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Deep Neural Networks
Distributed Intelligence
Ubiquitous Connectivity
Infinite Cloud
Architecting
Artificial
Intelligence
Experiences
Iqbal Arshad
SVP Engineering, Global Product Development
Motorola Mobility
Key Computing Trends
Internet Mobile Ai: Starting Now
1994: Netscape Browser
1997: Google Search
2007: iPhone with Safari Browser
2008: Motorola Droid with Google Maps
+
+
Enabling New Experiences
Vision – A World of Holistic Ai Experiences
Network
Data + Machine Learning
Analytics + Apps
Smartphone
Smartwatch
Tablet
Smart IoT Devices
Experiences
Smart Environments
Knowledge Extraction
System Architecture
Prediction
+
Inference
Predictions,
Alert, Advice
Feature Extraction
Descriptors, Text, Metadata
Sensor + Observational Data
DNN
Key Technical Enablers
Cloud Computing Mobile Computing Wireless Connectivity
GPU no longer just for graphics
Explosion in Cloud Capacity
Ubiquitous 4G LTE
Faster & FasterCPU & GPU Ahead of Traditional Needs
Sensor Laden Devices
2015 Lenovo Confidential. All rights reserved.
Distributed Intelligence
General-Purpose GPUs (GPGPUs) are helping fulfill the law of accelerating returns
The path to growth no longer depends on packing more transistors onto a die,
but packing more GPU cores into warehouses.
Key Technical Enablers
Open Source Ai tools exist ... but data is key
CNTK GPU Developer Kit
Getting the Data: Smart Phones + IoT in 2020
World Population: 7.7 billion
Smart Phones: 6 billion
IOT Devices: 20+ billion
Smartphones
2 billion
9% CAGR
Computers
749 million
3% CAGR
Smart Watches
91 million
80% CAGR
IoT Devices
2 billion
21% CAGR
Market Disruption: World of DNN Products
Smart Car IoT DevicesSmart Phone
Market Disruption: World of DNN Products
Smart Car
Autonomous Cars: Disrupting Transportation
Cheaper Public Transport
55% of taxi revenue is paid to drivers
Relax and let the car do the
driving
Everybody Can Own a Car
Safer Driving
94% of accidents involve human error
Better Commute Productivity
US average daily commute is 90 min
Safer for Pedestrians
150,000 pedestrian accidents per year
More Efficient Parking
Self parking cars need 15% less space
Connected Autonomous Cars
Central Control Unit
(DNN Compute, Car Control)
Sensor System
(GPS, Radar, Lidar)
OEM Cloud
(training, external data management)
Onboard
DNN
360 Degree Vision System
Crowd Sourced DNN
(mapping, driver data)
Other Clouds
Weather
Police
City
Smart Car: Autonomous Systems
● Forward facing radar and camera
vision system
● Ultrasonic sensors for 360º object
detection
● Onboard vision computing
algorithms to measure distance, read
signs and detect pedestrians
● DNN system trained by millions of
miles of crowd sourced driving videos &
data
● High precision maps gathered and
enhanced by all drivers
● Designed for riding, not driving
● Rotating roof top camera with 64
laser beams to create 3D images of
surrounding objects
● Smart GPS sensory system calibrated
by sensor map data captured by cars
on previous journeys
● Onboard computer vision algorithms
use windshield camera to help car
make safe and intelligent decisions on
busy roads
● Ultrasonic sensors alert car to
obstacles in rear and enable backup
systems
Smart Car: Self Driving Car
Market Disruption: World of DNN Products
Smart Phone
Intelligent Smartphone Platform
● Contextual notifications delivered to your
phone based on your location, calendar, search
history, email and sensor information
● Personalized voice trigger technology that
enables you to wake-up and control your phone
even when it’s locked and turned off
● Smart gestures that enables you to control and
interact with your phone using sensor input
● Smart sensors that track your biometric,
physical activity and sleep
Beam Formed
Multi Mic
Noise Reduction
Intelligent Smart Phones: Natural Language
DSP
