1.
The truth about
Artificial Intelligence
@Jon_Whittle@
MONASH
INFORMATION
TECHNOLOGY
PROFESSOR JON WHITTLE | Dean

2.
From January 2015 to January 2018, active AI startups increased 113%, while all
active startups increased 28%. VC funding for U.S. AI startups increased
350% from 2013 to 2017
Meanwhile, VC funding for all active startups increased 100%.
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

3.
South Korea and Taiwan have
experienced the most growth, 5x
growth since 2004
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

4.
From 2015 to 2017 the number of
job openings requiring Deep
Learning increased 34x
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

5.
UC Berkeley's 2017 introductory
ML course has 6.8x as many
students as it had in 2012
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

6.
Combined AI + ML 2017 course
enrollment at Tsinghua University
was 16x that of 2010
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

7.
“We found widespread adoption of different AI
technologies across sectors, functions, and
geographies around the world; about half of all
companies had embedded AI into a corporate
business process.
However, most had not yet adopted the
complementary practices necessary to capture
value from AI at scale.”
Michael Chui, McKinsey & Company and the McKinsey Global Institute
Taken from: AI Index Annual Report 2018

8.
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

9.
MONASH
INFORMATION
TECHNOLOGY
Taken from: AI Index Annual Report 2018

10.
“Organizations tend to incorporate AI capabilities in
functions that provide the most value within their
industry. For example, Financial services has
heavily incorporated AI in Risk, while Automotive
has done so in Manufacturing, and Retail has done
so in Marketing / sales.”
AI Index Annual Report 2018

11.
0
1
2
3
4
5
6
Australia Canada Germany France Singapore South Korea UK
$Bn (AUD) AI Investment over next 5 years
Alibaba: $15Bn
Softbank: up to $100Bn
Amazon: $16Bn
Alphabet: $13Bn The Chinese government is creating a $22Bn AI market in China
to ensure that China leads the world in AI by 2030.
US DARPA announces $3Bn+ investment plan to overcome
limitations on AI technology.
Source: various

12.
A brief history of AI’s ups and downs
Source: https://towardsdatascience.com/history-of-the-first-ai-
winter-6f8c2186f80b

13.
Deep learning
Big data
Computing power
“We really need to temper our expectations and stop hyping deep learning
capabilities. If we don’t, we may find ourselves in another AI Winter.”
Thomas Nield, https://hackernoon.com/is-another-ai-winter-coming-ac552669e58c

14.
“The best thing you can do is be specific about the
problem you are trying to solve and understand its
nature.
If you want to categorize text messages, you
probably want to use Naive Bayes.
If you are trying to optimize your transportation
network, you likely should use Discrete
Optimization.”
Thomas Nield, https://hackernoon.com/is-another-ai-winter-coming-
ac552669e58

15.
What is AI anyway?

16.
planning
knowledge
language
modelling
visionlearning
search
decision-making
reasoning
https://live.staticflickr.com/4584/26958833209_c27a912bbf_b.jpg

17.
Examples vs
rule-based
approach
See Cassie Kokyrnov’s blog https://hackernoon.com/why-ai-is-here-to-stay-
9c75b1868b9b?utm_source=The+Crunch&utm_campaign=2db03e5079-
THE_CRUNCH_55_COPY_01&utm_medium=email&utm_term=0_aa18ea5b4e-2db03e5079-
233747585

18.
Source: Joelle Pineau ICSE 2019 keynote,
https://2019.icse-conferences.org/details/icse-2019-Plenary-Sessions/20/Building-Reproducible-Reusable-and-Robust-Machine-Learning-Software

19.
Facebook AI Research
https://newsroom.fb.com/news/2019/05/f8-2019-day-2/

20.
AI in Law
Enforcement
Smart farming
https://static.independent.co.uk/s3fs-
public/thumbnails/image/2017/06/25/18/minority-report.jpg?w968https://tr4.cbsistatic.com/hub/i/r/2018/02/12/e0a1a532-03d1-4932-aebb-
ead6d88caae5/resize/1200x/b88a9dad26a46f674125d8d8816d0e8d/istock-913641932.jpg

21.
AI in Healthcare
Smart farming
https://media.apnarm.net.au/media/images/2019/02/24/b881821867z1_20190224085842_000g5i1earro2-0-
cfa3lk6nbues9touur2_ct1880x930.jpg

22.
AI in sustainable
development
Smart farming
https://cdn.vox-cdn.com/thumbor/Twe13cA0ZjVEJHTC-
RwU2vSnfcA=/0x243:2500x2118/1220x813/filters:focal(0x243:2500x2118):format(webp)/cdn.vox-
cdn.com/uploads/chorus_image/image/46679984/shutterstock_150559442.0.0.jpg

23.
AI in transport
Smart farming
emotiv.com

24.
Caveats

25.
Smart farming
https://automatedsmarthome.files.wordpress.com/2015/11/image.jpg?w=1024
Bias and Ethics

26.
Smart farming
https://automatedsmarthome.files.wordpress.com/2015/11/image.jpg?w=1024
Diversity
AI Index Annual Report 2018
80% of AI professors are male
On average, 80% of professors from UC Berkeley,
Stanford, UIUC, CMU, UC London, Oxford, and ETH
Zurich are male

27.
Smart farming
https://automatedsmarthome.files.wordpress.com/2015/11/image.jpg?w=1024https://miro.medium.com/max/1838/1*goFgCUHprcr
oxSLZvROjpg.jpeg
Explainable AI

28.
Smart farming
Responsible AI
functionality, cost, safety,
security, privacy
Inclusion, diversity,
responsibility, transparency,
well-being
IT now
Responsible
IT

29.
“We have data”
https://upload.wikimedia.org/wikipedia/commons/5/54/Data.jpg

30.
“AI promises to be the most disruptive class of
technologies during the next 10 years
One of the biggest aggregate sources for AI-
enhanced products and services acquired by
enterprises between 2017 and 2022 will be niche
solutions that address one need very well.
Business executives will drive investment in these
products, sourced from thousands of narrowly
focused, specialist suppliers with specific AI-
enhanced applications.”
John-David Lovelock, Gartner research vice president

31.
Top tips
• AI is good at specific tasks not general ones
• AI is good when 100% accuracy isn’t necessary
• Know what problem you are trying to solve
• Do you have the right data?
• Do you know which AI technique to apply?
• Be responsible in your application of AI
• Automation vs AI
• Applying AI requires expertise

32.
https://www.monash.edu/ai-data-science
Jon.whittle@monash.edu
@Jon_Whittle_
LinkedIn