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8/12/2019 The Evolution of Personal Assistants: From Science Fiction to Reality to the Transparent Brain
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The Evolution ofPersonal Assistants
from Science Fictionto Realityto the Transparent rain
Mobile Voice ConferenceSan Francisco, March 3-5, 2014
Marsal [email protected]
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Summary
2
ThesisHuman behavior is getting easier to observe and predict.
First Corollary
Personal assistants will become uncannily good.
Second Corollary
Deviating from the recommended course of action
will need to be enshrined as an unalienable right.
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The evolution of taxi receipts
3
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Measuring productivity
4
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Tracking shoppers
5
Source: The New York Times
Sourc
e:
Berry
&Ree
d
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Magnifying motion
6
Source:Wu, Hao-Yu, et al. Eulerianvideo magnification for revealing subtle
changes in the world. ACM Transactions
on Graphics (TOG) 31.4 (2012): 65.\
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Predicting user location from historical cell tower data: 93% accuracy
7
Source:Science 327, 1018 (2010)
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8
Amazons Anticipatory shipping
Sour
ce:Amazon
Source:US PTO
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Mechanical chess-playing Turk (Wolfgang von Kempelen, 1770)
9
Source:Wikipedia
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Singing automaton Olimpia
10
E.T.A. Hoffmanns The Sandman(1816)
Jacques Offenbachs Tales of Hoffmann(1881)
Source:You
Tu
be
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ApplesKnowledge Navigator(1987)
11
Messages and calendar
Document search
Related articles
Video conferencing
Article sharing
Data mashup
Source:App
le
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8/12/2019 The Evolution of Personal Assistants: From Science Fiction to Reality to the Transparent Brain
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Spike JonzesHer(2013)
13
Source: herthemovie.com
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Artificial Intelligence slowly but inexorably improving
14
Source: NIST
Progress in
Automatic Speech Recognition
Dynamic speaker adaptation Deep/recurrent neural networks Ultra large language modelsNatural Language Understanding
Conversation and topic modeling Knowledge Graph
570 million entities 18 billion facts & relationships
Machine Learning
Latent factor models for recommendersystemsleads to improved understanding of natural,
human-to-human conversations.
Source: Google
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Deep learning applied to Automatic Speech Recognition
Microsoft
Context-dependent deep neural network, hidden
Markov model:-33% WER
Deep tensor neural networks:-8% WER
Source: Large vocabulary speech recognition usingdeep tensor neural networks, Yu et al. (2012)
IBM
Deep neural network with linear feature-space
maximum mutual information discriminative
objective function:-5% WER
Source: Discriminative feature-space transforms using deep neural networks, Saon et al. (2012)
GoogleContext-dependent ANN/HMM hybrid system
pretrained with deep belief networks:-5% WER
Source: Application of pretrained deep neural networks to large vocabulary
speech recognition, Navdeep Jaitly et al. (2012)
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Deep learning applied to Natural Language Understanding
Source: Recursive deep models for semantic compositionality over a sentiment treebank, Socher et al. (2013)
Stanford Sentiment TreebankFrom semantic vector spaces to
recursive neural tensor networks:-25% sentiment accuracy error
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Knowledge Graphs
From disembodied strings to grounded entities
Yahoo! 10 M entities, 30 M properties, 10 M connections Microsoft 300 M entities, 800 M connections Google 570 M entities, 18 B properties and connections Wikipedia 4 M entities Freebase 40 M topics, 2 B facts Factual 66 M local businesses and POIs in 50 countries LinkedIn 225 M people Facebook 1.15 B peopleCf.
Cyc239 K concepts,2 M facts
OpenCyc6 K concepts,60 K facts
Source:Yahoo!
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8/12/2019 The Evolution of Personal Assistants: From Science Fiction to Reality to the Transparent Brain
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Recommender systems
Amazon Netflix Pandora
Spotify FourSquare LinkedIn
Source: Tempo AI
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Mobile devices capture data via many sensors
20
Cameras,
microphones,
Wi-Fi, LTE, GPS,
and
Source:Samsung
S
ource:
fun
fopensens
ing
frame
work
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Context awareness helps modulate response
Youre on speakerphone and my wife is in the car
Source:
Ento
urage
by
HBO
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Even more sensors are coming
Coupling an electronic skin tattoo to
a mobile communication device
(U.S. Pat. Application 20130297301)
Speech recognition from facial
muscle activity captured by
electrodes (Schultz & Wand, 2010)
Emotiv EPOC
EEG headset
Google Glass
3 axis gyroscope
3 axis accelerometer
3 axis magnetometer ambient light and proximity sensors
bone conduction transducer
camera, Wi-Fi, Bluetooth
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Quantified Self
Source:Giga OM
Source:Rachelle DiGregorio
Source:Giga OM
Source:Facebook
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ALL THAT HAPPENS MUST BE KNOWN
SHARING IS CARING
SECRETS ARE LIES
PRIVACY IS THEFT
WAR IS PEACE
FREEDOM IS SLAVERY
IGNORANCE IS STRENGTH
1949 2013
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The possibility of
total digital surveillance
touches the essence of our life.
It is thus an ethical task
that goes far beyond the
politics of security [ to the]freedom and dignity
of the individual.
Angela MerkelOn Freedom and Security
January 29, 2014Source:The New York Review of Books(March 20, 2014)
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Literally Transparent Brain
26Source: National Geographic Magazine
Source:National Geographic Magazine
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Towards mind reading
27
Source:Science 320.5880 (2008)
Source:Carneg
ieMe
llon
Un
ivers
ity
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Literally Transparent Brain
28Source: National Geographic Magazine
Source:National Geographic Magazine
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Literally Transparent Brain
29Source: National Geographic Magazine
Source:National Geographic Magazine
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When one has weighed the sun
in the balance, and measured
the steps of the moon, and
mapped out the seven heavens
star by star, there still remainsoneself. Who can calculate the
orbit of his own soul?Oscar Wilde
De Profundis (1897)
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urce:
Risda
ll