This presentation was given by Monojit Choudhury (Microsoft) as opening keynote in AI Dev Days 2018 on 9th March 2018 in Bangalore. www.aidevdays.com ---- Artificial Intelligence is changing the way we live, think and feel. It has instilled hope for a better world, as well as fear of being taken over by robots (even if not literally). How much of this is hype, and how much reality? In this talk, we will present my personal perspective on AI, based on our two decades of research experience in Natural Language Processing (NLP), AI and cognition, primarily as a scientist, but also from what Iwehave seen happening at Microsoft’s development centres and many start-ups with whom we have closely interacted with. Taking the case of Natural language understanding and dialogue systems as a running example, on one hand we will try to explain why Artificial General Intelligence is still a dream quite far away; on the other hand, we will try to argue that the most crucial aspect of building practical and useful AI systems is deep understanding of the domain, the user and the problem that one is trying to solve. Techniques like deep learning and platforms like Tensorflow, AzureML or MS Cognitive Services have improved the accuracy of AI systems and drastically reduced the time to production and scale; nevertheless, there are problems, seemingly very simple ones, that are much harder to solve not because of technology, but for a variety of other circumstantial reasons. In particular, we will highlight some unique and interesting challenges for the Indian market and user.

1. ARTIFICIAL INTELLIGENCE
FEATS,
LIMITS, &
CAVEATS
Monojit Choudhury
Microsoft Research Lab India
monojitc@microsoft.com @AIDevDays, 9th Mar 2018

2. The third wave of AI
Deep Learning
HumanParityin
Speech
Human Parity in
Vision Games
Speech-2-Speech
Translation

3. AI: Hype or Reality?
Subbarao
Kambhampati:
Challenges of
Human-Aware
AI Systems
AAAI 2018
Presidential Address

4. How long
will it take
for AI to
surpass
humans?
McKinsey Global institute analysis

5. • What makes Natural Language, Social,
and Emotional Understanding hard
problems?
• Can Deep Learning (or any futuristic
technology) magically solve these
problems?
• Is it necessary to solve these problems
to make practically useful AI systems?
Three Pressing Questions
LIMITS
FEATS
CAVEATS

6. Unlike chess or black
gammon, the rules of
the LANGUAGE GAME
are defined and redefined by
the language users every time
a game is played.
LudwigWittgenstein
(1889-1951)

7. It is not difficult to devise a paper machine which will play a
not very bad game of chess… Are there imaginable digital
computers which would do well in the imitation game?
AlanTuring, 1950
The biggest breakthrough in AI will be when computers
can read and understand information like humans do.
Bill Gates, 2017

8. Language
Understanding
Artificial
General
Intelligence
AI-completeºº

9. Language
Understanding
requires
Common Sense
• Linguistic Knowledge
– Words, idioms, proverbs, metaphors
• World Knowledge
• Contextual Knowledge
• Socio-cultural Norms

10. Two scientists walk into a bar.
"I'll have H2O," says the 1st.
"I'll have H2O, too," says the 2nd.
Bartender gives them water
because he is able to distinguish
the boundary tones that dictate
the grammatical function of
homonyms in coda position, as well as
pragmatic context.

11. Why is Pragmatics Important?
• Communicative intent
• Request, order, negotiation, persuasion,
threatening, inspiring, demotivating, …
• Social Functions
• Politeness, formality, socio-cultural conventions
• Non-literal Meanings
• Jokes, sarcasm, irony,
figurative language
• Resolving references
• Deixis, topic-focus

12. Language
usage
strongly
depends
on the
social
context

14. Has/Will
Deep Learning
revolutionize
Language
Understanding?
• Neural MachineTranslation Systems
are better than the Phrase-Based MT
Systems for some language pairs
– No gain for German-English
– Substantial gain for Japanese-English

15. Has/Will
Deep Learning
revolutionize
Language
Understanding?
• Neural Networks are universal
approximators, however, language is
NOT a continuous function, it is a
Discrete Combinatorial System
• Two fundamental benefits of deep
learning to NLP:
– Modeling Infinite context à Long distance
dependencies
– Discrete to continuous mapping à
word2vec

16. Word
Embeddings
“You shall know a word
by the company it
keeps.”
- Firth, 1957
Continuous Bag-of-Word
Skip grams

17. However,
Deep learning
cannot do
Common
Sense
Reasoning
Hard but tractable problems
• How to integrate external knowledge
sources?
• How to store learnt information
explicitly?
• How to reason over knowledge base
explicitly?
• How to acquire DATA for all these?

