The document discusses artificial intelligence and argues that the field is progressing more slowly than predicted. It makes four main points: 1) Recent AI accomplishments like image recognition and AlphaGo are narrow and rely on large datasets and computational power rather than true intelligence. 2) Progress in AI has not accelerated as much as claimed and past eras saw similar revolutionary changes in technology. 3) Claims of soon achieving superhuman AI are dubious as many animals already demonstrate abilities beyond humans. 4) Machines have long been able to perform tasks humans cannot, but near future AI will focus more on applications like consumer products, healthcare, and jobs rather than general human-level intelligence.

1. Intelligence
is not Artificial
piero scaruffi
www.scaruffi.com
April 2016
"The person who says it cannot be done should not
interrupt the person doing it" (Chinese proverb)

2. Piero Scaruffi
• piero scaruffi
p@scaruffi.com
www.scaruffi.com
Olivetti AI Center, 1987

3. 3
What I am going to tell you
Journalist: Are you afraid of A.I.?
Piero: I am afraid that it will not come
soon enough!

4. Table of Contents
1. From the electronic brain to AlphaGo
2. Why the Singularity is not coming any time soon
3. The near Future of A.I.
4

5. 55
Electronic Brains
1946: The first non-military computer, ENIAC, or
"Electronic Numerical Integrator and Computer",
is unveiled, built by John Mauchly and Presper
Eckert at the University of Pennsylvania

6. 66
Electronic Brains
Computation

7. 77
Electronic Brains
Computation

8. In the beginning…
Artificial Intelligence (1956)
• Knowledge-based approach uses
mathematical logic to simulate human
intelligence
• Neural-net approach simulates the
structure of the brain
8

9. 9
The #1 factor: Moore’s Law
The future of your brain is coming faste
than your brain can think…

10. The Age of Deep Learning
1997: Sepp Hochreiter's LSTM
1998: Yann LeCun 's second
generation Convolutional Neural
Networks
2006: Geoffrey Hinton’s Geoffrey
Hinton's Deep Belief Networks
2007: Yeshua Bengio's Stacked Auto-
Encoders
Deep
Learning

11. The Age of Deep Learning
Hava Siegelmann: Israel
Sepp Hochreiter‘: Germany
Yann LeCun: France
Geoffrey Hinton: Britain
Yeshua Bengio: France
Andrew Ng: China

12. 12
2010s
• Google (2012): 1.7 billion connections
(and 16,000 processors) learn to
recognize cats in YouTube videos
12

13. 13
2010s
• The personal assistant
– Apple Siri (2011)
– GoogleNow (2012)
– Microsoft Tay (2016)
– …
Apple 2011
Stanley Kubrick (1968)
“2001: A Space Odyssey”
(mandatory Hollywood
movie for AI presentation)
Microsoft,2016

14. 14
2010s
• Automatic translation

15. 15
2010s
• Auto-tagging and image caption
15

16. 16
2010s
2015: Microsoft’s 152-layer neural network

17. 17
2010s
• Multi-billion dollar investments in artificial
intelligence and robotics
– Amazon (Kiva, 2012)
– Google (Neven, 2006; Industrial Robotics, Meka,
Holomni, Bot & Dolly, DNNresearch, Schaft,
Bost, DeepMind, Redwood Robotics, 2013-14)
– IBM (AlchemyAPI, 2015; Watson project)
– Microsoft (Project Adam, 2014)
– Apple (Siri, 2011; Perceptio and VocalIQ, 2015;
Emotient, 2016)
– Facebook (Face.com, 2012)
– Yahoo (LookFlow, 2013)
– Twitter (WhetLab, 2015)
– Baidu (Deep Learning Inst in Cupertino, 2013)
17

18. 18
2010s
• DeepMind (2010): machine learning
(acquired by Google in 2014)
• Vicarious: machine learning
• Sentient: machine learning
• Wise.io
• Saffron
• Narrative Science
• …
18

