What is machine learning? Is IA relevant in the age of AI? How can I take advantage of cognitive computing? Learn the basics of these concepts and the implications for your work in this presentation. Carol Smith provides examples of machine learning use and will discuss the challenges inherent in in AI.
2. AI is when Machines
– Exhibit intelligence
– Perceive their environment
– Take actions to maximize
chance of success at a goal
https://developer.softbankrobotics.com/us-en/showcase/nao-ibm-create-new-hilton-concierge
3. IBM Watson / AI for IA's: Machine Learning Demystified
@carologic / #ias17 IA Summit 2017
Algorithm: Process or set of rules to be followed
https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-
algorithms/
4. IBM Watson / AI for IA's: Machine Learning Demystified
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Primer on Terms
• AI
– Artificial intelligence, Augmented Intelligence, Cognitive Computing
• Machine Learning (ML)
• Natural Language Processing (NLP)
• API’s - Application program interface
5. IBM Watson / AI for IA's: Machine Learning Demystified
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In the extreme…
Google Search for “movies with AI”
Copyrights as labeled.
6. IBM Watson / AI for IA's: Machine Learning Demystified
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How do machines learn?
https://commons.wikimedia.org/wiki/File:Baby_Boy_Oliver.jpg
7. IBM Watson / AI for IA's: Machine Learning Demystified
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Transfer human concepts and relationships
Photo by sunlightfoundation
https://www.flickr.com/photos/sunlightfoundation/2385174105
8. IBM Watson / AI for IA's: Machine Learning Demystified
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Number Five “Needs Input”
Short Circuit (1986 film)
Ally Sheedy and Number Five (Tim Blaney)
https://en.wikipedia.org/wiki/Short_Circuit_(1986_film)
9. IBM Watson / AI for IA's: Machine Learning Demystified
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Annotating Content
Image created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
10. IBM Watson / AI for IA's: Machine Learning Demystified
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Entity Type
• High level concepts applied to a mention
PERSON
Amanda Amanda Tomlin She
Model created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
11. IBM Watson / AI for IA's: Machine Learning Demystified
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Define Entity Types
PERSON ORGANIZATION TIME
Amanda works at IBM.
She has worked for the company for 15 years.
Model created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
12. IBM Watson / AI for IA's: Machine Learning Demystified
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Define Relationships
employedBy
Model created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
13. IBM Watson / AI for IA's: Machine Learning Demystified
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Relation type
employedBy
employedBy
Amanda works at IBM.
She has worked for the company for 15 years.
Model created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
14. IBM Watson / AI for IA's: Machine Learning Demystified
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Continue: Create Dictionaries, Rules and More…
Amanda works at IBM.
She has worked for the company for 15 years.
EmployedBy ORGANIZATION
Model created by Angela Swindell, Visual
Designer, IBM’er on Watson Knowledge Studio
15. IBM Watson / AI for IA's: Machine Learning Demystified
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This looks familiar?
• It is IA at it’s heart
• Organizing huge amounts of information
• Requires deep understanding of the content
• Taxonomies and ontologies come to life
16. IBM Watson / AI for IA's: Machine Learning Demystified
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Enormous amount of work.
Only as good as data
and time spent improving it.
17. IBM Watson / AI for IA's: Machine Learning Demystified
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Comparison of Machine Training
Training Duration Knowledge / Accuracy
Manual Months to years Best
Supervised
ML
Weeks to months High potential
Unsupervised
ML
Days to weeks Core knowledge only
18. IBM Watson / AI for IA's: Machine Learning Demystified
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Supervised (by a human) Machine Learning
Watson Knowledge Studio, Supervised Machine Learning:
https://www.ibm.com/us-en/marketplace/supervised-machine-learning
19. IBM Watson / AI for IA's: Machine Learning Demystified
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Knowledge and Accuracy
• How important is accuracy?
• Consider a reverse card sorting exercise
20. IBM Watson / AI for IA's: Machine Learning Demystified
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Across industries – does accuracy vary?
• Government safety compliance
• Financial compliance
• Ecommerce chat bot
21. IBM Watson / AI for IA's: Machine Learning Demystified
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Why does training take so long?
