how changing mobile and media technologies is changing the way we create innovations r1 2for public
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How Changing Mobile and Media Technologies is Changing The Way We Create Innovations
Mick Etoh
@mickbean
NTT DOCOMO
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Outline
Big-Data, Big-Server, and Fat-Pipe Solutions
Large-scale Signals from Wireless Infrastructure
APIs for Federated Systems
Definition of Innovation
Progress of Cellphone and Network Technologies
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Who am I?Digital VCR Development (1985)
Artificial Intellligence (1988)
Computer Vision and PR (1991)
Image Coding (1994)
Mobile Multimedia (2000)
Data Mining and NLP (2007-)Speech Recognition(2006) Machine Translation(2014-)
Mobile Network (2002-)
Investment(2012-)
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Connecting the dots….
4
Those experiences gave me the ability of
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Those experiences gave me the ability of
Connecting the technologies….
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What is Innovation?
Joseph Schumpeter‘s “neuer Kombinationen” (Theorie der wirtschaftlichen Entwicklung)
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“All technologies are combinations of technologies that already exist.” —
• Combinatorial Explosion • Creates Economy
W. Brian Arthur
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Innovation Example
2.5G Internet connectivity, DOCOMO
1998
Micro Browser, Access Co.
1995
i-mode, DOCOMO
1999New Biz. Concept:
Content Provider Bazar
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Wireless Technologies, the EnablersPersonal Storage SNS/Comm. Tools
LTE:~75Mbps2010
+Big data synchronization
Application Market (games, net contents, etc.)
3.5G: ~14Mbps 2006
+Smart Phone + Cloud
Mobile Multimedia
3G: 64-384Kbps 2001+CODEC
i-mode
2G:9.6KbpsX3 1998 +micro browser
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Very Simplified Formula
Wireless Broadband
Innovation X?
10
❌
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Distributed Speech Recognition(DSR) in 2006
First Implementation of ETSI AURORA Project (2000-2003)16 Khz Sampling MFCC feature vectors --> 5.6 Kbps
Mobile Terminal
Feature Extraction
Result
Encode
Server
Decode Rec. Engine
Dictionary
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Lessons Learned From the DSR(2006)
12
Pros• 16Khz sampling outperforms 8Khz Sampling.• Dedicated Feature Extraction Front End outperforms
the legacy IVR (Interactive Voice Response) methods.
Cons• Channel assumption was too narrow (i.e., Kbps-order).• No background noise model (left intact)
Bandwidth is not crucial.
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Mobile Issue: Battery
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3X energy density evolution
40MHz ARM(2001) Mbps
Broadband
Quad-Core 1GHz+
ARM(2014)
250X Improved
+
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Thin Client Architecture with Fat Pipe and Big Server since 2007
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LTE-Advanced Network (2016-)Macro Cell Base Station
Small Cell Base Station
Centeraized Radio Access Network
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Evolution of Wireless Technologies
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10 kbps
100 kbps
1 Mbps
10 Mbps
100 Mbps
1 Gbps
10 Gbps
2020
5G
2015201020052000
LTE
LTE-‐A
HSDPA, HDRWCDMA,
CDMA2000
MIMO
Carrier
Aggreg
ation/
MU-‐MI
MO
3D/Ma
ssive
MIMO
~3.5GHz
~60GHz
CDMA
OFDM/
OFDMA
Small C
ell
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Smart Phones as Information Hubs
WiFi
NFC
Bluetooth
Gyro
Microphone
CCD/CMOS Camera
GPS
Accelerometer
Cloud
Wireless Broadband
Smart Phone
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Camera+Snapdragon+Vuforia(FastCV)+Unity
18
Ball-in-a-maze puzzle
See youtube video.