Wake-Up
Trigger
Neural
Net
Google
Now
App
Noise
Reduction
Speech
Detection
Semantic
Analysis
Intent
Classifier
Evidence
Ranker
Generate
Response
Neural
Net
Market Disruption: World of DNN Products
IoT Devices
Smart IoT Devices: Autonomous Drones
● Real-time object detection, tracking
and smart video-cast algorithms
● 3D reconstruction of scenes to create
a model of the environment
● Smart autopilot modes to enable safe
navigation of specified flight paths
● Airport avoidance, and other cloud
controlled safety measures to enable
new use-cases
● Indoor and outdoor flight control
Market Disruption: Not Just Devices…
Building Ecosystems is the key
A New World: Transformed by Ai
Smart Transport Smart City Smart Enterprise
Smart Transportation
● Shared Transportation via enhanced car
services
● New Business Models for OEM & Service
Provider
● Mobility Services in autonomous vehicles
● Dynamic Traffic Control Systems will monitor
queue depths at intersections and toll gates
adapting to demand to maximize flow
● Lower Cost per mile
Smart Cities
● Utilities, police, fire and city will share a
common data set that powers a city wide DNN
● Crowdsourced mobile phone data recruited to
report public safety / health information
● Drones gather thermal images to detect poorly
insulated and drafty homes / offices
● Real-time gas & chemical detection by mobiles
on the street, alerting authorities
● Smart autopilot modes enable safe navigation
of specified flight paths in crowded airspace
Smart Enterprises
● Nvidia, Google and IBM are building HPC
Hyperscale platforms to enable enterprises to
leverage DNNs
● To remain competitive, every enterprise need to
understand how they will use Ai to improve consumer
experience.
● Companies will adjust pricing based on supply
chain and wide range of market analytics
● Clinicians will gain new insights through
applications that scour vast amount of health data
Deep Neural Networks
Distributed Intelligence
Ubiquitous Connectivity
Infinite Cloud
To survive, every company must
understand how they will apply artificial
intelligence technology to their business.
Soon our home, car, smart devices and
city will work together as a single
intelligent unit, sharing data and enabling
new user experiences.
Product engineers of the future must
consider device, cloud, data sources and
the application of machine learning
techniques to every product that they
design.
Summary

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Northwestern Computational Research Day keynote april 19, 2016 (1)

  • 1. Deep Neural Networks Distributed Intelligence Ubiquitous Connectivity Infinite Cloud Architecting Artificial Intelligence Experiences Iqbal Arshad SVP Engineering, Global Product Development Motorola Mobility
  • 2. Key Computing Trends Internet Mobile Ai: Starting Now 1994: Netscape Browser 1997: Google Search 2007: iPhone with Safari Browser 2008: Motorola Droid with Google Maps + + Enabling New Experiences
  • 3. Vision – A World of Holistic Ai Experiences Network Data + Machine Learning Analytics + Apps Smartphone Smartwatch Tablet Smart IoT Devices Experiences Smart Environments
  • 4. Knowledge Extraction System Architecture Prediction + Inference Predictions, Alert, Advice Feature Extraction Descriptors, Text, Metadata Sensor + Observational Data DNN
  • 5. Key Technical Enablers Cloud Computing Mobile Computing Wireless Connectivity GPU no longer just for graphics Explosion in Cloud Capacity Ubiquitous 4G LTE Faster & FasterCPU & GPU Ahead of Traditional Needs Sensor Laden Devices
  • 6. 2015 Lenovo Confidential. All rights reserved. Distributed Intelligence General-Purpose GPUs (GPGPUs) are helping fulfill the law of accelerating returns The path to growth no longer depends on packing more transistors onto a die, but packing more GPU cores into warehouses.
