Overview to University of Texas at Austin on AI technologies and what Thomson Reuters Labs is about.

1. Presented by:
Tarek Hoteit, PhD, IT Director
Katherine Li – Data Scientist
Image courtesy of https://pixabay.com/en/caution-computer-desk-geek-humor-1295260/
Applied AI/ML in the Workplace
Geek Food for Thought
@
The University of Texas in Austin
Computer Science Department
Thomson Reuters Labs
http://labs.tr.com

2. Agenda
• About Thomson Reuters & Thomson Reuters Labs
• Key AI projects @ Thomson Reuters
• Geek talk on Applied AI for students
• Code Walkthroughs

3. 3
Thomson Reuters
• Leading source of news and information for the professional market
• Business operation in 100 countries for over 100 years
• Key businesses: legal, tax & accounting, financial & risk*, Reuter News
• ~$5.3B revenue, 80% of 2017 Revenue cover legal professionals, tax professionals, and
corporates. 20% includes Reuters News and global print, 4.4% growth annually (post sale
of finance and risk)
• Distinct customer group regions – 62% America, 27% EMEA, 11% Asia
• 93% of product & services are online based
• Ranked 66 Best Global Brand in 2017*
Based on Investor Relations Summer 2018 Booklet & 2017 Fact Book
*Global Brand 2017 link

4. 4
What makes Thomson Reuters, Thomson Reuters?
Jim Smith, president & CEO explains

5. 5
Founding fathers of Thomson Reuters
Paul Reuter (1821-1899)
innovator and entrepreneur at young age
• Started working as clerk at the age of 13 and accidently met Carl
Friedrich Gauss, one of history’s most influential mathematicians
• Passionate for speedy transmission of information since childhood
• Age of 28 started a news-collecting agency in two cities between
Germany and France and connected both through pigeon-posts
• Expanded sharing of intelligence knowledge between Britain and
rest of Europe at 30 and later with the rest of the world using
special underground cable
https://commons.wikimedia.org/wiki/File:PaulJuliusReuter-bust-v.jpg
https://en.wikisource.org/wiki/1911_Encyclop%C3%A6dia_Britannica/Reuter,_Paul_Julius,_Baron_de

6. 6
Founding fathers of Thomson Reuters
Paul Reuter (1821-1899)
innovator and entrepreneur at young age

7. 7
Founding fathers of Thomson Reuters
Roy Herbert Thomson (1894-1976), 1st Baron Thomson of Fleet, media
entrepreneur
• In his late twenties, started selling radios in
Toronto but found it restricting for his
audience so he founded a radio station with
$201 in his pocket
• Age of 40 acquired his first newspaper with
a $200 down payment
• Modest man who rode the London
Underground each day to work
https://commons.wikimedia.org/wiki/File:Roy_Thomson.jpg
https://en.wikipedia.org/wiki/Roy_Thomson,_1st_Baron_Thomson_of_Fleet

8. 8
“With employees in more 100 countries serving across industries, we offer opportunities
as boundless as the world.”
visit our careers website http://tr.com/careers

9. 9
Thomson Reuters Technology & Careers
• Diverse products and solutions in technology
• Very active development community across the world
• Research & development innovation center (labs) across the world -
https://innovation.thomsonreuters.com/en/labs.html
• Internship programs in the US include Ann Arbor, MI; Eagan, MN and Dallas,
TX; U.S. – Ranked Top 100 internship program in 2018
• Developer Community for API access on financials, risk, legal, tax & accounting
via
• Open Source Community over 127 repos on GitHub
https://github.com/thomsonreuters
• Incubator program in Zurich for RegTech, LegalTech, TaxTech and NewsTech
• Active career opportunities at http://tr.com/careers

