Artificial intelligence is a global phenomenon, a technology that has arrived. No industry will be untouched by the changes and disruption these technologies bring. With the rapidly changing innovation landscape, patent offices are discussing the interplay between AI and patents. Corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policy makers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses. Patent analysts will have to respond to this changing environment by being more global in their perspective and will need analytic skills to deal with growing amount of data. The presentation will focus on these aspects and will highlight recent developments in AI methods and the breadth of AI applications that are of importance to patent searchers, analysts, and decision-makers. We will discuss some basics of AI and then zoom in on the neural networks based natural language processing methods and discuss their applications for patent corpus.

1. AI meets IP:
There is Nothing Artificial about it
Srinivasan Parthiban
VINGYANI IC-SDV 2019, Nice, France
08-09 April 2019

2. AI strategies
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3. What is AI?
• The term “artificial intelligence”
o Was coined in 1955
o Encompasses the broad concept of intelligent behaviour
by machines
o Has roots as far back as the 19th century, when futurists
and science fiction writers began raising the possibility of
“conscious machines”
• Can further be categorized as “strong AI” and
“narrow AI”
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4. Strong AI
• Refers to artificial general intelligence where machines have achieved
some level of consciousness
• As of yet, theoretical and not possible with today’s technology
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5. Narrow AI
• What is possible with today’s technology
• Refers to machine intelligence that is
focused on an individual task, such as a task
in computer vision or voice recognition
• While sophisticated with respect to the
task, it does not rely on general intelligence
like that of the human brain
• Examples include machine learning,
classification and regression trees, decision
trees, fuzzy logic, neural networks, etc.
• Is the subject matter of an ever growing
number of patents and applications
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6. Four waves of AI applications
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7. AI takes many forms …
Abilities, Tasks and Methods
Computer
Vision
Speech Natural Language
Processing
Planning/Decision
Making
Abilities
Tasks
Methods
AI encompasses
all of this!
Expert Systems Machine Learning RLDeep Learning
Today’ weather in
Alexandria is pleasant
Hello
ஹல ோ
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8. AI patent families and scientific publications
AI patents took off 10 years after scientific publicationsVINGYANI
Huge surge in AI patent applications in past 5 years
1997 - AI 2011 – ML 2016 - DL
1956

9. Why Now?
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Compute
Models
Data
Peta flops per sec

10. Google Patents
Google Patents includes
over 120 million patent
publications from 100+
patent offices around the
world, as well as many
more technical documents
and books indexed in
Google Scholar and Google
Books, and documents from
the Prior Art Archive.
Google Patents currently index full-text
documents from the following patent offices:
United States
Europe
Japan
China
South Korea
WIPO
Russia
Germany
The United Kingdom
Canada
France
Spain
Belgium
Denmark
Finland
Luxembourg
The Netherlands
Austria
Australia
Brazil
Switzerland
Taiwan VINGYANI

11. Patent applications per country
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12. Word Embeddings
Word embeddings are distributed
representations of text in an n-
dimensional space. These are essential
for solving most NLP problems.
Word2Vec 2013 Google
GloVe 2014 Stanford Univ
FastText 2016 Facebook
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Word embeddings are basically a form of word representation that bridges the
human understanding of language to that of a machine.

13. Deep Learning
Primitives
Fully
Connected Layer
CNN
RNN
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Deep Learning
Architectures

14. Transformer
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Scaled Dot-Product Attention
Multi-Head Attention
consists of several attention
layers running in parallel
The Transformer –model architecture

15. Differences in the Language Model Architecture
between major transfer learning methods
Embeddings from
Language Models
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LSTM
LSTM LSTM
LSTM LSTM
LSTM
LSTM
LSTM LSTM
LSTM LSTM
LSTM
ELMo
Bidirectional Encoder
Representations from Transformers
TRM TRM TRM
TRM TRM TRM
BERT
Generative
Pre-Training
TRM TRM TRM
TRM TRM TRM
OpenAI GPT

16. Uber: Improving Uber Customer Care with NLP &
Machine Learning
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Uber support
platform
What is the challenge?
And it is not easy to solve a ticket

17. The NLP pipeline for ticket
issue identification and
solution selection
is composed of three distinct
steps: preprocessing, feature
engineering, and
computation via pointwise
ranking algorithm.
UBER: Topic Modelling
a) Topic Modelling: TF-IDF
and LSA to extract topics
from rich text data in
customer support tickets
processed by customer
support platform.
b) b) Feature engineering: all
the solutions and tickets
are mapped to the topic
vector space, and cosine
similarity between
solution and ticket pairs
are computed. VINGYANI

18. The Vatican Secret Archive
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Mt. Everest
8.8 km

19. VINGYANI

20. NLP applications in Pharma
Electronic health records Drug discovery
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21. The real life Iron Man: Patent for the world's first 'jet suit'
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22. The Amazon Blimp Dropping Drones
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24. Facebook vs Google Data Center
Google Data Center Use Machine learning to save power consumption
Facebook Data Center went to Arctic circle to save power consumption

26. Patenting AI at USPTO and EPO
• The USPTO recently issued revised patent subject matter
eligibility guidance (“Revised Guidance”). See 84 Fed. Reg. 50
(January 7, 2019).
• The Revised Guidance did not change the law – it changed the
procedure by which the USPTO will conduct its patent subject
matter eligibility analysis
• The EPO Updated Guidelines for Examination
– New section on AI and machine learning (Chapter G-II, 3.3.1)
– Came into force on 1 November 2018
Those seeking and maintaining patent protection for AI will need
to stay abreast of the latest legal developments in this realm.

27. World’s 5 Largest IP Offices Name Artificial
Intelligence A Top Strategic Priority
• The heads of the patent offices of China,
Europe, Korea, Japan and the United States
met in mid 2018 and declared artificial
intelligence one of the top strategic priorities
for them as a group.

28. Unity:
A Look at the USPTO’s AI Development Efforts
The USPTO’s tool is called Unity and is planned for use in carrying out automated
prior art searches and presenting the results to examiners before beginning a traditional
manual
Pre-Classification/Automation

29. Areas where the Patent Offices are Planning to use AI
• Automatic pre-classification of incoming patent
applications to assign the file to the right unit.
• Automatic classification and re-classification of patent
documents according to the CPC scheme.
• Performing automatic searches on incoming patent
applications: selection and merging of documents sets
with machine learning methods.
• Machine Translation through Google’s Neural Network
based machine
• Developing more sophisticated and efficient business
operations for administrating IP
• Improvement of its services to users

30. Final Remarks
• Artificial intelligence (“AI”) has exploded in the last decade.
• AI technology has been adopted by many business sectors
and is rapidly becoming an integral part of society and our
everyday lives.
• AI may provide an economic boost within two decades.
• The number of published AI patent applications per year is
rising. Over half of all patent publications in the AI field
were published after 2013.
• AI technology has uses across many industries, and many AI
patent filings refer to multiple industries. The biggest
industries for AI patent filings are currently transportation,
telecommunications, and life and medical sciences.

31. Thank You
AI meets IP
VINGYANI
IC-SDV 2019, Nice, France
08-09 April 2019
Let us partner together!
www.vingyani.com
IC-SDV 2019, Nice, France
08-09 April 2019
AI meets IP