• Create algorithms
• Gather documents
• Create ground truth (annotation)
• Run training
• Improve and test again
• Repeat (new information, etc.)
22. IBM Watson / AI for IA's: Machine Learning Demystified
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Dependent on Experts
• Subject Matter Experts (SME’s) Availability
• Experience in Training varies
– Close collaboration
23. IBM Watson / AI for IA's: Machine Learning Demystified
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“The goal is not just the fastest
but the most productive
machine-learning platform for researchers.”
- Pradeep Dubey,
an Intel Fellow at the Intel Labs division
http://www.intel.com/content/www/us/en/analytics/machine
-learning/the-race-for-faster-machine-learning.html
24. IBM Watson / AI for IA's: Machine Learning Demystified
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Saving Time
Researcher’s office
subject to bookalanches
25. IBM Watson / AI for IA's: Machine Learning Demystified
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Cancer Burden in Sub-Saharan Africa
• Risk of getting cancer
and Risk of Dying
~same
The Cancer Atlas http://canceratlas.cancer.org/the-burden/
26. IBM Watson / AI for IA's: Machine Learning Demystified
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What if we could reduce the burden?
• Evidence based medicine available to every physician
• Making more informed treatment decisions
• Helping doctors (not replacing)
IBM Watson for Oncology
27. IBM Watson / AI for IA's: Machine Learning Demystified
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Saving Time
Result of ML are more highly trained
specialists
Not an “all knowing” being
28. Humans teach what we feel is important… teach them to share our values.
Super knowing - not super doing
Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
29. IBM Watson / AI for IA's: Machine Learning Demystified
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Optimist’s guide to the robot apocalypse - @sarahfkessler
“The optimist’s guide to the robot apocalypse” by Sarah Kessler. March 09, 2017. QZ.
@sarahfkessler https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
30. IBM Watson / AI for IA's: Machine Learning Demystified
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Examples
of AI and Cognitive Computing
31. IBM Watson / AI for IA's: Machine Learning Demystified
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Strategic Games
• 1997 Chess, IBM
• 2016 Go, Google
Floor goban, 2007, By Goban1 https://commons.wikimedia.org/wiki/File:FloorGoban.JPG
Graphic, Science Magazine: http://www.sciencemag.org/news/2016/03/update-why-week-s-man-
versus-machine-go-match-doesn-t-matter-and-what-does
32. IBM Watson / AI for IA's: Machine Learning Demystified
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Self Driving (autonomous) vehicles
Junior, a robotic Volkswagen Passat, in a parking lot at Stanford University, 24
October 2009, By: Steve Jurvetson
https://en.wikipedia.org/wiki/File:Hands-free_Driving.jpg
33. IBM Watson / AI for IA's: Machine Learning Demystified
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Understanding human speech
• Watson developed for quiz show Jeopardy!
• Won against champions in 2011 for $1 million
https://en.wikipedia.org/wiki/Watson_(computer)
Video: “IBM's Watson Supercomputer Destroys Humans in Jeopardy | Engadget”
https://www.youtube.com/watch?v=WFR3lOm_xhE
34. IBM Watson / AI for IA's: Machine Learning Demystified
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Automating labeling of birdsongs
“Comparison of machine learning methods applied to birdsong element classification” by David
Nicholson. Proceedings of the 15th Python in Science Conference (SCIPY 2016).
http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf
Photo by Gallo71 (Own work) [Public domain], via Wikimedia Commons
https://commons.wikimedia.org/wiki/File%3ARbruni.JPG
35. IBM Watson / AI for IA's: Machine Learning Demystified
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Image Recognition – Google Photos
Carol’s search for “cats” on her Photos account.
She likes Lacey and Magic quite a bit and being sisters, they like each other.
36. IBM Watson / AI for IA's: Machine Learning Demystified
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Automating Repetitive Work
• Highlight possible issues
• Radiologist confirms
https://www.technologyreview.com/s/600706/ibms-automated-
radiologist-can-read-images-and-medical-records/
37. IBM Watson / AI for IA's: Machine Learning Demystified
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88,000 retina images
• Watson knows what a healthy eye
looks like
• Glaucoma is the second leading
cause of blindness worldwide
– 50% of cases go undetected
https://twitter.com/IBMWatson/status/844545761740292096
38. IBM Watson / AI for IA's: Machine Learning Demystified
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Automation of repetitive inhuman tasks
• Bank in Brazil with 50 different products (!!)
