This document discusses emerging technologies like artificial intelligence (AI), machine learning, and drones. It contains three main sections: 1) trends driving AI, machine learning, and drones, 2) examples of applying these technologies pragmatically, and 3) overcoming challenges to move forward. PwC examples show AI and drones used for construction site analysis, smart cooler insights, cancer research, mobility strategies, call center transcription, financial advice, and oil/gas contract extraction. The document emphasizes demonstrating value through pilots, addressing data challenges, and blending intuition with data insights.

1. Industry Disruptors: AI, Machine
Learning and Drones
Dr. Anand S. Rao – Innovation Lead, PwC Data& Analytics
Dr. Falko Kuester – Prof of Visualization & VR, UCSD
www.pwc.com/analytics
January, 2017

2. PwC CES-2017
Today’s discussion
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1. The Future is Now - Trends & Drivers for AI, Machine Learning and Drones
2. From the art of the possible to pragmatic possibilities
3. Overcoming challenges and moving forward

3. PwC CES-2017
1. Future is Now
33

4. PwC CES-2017 4

5. Community Database
Cyber Infrastructure
Rapid Response
Mainstream Media
ANALYSIS
• Modeling & Simulation
• Machine Learning
• Data Fusion
• Visual Analytics
• Virtual & Augmented Reality
DISSEMINATION
• Field Testing
• Training
• Publishing
• 3D Printing
• Citizen Science
CURATION
• Data Storage
• Data Bases
• Meta Data Augmentation
• Blockchain
ACQUISITION
• Diagnostic Imaging & Sensing
• Analytical Diagnostics
• Communications
• Robotics / Drones
Data

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Creating an Ecosystem for Disruptive Technologies

7. PwC
Artificial Intelligence is a branch of computer science dealing with the
simulation of intelligent behavior in computers
Machine
Learning
Deep
Learning
Natural
Language
Processing
Deep Q&A
systems (or
Cognitive
Computing)
Natural
Language
Generation
Social Network
Analysis
Graph
Analysis
Robotics &
Drones
Sensors /
Internet of
Things
Knowledge
Representation
Simulation
Modelling
Visualization
Image
Analytics
Audio/Speech
Analytics
Machine
Translation
Virtual
Personal
Assistants
Recommender
Systems
Deep Causal
Reasoning
Topic Areas within Artificial Intelligence (non-exhaustive)

8. PwC CES-2017
2. From the art of the possible to pragmatic
possibilities

9. PwC CES-2017
Rating product “style” with image and text analysis
Project: Deep learning to identify vehicle features The Path to Value...
Automobile Images Make & Model Prediction Start with general Image
recognition model and stock photos
Use “transformations” to train for
auto
Combine with style ratings
to assess new designs…
Refine design based on preferences
by customer segment
Create generative model to assist
designers
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10. PwC CES-2017
Simulating market adoption with virtual models and agents
Project: Simulate adoption of personal mobility solutions The Path to Value...
Simulate a million ‘consumer’
agents and their purchase choices
based on causal reasoning
Run over 200K go-to- market
scenarios to prescribe the right city,
pricing, and # of vehicles
Personal mobility as a service
disrupting the transportation
sector
Incorporate real-time sensor data
from city and vehicles
Vehicle Fleets
(Driverless, Electric,
Sharing)
Simulating demand, charging and utilization by
geography
Modeling demand for vehicle miles travelled
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11. PwC CES-2017
Identification of materials and boundaries with drones
Project: Capture and assess drone images from construction environment The Path to Value...
OriginalCroppedImageModelOutput
Extend image analysis to object
detection and semantic
segmentation
Increase number of drone runs to
collect image time-series
Track volume of high value
materials usage
Reduce risks and enhance return
on capital investment projects
Add additional data types (e.g.,
thermal, etc.)
Key:
Background Trees
Asphalt
ConcreteCars
Reinforcement
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12. PwC’s Data & Analytics
PwC has worked with a number of clients across all sectors to solve
challenging problems for them using AI
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Example Recent PwC AI Projects
1
Aerial Image Analytics
for Construction
Applies deep
learning to images
of property (e.g.
cars) to automate
the assessment
of the damage
to assets
2
Smart Coolers
Uses a connected
network of sensors
to derive valuable
insights about their
surroundings and
activities of those
within it
3
NLP for Cancer
Research
Uses natural
language
processing and
question-answering
systems to improve
quality of patient
care
4
Personal Mobility
Uses agent-based
modeling to run
over 200k
strategies to create
a business unit
focused on ride
share and
driverless cars
5
Speech Recognition
Deep Learning
Applies a suite of
deep learning
algorithms to convert
call center data into
text, which can then
be analyzed using
NLP techniques
6
Financial Advisor
Support
Uses agent-based
modeling to
simulate household
financial security
under a range of
scenarios to
provide advice
7
Predictive
Maintenance for Oil
Wells
Uses semi-
supervised natural
language processing
to automatically
extract information
from commercial
leasing contracts

13. PwC’s Data & Analytics
Drone Video
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https://pwc.mediaspace.kaltura.com/media/entryId/1_cra40b7z

14. PwC’s Data & Analytics Video: Parking Lot
Asset Tracking

15. PwC CES-2017
3. Overcoming Challenges & Moving Forward
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Five key success factors to derive maximum benefits
from AI, big data & analytics
Start from business
decisions
Demonstrate value through
pilots before scaling
Fail forward – test
and learn culture
Address ‘big data’ –
don’t forget ‘lean’ data
Blend intuition and data-
driven insights

17. PwC CES-2017
Machine Learning for Augmented Intelligence
https://pwc.mediaspace.kaltura.com/media/t/1_yee8khtl

18. For more information:
Anand S. Rao
(anand.s.rao@pwc.com)
Twitter: @AnandSRao
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entity. Please see www.pwc.com/structure for further details..
Images from Google Deep Dream
For more information:
Falko Kuester
(fkuester@ucsd.edu)
chei.ucsd.edu