predictions and hard problems with ai
TRANSCRIPT
Rakuten Technology Conference, Tokyo, October 28, 2017
Laurent Ach
Manager of Rakuten Institute of Technology Paris
CTO PriceMinister - Rakuten
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• GIZMODO, article by George Dvorsky, Oct. 18, 2017, http://bit.ly/2gtk1S2
• VentureBeat, article by John Brandon, Oct. 2, 2017, http://bit.ly/2xLJoFl
• The Sun, article by James Beal and Andy Jehring, Aug. 1, 2017, http://bit.ly/2w0fVUq
• Mirror, article by Louise Sassoon, Aug. 1, 2017, http://bit.ly/2whUI7G
• TECH TIMES, article by Aaron Mamiit, Jul. 30, 2017, http://bit.ly/2wdoH0A
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Ray Kurzweil
Nick Bostrom
Intelligence explosion (I.J. Good, 1965)
Consulted by S. Kubrick for 2001: A Space Odyssey (1968)
Science fiction movies become reality… at least in predictions!
2006: The Singularity Is Near (Ray Kurzweil)
2014: SuperIntelligence (Nick Bostrom)
Stanley Kubrick
• Ray Kurzweil picture by Ed Schipul [CC BY-SA 2.0], via Wikimedia Commons
• Nick Bostrom picture by Future of Humanity Institute [CC BY-SA 4.0], via Wikimedia Commons
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Inte
llig
en
ce
(w
ait, w
ha
t?)
Time
Human Intelligence
Artificial Intelligence
Artificial General Intelligence
Artificial Super Intelligence
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Brain as Hardware? Mind as Software?
• Digicomp picture by Pterre [CC BY-SA 3.0 or GFDL], via Wikimedia Commons
• Punched card picture by Mutatis mutandis [GFDL, CC-BY-SA-3.0 or CC BY 2.5], via Wikimedia Commons
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Confirm action
Are you sure you want to upload your mind to this computer?
?
Warn me when I attempt to upload my mind
Cancel Upload
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Super Intelligent machines in conflict with Humans
or
Stupid machines, with too much decision power
“[…] we fight to make the machine slightly more intelligent, but they are still so stupid.
[…] The thing I’m more worried about, in a foreseeable future, is not computers taking
over the world. I’m more worried about misuse of AI”
Yoshua Bengio, in MIT Technology Review, January 29, 2016
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Features
Label
(what it is, semantics)
TrainingSupervised
learning
Unsupervised
learning
Features
Training
Clustering
(need a human to
add semantics)
apple /
pear /
banana
attributes (size, color, weight, …)
picture (raw pixels)
text description
Objects
Objects
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Using deep learning, computing semantic distances
Similar meanings
Transformation into vectors,
using a very big neural network
Pictures
Pictures
PicturesPicture
or Text
“low” dimension vectormillion dimensions vector
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1 + 1 = 2
Bits00000010
Computer Memory
(hardware)
Data2
This is “two”,
(useful to count things!)
This does not mean anything
for a computer
Human interpretation
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1. Deep Learning and Reinforcement Learning need to train on millions of examples
(see AlphaGoZero)
2. Computers don't know how the world works, have no “common sense”
3. No generalization capability: AI today is only narrow intelligence
4. Without human interpretation, there is no intelligence in Artificial Intelligence
“The definition of today’s AI is a machine that can make a perfect chess move while the room
is on fire.” - A sentence from the ’70s quoted by Fei-Fei Li.
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John Searle: “A program merely manipulates symbols, whereas a brain attaches
meaning to them” (1990)
David Chalmer, distinguishes
the easy problem and the hard
problem of consciousness (1994)
Reductive Materialism
(mind explained by brain events)
Eliminativism
(consciousness does not exist)
Panpsychism
(consciousness is everywhere)
Integrated Information Theory
(everything is information)
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Dualism
(mind + body)
centuries of fight
against dualism
subjective experience
remains a mystery for
objective sciences