10. 10
Thomson Reuters Labs – “Innovation is at the core of
everything we do”
Toronto: + Waterloo
• Partnerships with
CommuniTech &
University of Waterloo.
London:
• Partnerships with the
Open Data Institute and
Imperial College
Cape Town: Partnered
with the Cape Innovation
and Technology Initiative
(CiTi)
Singapore: Exploring
economic development
programs and university
partners. Feb 2017
Boston:
• Partnership with
MIT,
• FinTech Sandbox
Zurich:
• Expanding our footprint &
establishing new
partnerships. Blockchain
incubator. 2017
San Francisco:
• Starmine
Dallas:
• We are just getting
started
• Planned partnership
internal and external
(universities,
community)
labs.tr.com

11. 11
• Global team of data scientists, research scientists, full stack
developers, and designers; specializing in data science & analytics,
data visualization, artificial intelligence and blockchain.
• Major products recently rolled out
• West Law Edge – the most intelligence legal research platform ever
• World Check– risk intelligence for compliance and fight against crime
• Data Privacy Advisor – content intelligence with automated question and
answering capabilities
• TR Knowledge Graph Feed API & Thomson Reuters Intelligent Tagging –
entity relationship access to 2 finance billion records to incorporate in big
data solutions
• Reuters News Tracer - separate fact from rumor on Twitter in real-time
Thomson Reuters Labs – “Innovation is at the core of
everything we do”
labs.tr.com

12. 12
About WestLaw Edge
Team of 60+ AI research scientists, software engineers, and designers delivered the
product in partnership with other parts of the business.
Key AI Features:
• Identify overruling risk using machine learning and nlp
• Are cases that were decided on the same legal issue as red-flagged
cases still good law?
• NLP for issue identification and machine learning for risk classification
• Question Answering, using advanced NLP & machine learning
• Litigation Analytics
• Statistics by judge, court, attorney, law firm, or case type
• NLP for parsing dockets; machine learning for classifying outcomes
and chaining motions with outcomes

13. 13
About WestLaw Edge
http://www.westlawedge.com

14. 14
Mona Vernon with the Economist on the World in 2018
What’s driving the revolution of AI and machine learning?
“There is a combination of things that are coming together. A massive increase of
compute powers, algorithms are getting better, and, more importantly, there is this
rise of big data” – MonaVernon ,TR Labs CTO

15. 15
Industry AI innovation includes you! The University of
Texas at Austin is at the hub of AI research
• Great clubs in AI development : UTCS Artificial Intelligence
• More 100 projects and majority in neural networks (project list)
• Mostly PhD students and alumni (people-list)
• Numerous publications (list)
• Wide variation of labs such as automatic programming, computer
vision, deep learning, neural networks, and more (labs list)
• Also lots more clubs for computer science students, grads and under-
grads. (CS Students organizations)
Computer Science program ranked
6th in the world in 2014 (article)

16. 16
Don’t just stop there…
Consider applying AI now and all the time as a potential
startup, side projects, open source contributions, social
change, or even at home !

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Publishing is great but consider more applied AI, open source code
contribution, makers projects, and solutions that have a societal impact!
We have enough papers. Stop publishing, and start transforming people’s
lives with technology!” - Andrew Ng 2017
Andrew Karpathy (2017) “a peek at trends in machine learning”

18. 18
Consider automated machine learning services such as
AutoML for your next project
• Cloud-based services for ML/AI accessible for everyone
• Small-business like Sittercity automated baby-sitter review process with no ML
experience using Google Cloud AutoML (article)
• Feedzai Genome currently using AutoML for fraud dection (article)
•
Traditional ML vs. AutoML SOURCE: JANAKIRAM MSV

19. 19
Play around with gadgets and DIY tools
Raspberry PI Zero
Or Zero W $5-$10
Amazon DeepLens $249
Google AIY ~$50 for Voice, ~$90 for Vision
Pocket Chip $50 remaining stock
IBM TJBot -A Watson
Maker Kit