• CSR needs help
• Able to serve that customer much better
Paraphrase from Vanitha Narayanan, chairman of IBM India, in
http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
39. IBM Watson / AI for IA's: Machine Learning Demystified
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American Nightmare: Tax Day
https://www.hrblock.com/lp/fy17/hrblock-and-watson.html
40. IBM Watson / AI for IA's: Machine Learning Demystified
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Conversations for Easy ordering
• Order via text, email, Facebook
Messenger or with a Slackbot
• Cognitive pieces:
– Speech-to-text
– Chat
– API’s in backend
Story: http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-
%E2%80%9CEasy-Button%E2%80%9D-Life-IBM-Watson
Photo: Easy Button from Staples: http://www.staples.com/Staples-Easy-Button/product_606396
41. IBM Watson / AI for IA's: Machine Learning Demystified
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Where’s the IA? Consider Chatbots
• Hierarchy of information
• Mapping between questions
and responses
– Expected language
– Appropriate automated
responses
– When to escalate
to a human
https://www.pexels.com/photo/close-up-of-mobile-phone-248512/
https://www.amazon.com/Amazon-Echo-Bluetooth-Speaker-with-WiFi-Alexa/dp/B00X4WHP5E
https://www.ibm.com/watson/developercloud/doc/conversation/index.html
42. IBM Watson / AI for IA's: Machine Learning Demystified
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Personality Insights – Watson – Analyzing @carologic
IBM Watson Developer Cloud, Personality Insights
https://personality-insights-livedemo.mybluemix.net/
43. IBM Watson / AI for IA's: Machine Learning Demystified
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Tone Analyzer - Watson
IBM Watson Developer Cloud, Tone Analyzer
https://tone-analyzer-demo.mybluemix.net/
44. IBM Watson / AI for IA's: Machine Learning Demystified
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What it is not
• Optical character recognition
• Now considered routine computing
Portable scanner and OCR (video)
https://en.wikipedia.org/wiki/File:Portable_scanner_and_OCR_(video).webm
45. IBM Watson / AI for IA's: Machine Learning Demystified
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Ethics in AI
46. IBM Watson / AI for IA's: Machine Learning Demystified
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How might we…
• build systems that have ethical and moral foundation?’
• that are transparent to users?
• teach mercy and justice of law?
• extend and advance healthcare?
• increase safety in dangerous work?
Grady Booch, Scientist, philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
47. IBM Watson / AI for IA's: Machine Learning Demystified
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So that we trust machines just as much
as a well-trained human?
48. IBM Watson / AI for IA's: Machine Learning Demystified
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AI will
“extend human experience in profound ways”
- Grady Booch, Scientist, philosopher, IBM’er
Grady Booch, Scientist, philosopher, IBM’er
https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
49. IBM Watson / AI for IA's: Machine Learning Demystified
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How do we evolve the practice of IA
to deal with the new issues
these technologies bring
and the new information that is created?
50. IBM Watson / AI for IA's: Machine Learning Demystified
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Cognitive computers are
• Knowledgeable about what taught
• Aware of nuances
• Control ONLY what we give them control of
• Continue to learn with more data
51. Remember: “We can unplug the machines!”
Grady Booch, Scientist, philosopher, IBM’er https://www.ted.com/talks/grady_booch_don_t_fear_superintelligence
52. IBM Watson / AI for IA's: Machine Learning Demystified
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Explore the technology
Try the tools
Pair with others
IBM Watson Developer Tools (free trials):
https://console.ng.bluemix.net/catalog/?categ
ory=watson
53. IBM Watson / AI for IA's: Machine Learning Demystified
@carologic / #ias17 IA Summit 2017
Contact Carol
in/CarolJSmith
@Carologic
slideshare.net/carologic
54. IBM Watson / AI for IA's: Machine Learning Demystified
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Additional Information
and Resources
55. IBM Watson / AI for IA's: Machine Learning Demystified
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“The biggest challenge here is “understanding
people, not just what they vocalize,”....
