been correct, but it is
about the hardware, not the software (the
“body”, not th...
A Comparative History of
Accelerating Progress
• One century ago, within a relatively short period
of time, the world adop...
A Comparative History of
Accelerating Progress
• while at the same time the office was
revolutionized by
– cash registers,...
A Comparative History of
Accelerating Progress
• There were only 5 radio stations in 1921 but
already 525 in 1923
• The US...
A Comparative History of
Accelerating Progress
• On the other hand today…
– 44 years after the Moon landing we still haven...
A Comparative History of
Accelerating Progress
We chronically underestimate progress in
previous centuries because most of...
A Comparative History of
Accelerating Progress
• 3rd of april 1988 the Los Angeles Times
Magazine ran a piece titled "L.A....
A Comparative History of
Accelerating Progress
• Today there is a lot of change
• But change is not necessarily progress
•...
Superhuman intelligence
• Possible: Colin McGinn’s cognitive closure
(there are things we will never understand)
• Impossi...
Decelerating Intelligence
• You are the tools you use
• Tools shape the brain
• What might be accelerating is the loss of
...
Decelerating Intelligence

1.

• The Turing Test was asking “when can machines be said
to be as intelligent as humans?”
• ...
Semantics
• It is not intelligent to talk about intelligent
machines: whatever they do is not what we
do, and, therefore, ...
Semantics
• Memory is reconstructive
• Data storage is not “memory”
• Exponentially increasing data storage does not mean ...
Non-human Intelligence
• Bats can avoid objects in absolute darkness at
impressive speeds
• Migratory animals can navigate...
Non-human Intelligence
• And don't underestimate the brain of an
insect either: how many people can fly and
land upside do...
Non-human Intelligence
• Many animals have powers we don't have

29
Non-human Intelligence
• We already built machines that can do
things that are impossible for humans:
– Telescopes and mic...
Non-human Intelligence
• What is the difference between non-human
intelligence (which is already here and has
always exist...
Artificial General Intelligence
• Task-specific vs General-purpose
Intelligence
• Originally, A.I. was looking for general...
Artificial General Intelligence
• How to simulate an average human (not just one
human task) - the “logic theorist” soluti...
Artificial General Intelligence
• Intelligent Behavior from Structured
Environments
• We structure the chaos of nature bec...
Artificial General Intelligence
• The Multiplication of Appliances and Artificial
Intelligence by Enumeration
• We have ma...
Artificial General Intelligence
• The enumeration problem: which human functions
qualify as "intelligent"?
• There are ver...
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...
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...
Tips for better A.I.
• What conditions may foster a breakthrough:
it is not the abundance of a resource (such
as computing...
Dangers of machine intelligence
• Who's Responsible for a Machine's Action?
• We believe machines more than we believe
hum...
41
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Demystifying Machine Intelligence

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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

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Demystifying Machine Intelligence

  1. 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. 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. 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. 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. 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. 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. 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) 7
  8. 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. 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. 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. 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) 11
  12. 12. An easy science • Artificial Intelligence is not subjected to the same scrutiny as other sciences • Its success stories are largely unproven 12
  13. 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. 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. 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. 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 16
  17. 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 17
  18. 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. 19. A Comparative History of Accelerating Progress We chronically underestimate progress in previous centuries because most of us are ignorant about those eras 19
  20. 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 20
  21. 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?) 21
  22. 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) 22
  23. 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. 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 24 MACHINE
  25. 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 25
  26. 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? 26
  27. 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. 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? 28
  29. 29. Non-human Intelligence • Many animals have powers we don't have 29
  30. 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 30
  31. 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. 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) 32
  33. 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. 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 34
  35. 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 35
  36. 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. 36
  37. 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 37
  38. 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. 38
  39. 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. 39
  40. 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 40
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