  • 7. Key Technical Enablers Open Source Ai tools exist ... but data is key CNTK GPU Developer Kit
  • 8. Getting the Data: Smart Phones + IoT in 2020 World Population: 7.7 billion Smart Phones: 6 billion IOT Devices: 20+ billion Smartphones 2 billion 9% CAGR Computers 749 million 3% CAGR Smart Watches 91 million 80% CAGR IoT Devices 2 billion 21% CAGR
  • 9. Market Disruption: World of DNN Products Smart Car IoT DevicesSmart Phone
  • 10. Market Disruption: World of DNN Products Smart Car
  • 11. Autonomous Cars: Disrupting Transportation Cheaper Public Transport 55% of taxi revenue is paid to drivers Relax and let the car do the driving Everybody Can Own a Car Safer Driving 94% of accidents involve human error Better Commute Productivity US average daily commute is 90 min Safer for Pedestrians 150,000 pedestrian accidents per year More Efficient Parking Self parking cars need 15% less space
  • 12. Connected Autonomous Cars Central Control Unit (DNN Compute, Car Control) Sensor System (GPS, Radar, Lidar) OEM Cloud (training, external data management) Onboard DNN 360 Degree Vision System Crowd Sourced DNN (mapping, driver data) Other Clouds Weather Police City
  • 13. Smart Car: Autonomous Systems ● Forward facing radar and camera vision system ● Ultrasonic sensors for 360º object detection ● Onboard vision computing algorithms to measure distance, read signs and detect pedestrians ● DNN system trained by millions of miles of crowd sourced driving videos & data ● High precision maps gathered and enhanced by all drivers
  • 14. ● Designed for riding, not driving ● Rotating roof top camera with 64 laser beams to create 3D images of surrounding objects ● Smart GPS sensory system calibrated by sensor map data captured by cars on previous journeys ● Onboard computer vision algorithms use windshield camera to help car make safe and intelligent decisions on busy roads ● Ultrasonic sensors alert car to obstacles in rear and enable backup systems Smart Car: Self Driving Car
  • 15. Market Disruption: World of DNN Products Smart Phone
  • 16. Intelligent Smartphone Platform ● Contextual notifications delivered to your phone based on your location, calendar, search history, email and sensor information ● Personalized voice trigger technology that enables you to wake-up and control your phone even when it’s locked and turned off ● Smart gestures that enables you to control and interact with your phone using sensor input ● Smart sensors that track your biometric, physical activity and sleep
  • 17. Beam Formed Multi Mic Noise Reduction Intelligent Smart Phones: Natural Language DSP Wake-Up Trigger Neural Net Google Now App Noise Reduction Speech Detection Semantic Analysis Intent Classifier Evidence Ranker Generate Response Neural Net
  • 18. Market Disruption: World of DNN Products IoT Devices
  • 19. Smart IoT Devices: Autonomous Drones ● Real-time object detection, tracking and smart video-cast algorithms ● 3D reconstruction of scenes to create a model of the environment ● Smart autopilot modes to enable safe navigation of specified flight paths ● Airport avoidance, and other cloud controlled safety measures to enable new use-cases ● Indoor and outdoor flight control
  • 20. Market Disruption: Not Just Devices… Building Ecosystems is the key
  • 21. A New World: Transformed by Ai Smart Transport Smart City Smart Enterprise
  • 22. Smart Transportation ● Shared Transportation via enhanced car services ● New Business Models for OEM & Service Provider ● Mobility Services in autonomous vehicles ● Dynamic Traffic Control Systems will monitor queue depths at intersections and toll gates adapting to demand to maximize flow ● Lower Cost per mile
  • 23. Smart Cities ● Utilities, police, fire and city will share a common data set that powers a city wide DNN ● Crowdsourced mobile phone data recruited to report public safety / health information ● Drones gather thermal images to detect poorly insulated and drafty homes / offices ● Real-time gas & chemical detection by mobiles on the street, alerting authorities ● Smart autopilot modes enable safe navigation of specified flight paths in crowded airspace
  • 24. Smart Enterprises ● Nvidia, Google and IBM are building HPC Hyperscale platforms to enable enterprises to leverage DNNs ● To remain competitive, every enterprise need to understand how they will use Ai to improve consumer experience. ● Companies will adjust pricing based on supply chain and wide range of market analytics ● Clinicians will gain new insights through applications that scour vast amount of health data
  • 25. Deep Neural Networks Distributed Intelligence Ubiquitous Connectivity Infinite Cloud To survive, every company must understand how they will apply artificial intelligence technology to their business. Soon our home, car, smart devices and city will work together as a single intelligent unit, sharing data and enabling new user experiences. Product engineers of the future must consider device, cloud, data sources and the application of machine learning techniques to every product that they design. Summary