Our motivations are often not expressed upfront,
yet it is key to understanding what people want to
get done.”
- Rob High, IBM fellow and Watson CTO
https://techcrunch.com/2017/02/27/for-ibms-cto-for-watson-not-a-
lot-of-value-in-replicating-the-human-mind-in-a-computer/
56. IBM Watson / AI for IA's: Machine Learning Demystified
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3 Guiding Principles – Ethical AI
• Purpose
– Aid humans, not replace them.
– Symbiotic relationship
• Transparency
– How AI trained, and what data was used "The human needs to remain
in control of the system"
• Skills
– Built with people in the industry,
– Human workers trained on how to use these tools to their advantage
“3 guiding principles for ethical AI, from IBM CEO Ginni Rometty” by Alison DeNisco.
January 17, 2017, Tech Republic http://www.techrepublic.com/article/3-guiding-
principles-for-ethical-ai-from-ibm-ceo-ginni-rometty/
57. IBM Watson / AI for IA's: Machine Learning Demystified
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Should work to Reduce Waste
• Sharing of models, annotators, algorithms not desirable
(currently):
– Huge amount of work
– Proprietary information
• Benefits are not clear to business (yet):
– “A rising tide lifts all boats"
– Build on others work
– Solve more interesting problems
58. IBM Watson / AI for IA's: Machine Learning Demystified
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Watson is a cognitive technology that can think like a human.
• Understand
• Analyze and interpret all kinds of data
• Unstructured text, images, audio and video
• Reason
• Understand the personality, tone, and emotion of content
• Learn
• Grow the subject matter expertise in your apps and systems
• Interact
• Create chat bots that can engage in dialog
https://www.ibm.com/watson/
59. IBM Watson / AI for IA's: Machine Learning Demystified
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More on Strategic Games
Graphic, Science Magazine: http://www.sciencemag.org/news/2016/03/update-why-week-s-man-
versus-machine-go-match-doesn-t-matter-and-what-does
60. IBM Watson / AI for IA's: Machine Learning Demystified
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The Job Question
• Make new economies
and opportunities – potentially:
– Create jobs
– Entire new fields
• Some jobs will be lost
– What can we do to mitigate
this?
Jobs that no longer exist: The Lector http://www.ranker.com/list/jobs-that-no-
longer-exist/coy-jandreau
61. IBM Watson / AI for IA's: Machine Learning Demystified
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Additional Resources
• “How IBM is Competing with Google in AI.” The Information. https://www.theinformation.com/how-ibm-is-
competing-with-google-in-ai?eu=2zIDMNYNjDp7KqL4YqAXXA
• “The business case for augmented intelligence” https://medium.com/cognitivebusiness/the-business-case-
for-augmented-intelligence-36afa64cd675
• “Comparison of machine learning methods applied to birdsong element classification” by David Nicholson.
Proceedings of the 15th Python in Science Conference (SCIPY 2016).
http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf
• “Staples’ “Easy Button” Comes to Life with IBM Watson” in Business Wire, October 25, 2016.
http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-
Button%E2%80%9D-Life-IBM-Watson
• “How Staples Is Making Its Easy Button Even Easier With A.I.” by Chris Cancialosi, Forbes.
