Deep neural networks, distributed intelligence, ubiquitous connectivity and infinite cloud computing will enable new intelligent experiences. Key trends include the growth of mobile devices, artificial intelligence, and internet connectivity. These technologies will be applied across smart phones, cars, IoT devices, and smart environments. Product engineers must consider how to integrate device, cloud, data sources and machine learning techniques to transform industries like transportation, cities, and enterprises.
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
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
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.
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
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
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
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