18. 1950s – 1980s: Rule based systems
Linguists ruled the world
1990s – 2000s: Basic statistical learning
Linguistic insights with some data
2000s – 2010s: Large scale supervised
and semi-supervised learning
Big data with some linguistic insight
2010s - : Deep learning
ONLY DATA
A brief
history of
NLP
Linguistic
insight
Data

19. How much
DATA?
POSTagging
(#annotated
words)
Machine
Translation
(#parallel
sentences)
Speech
Recognition
(hours of
speech)
1950s-1980s
Rule-based
As much as needed for linguistic analysis
1990s-2000s
Linguistic
insights +
Statistical
10k – 100k 10k-100k 10-100
2000s – 2010s
Big data
100k – 100M 100k – 1M 1o-1000
2010s –
Deep
Learning
1M – 1B 1M – 1B 1000 – 10k
Natural languages are fascinating.
Adj Noun Verb Adj
Natural languages are fascinating.
自然语言是迷人的。
Na-tu-ral lan-gua-ges are fa-sci-na-ting

20. All
languages
are equal,
but
some are
more equal
than others.
Breaking the Zipfian Barrier of NLP.
Invited talk at IJCNLP 2008Workshop
Rank of Language
#Words(million)inLDC
Amount of resources present for
various languages on LDC (2008)
English
Chinese
Spanish Arabic

21. Even if we solve the problem
of language understanding
for a few languages by next 3
or 4 decades, it will take at
least a century for building
such technology for most of
the major languages of the
world, unless brain-reading
becomes a reality.
Or maybe most of the
minority languages will die
by then!

22. • What makes Natural Language, Social,
and Emotional Understanding hard
problems?
• Can Deep Learning (or any futuristic
technology) magically solve these
problems?
• Is it necessary to solve these problems
to make practically useful AI systems?
Three Pressing Questions
CAVEATS

23. Challenges of Human-Aware AI Systems
Our Systems seem
happiest
• Either far away from
humans
• Or in an adversarial
stance with humans
Subbarao
Kambhampati:
AAAI 2018
Presidential Address

24. AI is a tool.
Not the problem
&
Almost never
the complete
solution
• Human-aware AI
– AI should collaborate, not
compete with humans
– The strengths of the two are
complementary
– Users are usually cooperative –
leverage!

25. AI is a tool.
Not the problem
&
Almost never
the complete
solution
• Data is the new electricity
– Invest and innovate in
collecting data
– Beware of privacy issues and
biases in data
– Contribute back
– Invest in low-resource
technology

26. AI is a tool.
Not the problem
&
Almost never
the complete
solution
• Understand the problem, the
users and the context
– Human-Computer Interaction
– Ethnography and Sociology
– Market Research

27. Code-mixing
• ni som har möjlighet att delta i missing people's sökande efter
snälla snälla gör det!!!!
• Adik… sem brape boleh bwak kenderaan? normal parent
question – UiTMLendufornia
• jit fi la fin du mois de decembre kan ljaw bared ktir wttalj
Code-Mixing or Code-Switching is mixing of more than one language
in a single conversation or utterance.

28. MULTILINGUAL
SOCIETIES
provide unique and
interesting challenges
• Code-switching
• Language preference
• Linguistic
Accommodation of
Language choice
50% of the world’s
population is multilingual

29. The Mélange Team: Kalika Bali, Monojit Choudhury, Sunayana Sitaram, Indrani Medhi Thies,
Anshul Bawa, Adithya Pratapa, Brij Srivastava
Past members: Ashutosh Baheti, Shruti Rijhwani, Royal Sequeira, Chandra Maddila and a
bunch of interns
Project Mélange
https://www.microsoft.com/en-us/research/project/melange/

30. Thank you!
monojitc@microsoft.com