https://www.forbes.com/sites/chriscancialosi/2016/12/13/how-staples-is-making-its-easy-button-even-easier-
with-a-i/#4ae66e8359ef
• “Inside Intel: The Race for Faster Machine Learning”
http://www.intel.com/content/www/us/en/analytics/machine-learning/the-race-for-faster-machine-
learning.html
62. IBM Watson / AI for IA's: Machine Learning Demystified
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More Resources
• “Update: Why this week’s man-versus-machine Go match doesn’t matter (and what does)” by Dana
Mackenzie. Science Magazine. Mar. 15, 2016 http://www.sciencemag.org/news/2016/03/update-why-week-
s-man-versus-machine-go-match-doesn-t-matter-and-what-does
• “For IBM’s CTO for Watson, not a lot of value in replicating the human mind in a computer.” by Frederic
Lardinois (@fredericl), TechCrunch, Posted Feb 27, 2017. https://techcrunch.com/2017/02/27/for-ibms-cto-
for-watson-not-a-lot-of-value-in-replicating-the-human-mind-in-a-computer/
• “Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You” Most Powerful Women by
Michelle Toh. Mar 02, 2017. Fortune. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
• “Facebook scales back AI flagship after chatbots hit 70% f-AI-lure rate - 'The limitations of automation‘” by
Andrew Orlowski. Feb 22, 2017. The Register https://www.theregister.co.uk/2017/02/22/facebook_ai_fail/
• “Microsoft is deleting its AI chatbot's incredibly racist tweets” by Rob Price. Mar. 24, 2016. Business Insider
UK. http://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3
Special Thanks: Soundtrack to 'Run Lola Run', 1998 German thriller film written and directed by Tom Tykwer,
and starring Franka Potente as Lola and Moritz Bleibtreu as Manni. Soundtrack by Tykwer, Johnny Klimek, and
Reinhold Heil
63. IBM Watson / AI for IA's: Machine Learning Demystified
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Even More Resources
• “IBM’s Automated Radiologist Can Read Images and Medical Records” by Tom Simonite, February 4, 2016.
Intelligent Machines, MIT Technology Review. https://www.technologyreview.com/s/600706/ibms-
automated-radiologist-can-read-images-and-medical-records/
• “The IBM, Salesforce AI Mash-Up Could Be a Stroke of Genius” by Adam Lashinsky, Mar 07, 2017. Fortune.
http://fortune.com/2017/03/07/data-sheet-ibm-salesforce/
• "Google can now tell you're not a robot with just one click" by Andy Greenberg. Dec. 3, 2014. Security:
Wired. https://www.wired.com/2014/12/google-one-click-recaptcha/
• “Essentials of Machine Learning Algorithms (with Python and R Codes)” by Sunil Ray, August 10, 2015.
Analytics Vidhya. https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/
• IBM on Machine Learning https://www.ibm.com/analytics/us/en/technology/machine-learning/
• “At Davos, IBM CEO Ginni Rometty Downplays Fears of a Robot Takeover” by Claire Zillman, Jan 18, 2017.
Fortune. http://fortune.com/2017/01/18/ibm-ceo-ginni-rometty-ai-davos/
• “Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You” by Michelle Toh. Mar 02,
2017. Fortune. http://fortune.com/2017/03/02/google-ibm-artificial-intelligence/
64. IBM Watson / AI for IA's: Machine Learning Demystified
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Yes, even more resources
• Video: “IBM Watson Knowledge Studio: Teach Watson about your unstructured data”
https://www.youtube.com/watch?v=caIdJjtvX1s&t=6s
• “The optimist’s guide to the robot apocalypse” by Sarah Kessler, @sarahfkessler. March 09, 2017. QZ.
https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
• “AI Influencers 2017: Top 30 people in AI you should follow on Twitter" by Trips Reddy @tripsy, Senior
Content Manager, IBM Watson . February 10, 2017 https://www.ibm.com/blogs/watson/2017/02/ai-
influencers-2017-top-25-people-ai-follow-twitter/
• “3 guiding principles for ethical AI, from IBM CEO Ginni Rometty” by Alison DeNisco. January 17, 2017,
Tech Republic http://www.techrepublic.com/article/3-guiding-principles-for-ethical-ai-from-ibm-ceo-ginni-
rometty/
• "Transparency and Trust in the Cognitive Era" January 17, 2017 Written by: IBM THINK Blog
https://www.ibm.com/blogs/think/2017/01/ibm-cognitive-principles/
• "Ethics and Artificial Intelligence: The Moral Compass of a Machine“ by Kris Hammond, April 13, 2016.
