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1 of 38
About
1. CEO DevRain, devrain.com.
2. CTO ДонорUA, donor.ua.
3. PhD in Computer Science.
4. Microsoft Regional Director
5. Microsoft AI Most Valuable Professional
6. Open data, Smart City expert.
7. Ex-EGAP Challenge coordinator.
8. The Best Professional in Software Architecture
(Ukrainian IT Award).
Global issues
1. Employment and skills
2. Climate change
3. Food, Energy and Water
4. Health, Sleep, Nutrition
5. Media Biases and Access
6. Corruption
7. People with disabilities
8. Gender Equality
9. Ending Poverty
10. Ageing
11. AIDS
12. Human Rights
13. Saving animals
14. International Law and
Justice
15. Migration
16. Oceans and the Law of
the Sea
17. Peace and Security
18. Population
19. Refugees
20. Africa
21. Fakes
22. Privacy
23. Quality education
24. Democracy
25. Terrorism
26. Populism
Source: United Nations
How can AI and machine learning
be applied to solve some of
society's biggest challenges?
Process
1. Creating dataset (open data, manual, IoT)
2. Understanding data (feature engineering)
3. Model
1. Creation
2. Evaluation
3. Validation
4. Improvement
Types of problems
1. Clustering
1. Given news articles, cluster into different types of news.
2. Classification
1. Yes/No - binary classification
2. “Is this picture a cat or a dog or a tiger?” - multi-class
classification
3. Association analysis
1. If {A, B} then {C}
4. Regression
1. What is the price of house in a specific city?
CareerVillage.org
Nonprofit that crowdsources career advice for
underserved youth.
Your objective: develop a method to recommend
relevant questions to the professionals who are
most likely to answer them.
https://www.kaggle.com/c/data-science-for-good-careervillage
DonorUA: predicting if person
will donate a blood
Features:
1. Recency – months since last donation
2. Frequency – total number of donation
3. Monetary – total blood donated in c.c.
4. Time – months since first donation
Full article:
http://devrain.com/posts/solving-classification-
problems-with-azure-machine-learning-for-blood-
donations-prediction
Natural Language Processing
1. Sentiment analysis
2. Categorization
3. Named Entity Recognition
4. Summarization
5. Key phrases extracting
6. Part-of-Speech
7. Content Analysis
DonorUA
1. Social media monitoring
2. Donor – recipient match
3. Predicting supply/demand
4. Donor’s portrait
http://blog.1991.center/donorua
Join our Telegram channel:
https://t.me/donorua
Language Understanding (LUIS.ai)
A machine learning-based service to build natural language into apps, bots, and IoT devices.
Quickly create enterprise-ready, custom models that continuously improve.
Word embedding
Vector Representations of Words
Image recognition
Hot dog or not hot dog?
Fighting fire with machine learning:
using TensorFlow to predict wildfires
“We decided to develop a device that
could identify and predict areas in a
forest that are susceptible to wildfires,
providing an early warning to fire
departments.
Using TensorFlow, we can analyze images
of biomass and estimating their moisture
content and size to determine the
amount of dead fuel.”
https://www.blog.google/technology/ai/fighting-fire-machine-
learning-two-students-use-tensorflow-predict-wildfires/
AI helps farmers identify diseased plants
An example of a
diseased cassava leaf.
Cassava is a crop that
provides for over half
a billion people daily.
https://www.blog.google/technology/a
i/ai-takes-root-helping-farmers-
identity-diseased-plants/
Вирубка лісів
Згідно зі статистикою організації Глобального
моніторингу лісів, за останні 15 років Україна
втратила майже 500 тис. га лісу. З 2015 року,
коли у країні був введений мораторій на
експорт лісу-сировини, як не парадоксально
звучить, показники вирубки лісів масово
збільшилися. За оцінками деяки фахівців
протягом 2016 року в Україні було вирубано
16,4 млн кубометрів деревини, з них 8-9 млн
кубометрів легально.
http://texty.org.ua/d/deforestation-longread/
http://texty.org.ua/pg/blog/nartext/read/76201/J
ak_big_data_i_drony_mozhut_vratuvaty
Seeing AI
A free app that narrates
the world around you.