20. 20
Consider multilingual projects for your hometown
Field of
Study
Percent
Internation
al
Number of
Full-Time
Internation
al Graduate
Students in
2015
Number of
Full-Time
U.S.
Graduate
Students in
2015
Electrical
Engineering
81% 32,736 7,783
Petroleum
Engineering
81% 1,258 302
Computer
Science
79% 45,790 12,539
Industrial
Engineering
75% 7,676 2,539
Statistics 69% 4,321 1,966
Economics 63% 7,770 4,492
Mechanical
Engineering
62% 12,676 7,644
Civil
Engineering
59% 9,159 6,284
Chemical
Engineering
57% 5,001 3,834
Pharmaceuti
cal
Sciences
56% 1,931 1,502
Metallurgic
al/Material
s
Engineering
55% 3,723 3,103
Agricultura
l
Engineering
53% 726 654
Agricultura
53% 881 796
79% of computer science students in the USA
are international students but most benefit will
go to China and USA. Great but how about
other nations or in your own hometown?
https://www.insidehighered.com/quicktakes/2017/10/11/foreign-
students-and-graduate-stem-enrollment
PWC 2017

21. 21
Be practical in your solutions - think future generation (your generation)
“Gen Z Is Set to Outnumber
Millennials Within a Year”
“Gen Z will comprise 32 percent
of the global population of 7.7
billion in 2019, nudging ahead
of millennials, who will account
for a 31.5 percent share” - Bloomberg
https://www.fusionnetworks.co.nz/news/2018/09/generation-z
https://www.bloomberg.com/news/articles/2018-08-20/gen-z-to-outnumber-millennials-within-a-
year-demographic-trends
“Gen Z Is Coming to Your Office. Get
Ready to Adapt.”
“The generation now entering the
workforce is sober, industrious and driven
by money. They are also socially awkward
and timid about taking the reins” - WSJ

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Code walkthrough

23. 23
• We saw BeVote app launched by UT Austin and found it awesome!
• Brainstormed in few minutes how to use Applied AI for a chatbot version
• We then took some content examples from the website and
developed chatbot for Facebook Messenger
Took some text
And added to an AWS
Lambda function in
Python
Used NLP TFIDF
algorithm and
Facebook
Developer toolkit
Code Walkthrough 1 – BeVote app-inspired Chatbot – 2 hours to complete

24. 24
Code Walkthrough 2 – courses recommendation engine
• We built different types of recommendation engine for courses, similar to Netflix
or Amazon: 1) similar courses 2) people who took this also took that 3)
personalized recommendation

25. Built in few hours a Sentiment Analysis on Twitter using Django, Docker containers,
Python & Google NLP
Twitter API using Tweepy
Python Library & Twitter
Dev Account
Local Docker running
PostGresql databaseDjango & Python to run
and manage the code
and data
Google Cloud Natural
Language Processing
SDK to run sentiment
analysis
GITHUB Source Code:
https://github.com/hoteit/sentiment-
tweets
Code Walkthrough 3 –Sentiment Analysis using pretrained Google Cloud NLP

26. Training Google AutoML for 4 hours & $5 to categorize Coursera students reviews
Searched for a dataset on
https://toolbox.google.com/da
tasetsearch
Found “100K+ Scraped
Course Reviews from the
Coursera Website (As of
May 2017)
Analyzed the data,
cleaned when necessary
(pretraining step)
Created Google Cloud
AutoML project & activated
NLP APIs, uploaded data
No AI expertise needed!
Dataset import
Train/Evaluate/Predict model
GitHub Source Code https://github.com/hoteit/coursereviews-automl
Code Walkthrough 4 – Course Reviews using AutoML

27. 27
Contact us
Tarek Hoteit - @hoteit
LinkedIn https://www.linkedin.com/in/hoteit
Homepage http://tarek.computer
Tarek.Hoteit@tr.com
Katherine Li
LinkedIn https://www.linkedin.com/in/shiqi-dartmouth/
Homepage https://katherine-shiqi.github.io
katherine.li@tr.com