Deep Neural NetworksDistributed IntelligenceUbiquitous Connectivity

Infinite Cloud

Architecting Artificial Intelligence Experiences

Iqbal ArshadSVP Engineering, Global Product DevelopmentMotorola 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+

InferencePredictions,Alert, Advice

Feature ExtractionDescriptors, 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 IntelligenceGeneral-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

Smartphones2 billion9% CAGR

Computers749 million 3% CAGR

Smart Watches91 million 80% CAGR

IoT Devices2 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 Transport55% of taxi revenue is paid to drivers

Relax and let the car do the driving

Everybody Can Own a Car

Safer Driving94% of accidents involve human error

Better Commute ProductivityUS average daily commute is 90 min

Safer for Pedestrians150,000 pedestrian accidents per

year

More Efficient ParkingSelf 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)

OnboardDNN

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 FormedMulti Mic

Noise Reduction

Intelligent Smart Phones: Natural Language

DSPWake-UpTrigger

NeuralNet

GoogleNowApp

Noise Reduction

SpeechDetection

SemanticAnalysis

IntentClassifier

EvidenceRanker

GenerateResponse

NeuralNet

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 NetworksDistributed IntelligenceUbiquitous 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