Recode. http://www.recode.net/2016/4/13/11644890/ethics-and-artificial-intelligence-the-moral-compass-of-
a-machine
65. IBM Watson / AI for IA's: Machine Learning Demystified
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Last bit: I promise
• "The importance of human innovation in A.I. ethics" by John C. Havens. Oct. 03, 2015
http://mashable.com/2015/10/03/ethics-artificial-intelligence/#yljsShvAFsqy
• "Me, Myself and AI" Fjordnet Limited 2017 - Accenture Digital. https://trends.fjordnet.com/trends/me-myself-
ai
• "Testing AI concepts in user research" By Chris Butler, Mar 2, 2017. https://uxdesign.cc/testing-ai-concepts-
in-user-research-b742a9a92e55#.58jtc7nzo
• "CMU prof says computers that can 'see' soon will permeate our lives“ by Aaron Aupperlee. March 16, 2017.
http://triblive.com/news/adminpage/12080408-74/cmu-prof-says-computers-that-can-see-soon-will-
permeate-our-lives
• “The business case for augmented intelligence” by Nancy Pearson, VP Marketing, IBM Cognitive.
https://medium.com/cognitivebusiness/the-business-case-for-augmented-intelligence-
36afa64cd675#.qqzvunakw
66. IBM Watson / AI for IA's: Machine Learning Demystified
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Definition: Artificial Intelligence
• Artificial intelligence (AI) is intelligence exhibited by machines.
• In computer science, an ideal "intelligent" machine is a flexible rational agent that
perceives its environment and takes actions that maximize its chance of success
at some goal.[1] Colloquially, the term "artificial intelligence" is applied when a
machine mimics "cognitive" functions that humans associate with other human
minds, such as "learning" and "problem solving".[2]
• Capabilities currently classified as AI include successfully understanding human
speech,[4] competing at a high level in strategic game systems (such as Chess
and Go[5]), self-driving cars, and interpreting complex data.
Wikipedia: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
67. IBM Watson / AI for IA's: Machine Learning Demystified
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Definition: The Singularity
• If research into Strong AI produced sufficiently intelligent software, it might be able to reprogram
and improve itself. The improved software would be even better at improving itself, leading to
recursive self-improvement.[245] The new intelligence could thus increase exponentially and
dramatically surpass humans. Science fiction writer Vernor Vinge named this scenario
"singularity".[246] Technological singularity is when accelerating progress in technologies will
cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and
control, thus radically changing or even ending civilization. Because the capabilities of such an
intelligence may be impossible to comprehend, the technological singularity is an occurrence
beyond which events are unpredictable or even unfathomable.[246]
• Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in
digital technology) to calculate that desktop computers will have the same processing power as
human brains by the year 2029, and predicts that the singularity will occur in 2045.[246]
Wikipedia: https://en.wikipedia.org/wiki/Artificial_intelligence#cite_note-Intelligent_agents-1
68. IBM Watson / AI for IA's: Machine Learning Demystified
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Definition: Machine Learning
• Ability for system to take basic knowledge (does not mean simple or non-complex) and apply that
knowledge to new data
• Raises ability to discover new information
• Find unknowns in data
• https://en.wikipedia.org/wiki/Machine_learning
More Definitions
• Algorithm: a process or set of rules to be followed in calculations or other problem-solving operations,
especially by a computer. https://en.wikipedia.org/wiki/Algorithm
• Natural Language Processing (NLP): https://en.wikipedia.org/wiki/Natural_language_processing
69. IBM Watson / AI for IA's: Machine Learning Demystified
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Definition: Dictionary
Hinweis der Redaktion
More recently,
The Terminator, Short Circuit, 2001 Space Odyssey, The Matrix, Metropolis
Westworld
Python
Decision Tree
AI - intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents“ – Wikipedia
CC - simulation of human thought processes in a computerized model. CC involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works.
ML - is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
NLP - field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages and, in particular, concerned with programming computers to fruitfully process large natural language corpora.
API - set of routines, protocols, and tools for building software applications. An API specifies how software components should interact. Additionally, APIs are used when programming graphical user interface (GUI) components. – Wikipedia
Metropolis (1927), 2001 Space Odyssey (1968), War Games (1983), Blade Runner (1982), The Terminator (1984), Short Circuit (1986), The Matrix (1999), Ex Machina (2015),
Training
Don’t learn like a typical human
Only what they need to know
Provide body of knowledge for ground-truth
curated
representative
used to compare further knowledge
The machine learning initial analysis includes identifying entities by type (person, organization) and then by classifying them into groups - for example “IBM” and “Big Blue” are both ways to refer to IBM the company. Relationships can also be identified - for example between a person (an employee) and IBM. Dictionaries are also used to define terms such as “apple”. Apple can mean a fruit, multi-national corporation, or a type of computer - which is it in these documents?