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https://play.google.com/store/apps/
details?id=jp.co.sompo_japan.safetysight
iOnRoad
Safety Sight(2014)
http://www.ionroad.com/
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History of Cellphone Sensors
20
Barometric
Magnetometer
AccelerometerFingerprint
Co-Processors
GPS
2005 2010 2015
Navigation
Power reduction
biometrics
Navigation Compass
altimeter, weather forecast
pedometer, game controler
Mar/03
July/03
April/04
July/06
June/12
May/13
Gyroscope Image StabilizationNov./09
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Coprocessor solution (iphone 5s)
21
A6 Magnetometer
Accelerometer
Gyroscope
A7 M7 Magnetometer
Accelerometer
Gyroscope
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Sensor Fusion
22
3 axis gyroscope 2000°/second precision
3 axis accelerometer +-50mg precision
3 axis magnetometer 6° precision
Pressure sensor +/- 10 Pa precision
Ultrasound sensors for ground altitude measurement
60 fps vertical QVGA camera for ground speed measurement
http://ardrone2.parrot.com/ardrone-2/specifications/
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Flying Cell Phone: Androcopter
23http://diydrones.com/profiles/blogs/androcopter-use-you-smartphone-as-an-autopilot
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Siri24
Big-Data, Big-Server, and Fat-Pipe Solution
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“Shabette-Concier” Voice agent
• Launched Mar. 1, 2012
• Over 40 services in it
• Including chatting
• 10 million users
ShabetteVoice
= ConcierConcierge
=How may I help you?
25
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© 2014 NTT DOCOMO, INC. All rights reserved.Touch the Concier.Q: “What is the height of Mt. Fuji?”A: “3,766m!”Q: “When is holding schedule of the Tokyo Olympic Games?”A: “It will hold in 2020.” 26
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Basic Architecture 2010
Logging
VoiceRecognition
TaskRecognition
Logging
Voicetext text contents
Service Providers’ DB
contents
text
Text to speech
27
Fat-Pipe
Big-Servers
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BELIEF: More data usually beats better algorithms.
Speech
Speech Data
Language Data
Machine Learning Machine Learning
Acoustic Model Lexicon Language
Model
Speech Recognition I want...
Text
Voice Recognition
28
Big-Data
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Performance Improvement by Data
Prec
isio
n (%
)
40
50
60
70
80
90
Text Data Amount in Million Lines1 10 100 1000
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Virtuous Circle Enabled by Machine Learning
Improved Performance
Better User Experience More Data
Machine Learning
30
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Signal Processing in Mobile Comm.Signals From Each Mobile Device about
audio, image, video, and extra sensors for Applications: Information Retrieval, Navigation, etc.
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Signals From Gigantic Social Infrastructure about crowds, traffic, earthquake, and weather for
Applications: Large-scale Infrastructure Optimization and Human Security
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Earthquake Early Warning System(2007)
32
Mobile Telecommunication System
TV Broadcasting
System
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Earthquake Early Warning System
33
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PM 14:46, March 11th, 2011
34http://pics.livejournal.com/druzifer/pic/004q2qar
Great Eastern Japan Earthquake
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Connecting the technologies
through APIs…
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+ Character Recognition,Environment Sensor,Data Storage BOX,Location Information, Mobile Payment, and more.
API as Catalysts
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Yet another Google Goggle/Amazon Flow
37https://twitter.com/ksasao
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API AggregatorMashape is the largest API marketplace, powering thousands of APIs and Applications.
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Rank.25
Rank.34
Rank.39
Rank.43
Rank.16 ICCV2013
Rank.6 Googleglass
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Rank.51
Rank.57
Rank.62
Rank.77
Rank.85
Rank.87
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Take aways for “connecting the dots.”
41
Wireless Broadband
Innovation X?❌
Big-Server, Big-Data, and Fat-Pipe for Smart Thin clients
Virtuous Circle by Machine Learning
Large-scale Signals from Wireless Infrastructure
APIs as Connecters and Indicators of your inventions.
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Design of combination
from existing and
foreseeable
technologies
Research for Impact factor
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Signals from GPS around Tokyo in a normal and non-eventful day. 43
My dream is …to connect the systems.
Innovation X
Speech Dialogue System
Computer Vision System
unknown?