Designed for the low
vision community, this
research project
harnesses the power of
AI to describe people,
text and objects.
https://www.microsoft.com/en-
us/seeing-ai
Wild Me
Wild Me used computer vision and deep
learning algorithms to create a platform called
Wildbook, which scans millions of
crowdsourced wildlife images at scale.
Wildbook can identify the species as well as
the individual animal, and the public can follow
the movements of their favorite animals. The
aggregated data is used by scientists to help
inform conservation decisions. Microsoft is
supporting their efforts by hosting Wildbook
on Azure and making Wild Me’s open source
algorithms available as APIs.
https://www.microsoft.com/en-us/ai/ai-for-earth-
projects?activetab=pivot1:primaryr3
Object recognition
Analyze images to detect objects, tags, texts etc.
Emotion recognition
Analyze faces to detect a range of feelings.
Face verification
Check the
likelihood that
two faces
belong to the
same person.
https://www.projectmurphy.net/
What if...
Project Murphy
Video Indexer
Unlock video insights
Linked Data
Semantic Web
Office 365 Graph
Microsoft Academic
Uber Movement
Microsoft Research Open Data
https://msropendata.com/
Can AI become an issue?
Fakes
GPT-2
GPT-2 generates synthetic
text samples in response to
the model being primed with
an arbitrary input. The model
is chameleon-like — it adapts
to the style and content of the
conditioning text. This allows
the user to generate realistic
and coherent continuations
about a topic of their
choosing.
https://blog.openai.com/better-language-
models/#sample8
Ethics and Biases
Programs and Organizations
• AI for Sustainable Global Development
https://ai4good.org/
• Google AI for Social Good
https://ai.google/social-good
• AI for good with Microsoft Artificial Intelligence
https://www.microsoft.com/en-us/ai/ai-for-good
Join us!
• Telegram
https://t.me/devraincommunity
• Facebook Page
https://www.facebook.com/DevRainSolutions/
• Meetup
https://www.meetup.com/devrain/
Q&A
Oleksandr Krakovetskyi
CEO DevRain
alex.krakovetskiy@devrain.com
@sashaeve
fb.com/alex.krakovetskiy

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Artificial Intelligence for Goods: Cases and Tools

  • 1.
  • 2. About 1. CEO DevRain, devrain.com. 2. CTO ДонорUA, donor.ua. 3. PhD in Computer Science. 4. Microsoft Regional Director 5. Microsoft AI Most Valuable Professional 6. Open data, Smart City expert. 7. Ex-EGAP Challenge coordinator. 8. The Best Professional in Software Architecture (Ukrainian IT Award).
  • 3. Global issues 1. Employment and skills 2. Climate change 3. Food, Energy and Water 4. Health, Sleep, Nutrition 5. Media Biases and Access 6. Corruption 7. People with disabilities 8. Gender Equality 9. Ending Poverty 10. Ageing 11. AIDS 12. Human Rights 13. Saving animals 14. International Law and Justice 15. Migration 16. Oceans and the Law of the Sea 17. Peace and Security 18. Population 19. Refugees 20. Africa 21. Fakes 22. Privacy 23. Quality education 24. Democracy 25. Terrorism 26. Populism Source: United Nations
  • 4. How can AI and machine learning be applied to solve some of society's biggest challenges?
  • 5. Process 1. Creating dataset (open data, manual, IoT) 2. Understanding data (feature engineering) 3. Model 1. Creation 2. Evaluation 3. Validation 4. Improvement
  • 6. Types of problems 1. Clustering 1. Given news articles, cluster into different types of news. 2. Classification 1. Yes/No - binary classification 2. “Is this picture a cat or a dog or a tiger?” - multi-class classification 3. Association analysis 1. If {A, B} then {C} 4. Regression 1. What is the price of house in a specific city?