The machine learning initial analysis includes identifying entities by type (person, organization) and then by classifying them into groups - for example “IBM” and “Big Blue” are both ways to refer to IBM the company. Relationships can also be identified - for example between a person (an employee) and IBM. Dictionaries are also used to define terms such as “apple”. Apple can mean a fruit, multi-national corporation, or a type of computer - which is it in these documents?
Rules based learning - complexity in that a rule is a rule
If you say for example 4 digit number + capital word matched from dictionary + capital word matched from dictionary = vehicle
Then every time that event occurs in your data it is labeled vehicle. Might be fine if a narrow set of information (vehicle incident reports from NISTA)
Might be require major rework if broader.
Skills Needed
Manual: Coder, NLP and SME
Supervised ML: NLP and SME
Unsupervised ML: BA and coder support
Consider a reverse card sorting exercise
30 participants
How important is it that they all get it right every time?
Consider your industry
Government safety compliance
Accidents related to this tire?
Financial compliance
Accounts with connections to this organization?
Ecommerce chat bot
Women’s pants with pockets?
When carefully (or not so carefully) piled books succumb to gravity
Grew up with bookalanches occurring regularly
Stepfather is an oncologist – would bring home piles of articles, papers, books and more.
He reads everything he can get his hands on. He never stops trying to understand and fight cancer.
Late stage of disease at diagnosis and lack of treatment
Analyzes a patient’s medical information against a vast array of data and expertise to provide evidence-based treatment options.
Saving some trees and reducing bookalanches
IBM’s Deep Blue beat world chess champion Garry Kasparov in a 6 game match
Google's AlphaGo beat human world Go champion Lee Sedol, 4:1
Developed initially to answer Jeopardy! questions
IBM's Watson named after IBM's first CEO, industrialist Thomas J. Watson.
“Comparison of machine learning methods applied to birdsong element classification” by David Nicholson. Proceedings of the 15th Python in Science Conference (SCIPY 2016). http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf
“Analysis of birdsong (for neuroscience or the many other fields that study this behavior) typically focuses on "syllables" or "notes", recurring elements in the song… Each individual has a unique song that bears some similarity to the song of the bird that tutored it, but is not a direct copy. To analyze song, experimenters label syllables by hand. Typically the experimenter records one bird at a time while carrying out a behavioral experiment. However, each songbird produces thousands of songs a day, more than can be labeled. In order to deal with this mountain of data, some labs have developed automated analyses.”
David Nicholson trained a classifier on syllables of one bird’s song to automate labeling of those syllables (same bird).
This was not to train a classifier to distinguish the song of one bird from another.
Specialists spend more time on more complex patients
IBM’s Avicenna software highlighted possible embolisms on this CT scan in green, finding mostly the same problems as a human radiologist who marked up the image in red.
IBM Research Australia is working to help stop this ‘silent thief of sight’ by teaching Watson to detect it. After learning from 88,000 retina images, Watson can understand what a healthy eye looks like, and identify abnormalities that indicate of the onset of eye diseases like glaucoma. In the future, this early detection technology could help keep glaucoma out of sight for millions.
Pull data from customer record
System suggests answers from chat
Find relevant information faster
Reorder
Track shipments
Chat with CSR
http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-Button%E2%80%9D-Life-IBM-Watson
“Simplifies the customers’ shopping experience, allowing them to quickly reorder supplies, track shipments or chat about customer service needs.”
Staples “Easy Button” office supply reordering system which integrates IBM’s Watson technology to simplify office supply management for Staples Business Advantage Customers
teach to discern between right and wrong?
letter vs. spirit of law?
Take set of knowledge we give them and apply to new data
Help humans discover patterns and find unknown
The Job: To read to large rooms of factory workers slaving away at remedial tasks for hours on end. Lectors were sometimes even hired with pooled money from the factory workers themselves for their entertainment.
Who Did It: Well spoken gentlemen.
Why It Went Away: A whole smorgasbord of reasons from the radio, to the Walk-Man, iPhones, iPods, podcasts...
By Coy Jandreau - user uploaded image