19. 19
2010s
• Computer Go/Weichi
– 2009: Fuego Go (Monte Carlo program by Univ.
of Alberta) beats Zhou Junxun
– 2010: MogoTW (Monte Carlo program
developed in 2008 by a Euro-Taiwanese team)
beat Catalin Taranu
– 2012: Tencho no Igo/ Zen (Monte Carlo program
developed by Yoji Ojima in 2005) beat Takemiya
Masaki
– 2013: Crazy Stone (Monte Carlo program by
Remi Coulom in 2005) beat Yoshio Ishida
– Pachi (open-source Monte Carlo program by Petr
Baudis)

20. 20
2010s
2016: Google/DeepMind’s AlphaGo beats the
weichi champion Se-dol Lee

21. 21
Robots

22. 22
The Singularity?
The four assumptions of the Singularity
movement
1. Artificial Intelligence systems are
producing mindboggling results
2. Progress is accelerating like never before
3. For the first time we will have to deal with
super-human intelligence
4. For the first time we will have machines
that can do things that humans cannot do
22

23. 23
The Singularity?
1
Artificial Intelligence systems are
producing mindboggling results

24. 24
1. Reality Check
• The curse of Moore’s law
– 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
– Moore’s Law is ending (Intel’s announcement
2016)

25. 25
Reality Check
• Recognizing a cat is something that
any mouse can do (it took 16,000
computers working in parallel)
• It took 1.2 million human-tagged
images for Deep Learning to lower
the error rate in image recognition
• Voice recognition and handwriting
recognition still fail most of the time,
especially in everyday interactions

26. 26
Reality Check
• DeepMind’s AlphaGo
– Supervised learning
– Large dataset of 150,000 games
– Monte Carlo tree search
– Reinforcement learning (playing against
itself)

27. 27
Reality Check
• DeepMind’s AlphaGo
– What else can AlphaGo do besides playing
Go? Absolutely nothing.
– What else can you do besides playing Go?
– What AlphaGo did: it learned from Go
experts
– AlphaGo consumed 440,000 W to do just
one thing
– Your brain uses 20 W and does an infinite
number of things

28. 28
Reality Check
• DeepMind’s AlphaGo
– Let both the human and AlphaGo run on
20 Watts and see who wins.
A 20 Watt machine of 1915
A 440,000 Watt machine of 2015

29. 29
Reality Check
Supervised learning
• Learning by imitation
• Only as good as the expert that you
imitate
• The learned skills cannot be applied to
other fields

30. 30
Reality Check
• Limitations of image recognition
– 2013 (Google + New York Univ + UC
Berkeley): tiny perturbations alter the way
a neural network classifies the image
The difference is invisible to humans, but enough to fool a neural network

31. 31
Reality Check
• Structured Environment
– The more we structure the environment, the
easier for extremely dumb people and
machines to survive and thrive in it.
– What really "does it" is not the machine: it's
the structured environment

32. 32
The Singularity?
2
Progress has never accelerated so much

33. 3333
2. 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
– Cinema
• while at the same time science came up with
– Quantum Mechanics
– Relativity

34. 3434
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

35. 3535
Accelerating progress?
• while at the same time cities adopted high-rise
buildings

36. 3636
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

37. 37
The Singularity?
3
For the first time we’ll have to deal with
super-human intelligence

38. 38
3. Non-human Intelligence
• Super-human intelligence has been around for a
long time: many animals have powers we don't
have

39. 39
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

40. 40
The Singularity?
4
For the first time we will soon have machines
that can do things that humans cannot do

41. 41
4. Machine 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

42. 42
Super-human Machine Intelligence
• The medieval clock could already do
something that no human can
possibly do: keeping time
• That’s why we have to ask “What
time is it?”

43. The Singularity?
• The four assumptions are dubious at best
43

44. 44
Decelerating Human Intelligence?
Journalist: Are you afraid of Artificial
Intelligence?
Piero: I am afraid of Human Stupidity

45. 45
The Turing Point
• 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
HOMO MACHINE
IQ
HOMO MACHINE
IQ
1. 2.