  • 7. CareerVillage.org Nonprofit that crowdsources career advice for underserved youth. Your objective: develop a method to recommend relevant questions to the professionals who are most likely to answer them. https://www.kaggle.com/c/data-science-for-good-careervillage
  • 8. DonorUA: predicting if person will donate a blood Features: 1. Recency – months since last donation 2. Frequency – total number of donation 3. Monetary – total blood donated in c.c. 4. Time – months since first donation Full article: http://devrain.com/posts/solving-classification- problems-with-azure-machine-learning-for-blood- donations-prediction
  • 9. Natural Language Processing 1. Sentiment analysis 2. Categorization 3. Named Entity Recognition 4. Summarization 5. Key phrases extracting 6. Part-of-Speech 7. Content Analysis
  • 10. DonorUA 1. Social media monitoring 2. Donor – recipient match 3. Predicting supply/demand 4. Donor’s portrait http://blog.1991.center/donorua Join our Telegram channel: https://t.me/donorua
  • 11. Language Understanding (LUIS.ai) A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve.
  • 12.
  • 15. Hot dog or not hot dog?
  • 16. Fighting fire with machine learning: using TensorFlow to predict wildfires “We decided to develop a device that could identify and predict areas in a forest that are susceptible to wildfires, providing an early warning to fire departments. Using TensorFlow, we can analyze images of biomass and estimating their moisture content and size to determine the amount of dead fuel.” https://www.blog.google/technology/ai/fighting-fire-machine- learning-two-students-use-tensorflow-predict-wildfires/
  • 17. AI helps farmers identify diseased plants An example of a diseased cassava leaf. Cassava is a crop that provides for over half a billion people daily. https://www.blog.google/technology/a i/ai-takes-root-helping-farmers- identity-diseased-plants/
  • 18. Вирубка лісів Згідно зі статистикою організації Глобального моніторингу лісів, за останні 15 років Україна втратила майже 500 тис. га лісу. З 2015 року, коли у країні був введений мораторій на експорт лісу-сировини, як не парадоксально звучить, показники вирубки лісів масово збільшилися. За оцінками деяки фахівців протягом 2016 року в Україні було вирубано 16,4 млн кубометрів деревини, з них 8-9 млн кубометрів легально. http://texty.org.ua/d/deforestation-longread/ http://texty.org.ua/pg/blog/nartext/read/76201/J ak_big_data_i_drony_mozhut_vratuvaty
  • 19. Seeing AI A free app that narrates the world around you. Designed for the low vision community, this research project harnesses the power of AI to describe people, text and objects. https://www.microsoft.com/en- us/seeing-ai
  • 20. Wild Me Wild Me used computer vision and deep learning algorithms to create a platform called Wildbook, which scans millions of crowdsourced wildlife images at scale. Wildbook can identify the species as well as the individual animal, and the public can follow the movements of their favorite animals. The aggregated data is used by scientists to help inform conservation decisions. Microsoft is supporting their efforts by hosting Wildbook on Azure and making Wild Me’s open source algorithms available as APIs. https://www.microsoft.com/en-us/ai/ai-for-earth- projects?activetab=pivot1:primaryr3
  • 21. Object recognition Analyze images to detect objects, tags, texts etc.
  • 22. Emotion recognition Analyze faces to detect a range of feelings.
  • 23. Face verification Check the likelihood that two faces belong to the same person.
  • 31. Microsoft Research Open Data https://msropendata.com/
  • 32. Can AI become an issue?
  • 33. Fakes
  • 34. GPT-2 GPT-2 generates synthetic text samples in response to the model being primed with an arbitrary input. The model is chameleon-like — it adapts to the style and content of the conditioning text. This allows the user to generate realistic and coherent continuations about a topic of their choosing. https://blog.openai.com/better-language- models/#sample8
  • 36. Programs and Organizations • AI for Sustainable Global Development https://ai4good.org/ • Google AI for Social Good https://ai.google/social-good • AI for good with Microsoft Artificial Intelligence https://www.microsoft.com/en-us/ai/ai-for-good
  • 37. Join us! • Telegram https://t.me/devraincommunity • Facebook Page https://www.facebook.com/DevRainSolutions/ • Meetup https://www.meetup.com/devrain/