predictions and hard problems with ai

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