46. 46
The near Future of
Artificial Intelligence
"The person who says it cannot be done should not
interrupt the person doing it" (Chinese proverb)

47. 47
The near future…
• Today’s #1 application of A.I.: to make people buy
things that they don’t need
• Tomorrow’s #1 application of A.I.: to make people
buy things that they don’t need (and that sometimes
kill you)
Wei Zexi’s parents (2016)

48. 48
The near future…
• Where A.I. is truly successful…
– "The best minds of my generation are thinking
about how to make people click ads" (former
Facebook research scientist Jeff Hammerbacher
in 2012)
– So far A.I. has not created better doctors or
engineers, but better salesmen

49. 49
The near future
• Toys: many robots are an evolution of Pinocchio,
not of Shakey

50. 50
The near future
• Service Robots

51. The near future
51
Knightscope's K5 robot
security guard at the Stanford
Shopping Center (2016)
Savioke's robot concierge Botlr
at the Aloft hotel in Cupertino
(2016)
Simbe's robot clerk Tally at a
Target store in San Francisco
(2016)

52. 52
The near future
• A new class of appliances
Chef robot (2015)
BioBeats (2016): app
that takes data from
several wearables and
uses A.I. to deliver
health advice.
Smart Tissue Autonomous Robot
(Peter Kim , Washington, 2016)

53. 53
The near future
• Robots for an aging society (social
companion robots)

54. 54
The near future
• Robots for dangerous jobs (explosives, radioactive
areas, other planets)

55. 55
A little later in time…
• Industry-specific virtual assistants
• Chatbots that replace search engines
• Face-reading algorithms: detecting human
emotion (eg Emotient)

56. 56
A little later in time…
• Analysis of medical images: X-Rays,
MRIs, Computed Tomography (CT), etc
– Philips Health Care: 135 billion
medical images, 2 million new images
every week
– Helping radiology, cardiology and
oncology departments understand
images

57. 57
A little later in time…
• Robots
– Knowledge sharing among machines (eg
Open Ease, RoboBrain)
– Robots that can turn high-level
descriptions into specific actions (eg
RoboHow)
– Learning from human demonstrations and
advice, not just by imitation (eg
RoboBrain)

58. 58
A little later in time…
• Progress in fundamental A.I.
– Deep reinforcement learning (DeepMind,
Osaro)
– Common sense - knowledge-based
reasoning
• Doug Lenat’s Cyc (1984)
• Catherine Havasi’s Open Mind Common
Sense (1999)
• Google’s Knowledge Graph
• Microsoft’s Satori

59. 59
The next breakthroughs
• Transfer learning: transfer knowledge across tasks
• Multitasking
• Adaptation

60. 60
The next breakthrough
• Progress in fundamental A.I.
– Common sense
Children form a
human arrow to
direct a helicopter
towards the suspects
(Enland, April 2016)

61. 61
Beware of…
• Machine Learning as a tool for better forecasting
• Driver-less cars = brain-less cars
• Smart appliances that try to understand your habits
and customize your experience
• Intelligent agents “who” sift through strategic
information
• Chatbots that try to be funny
• Cyber-attacks

62. 62
Information-based System
Data
Base
Who is the
president of
the USA?
Where is
Rome?
OBAMA
ITALY

63. 63
Knowledge-based System
Know
ledge
Base
Who will the
president of
the USA?
Where is
Atlantis?
X
Y

64. 64
Don’t be afraid of the robot
• AI systems "don't have the intentionality, really,
even of an insect“ (Rodney Brooks)

65. 65
Don’t be afraid of the robot
• We need AI soon.
• The society of robots will create new jobs that
today we can’t even imagine.
• Who would have imagined that the same
technology that gave us computer automation
would create millions of jobs in mobile
communications?

66. 66
Don’t be afraid of the robot
• Robots will create an even more complex
society in which human intelligence will be
even more important.
• The future always surprises us.

67. 67
Journalist: Are you afraid of A.I.?
Piero: I am afraid that it will not come
soon enough!

68. The robots are coming!
The robots are coming!
piero scaruffi
www.scaruffi.com
April 2016
"The person who says it cannot be done should not
interrupt the person doing it" (Chinese proverb)
Ningbo Robotop conference, June 2016

69. 69
The End (for now)
"Computers are useless: they can only
give you answers“
(Pablo Picasso)
p@scaruffi.com
www.scaruffi.com